M.D Stefano Coiro
email: stefano.coiro@hotmail.it

M.D Nicolas Girerd
email: n.girerd@chru-nancy.fr

M.D John J V Mcmurray
email: john.mcmurray@glasgow.ac.uk

M.D Bertram Pitt
email: bpitt@med.umich.edu

M.D Karl Swedberg
email: karl.swedberg@gu.se

M.D Dirk J Van Veldhuisen
email: d.j.van.veldhuisen@umcg.nl

M.S Zohra Lamiral
email: z.lamiral@chru-nancy.fr

M.D Patrick Rossignol
email: p.rossignol@chru-nancy.fr

M.D Faiez Zannad
email: f.zannad@chru-nancy.fr

Diuretic therapy as prognostic enrichment factor for clinical trials in patients with heart failure with reduced ejection fraction

Keywords: Heart failure with reduced ejection faction; eplerenone, loop diuretics, heart failure hospitalization, prognostic enrichment criteria

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

List of abbreviations

Introduction

In event-driven trials in heart failure (HF), it has been common to enroll patients at heightened risk of disease-related outcomes by enriching for selected baseline characteristics associated with these outcomes e.g. demographics (such as age), medical history (e.g. of prior HF hospitalization) and laboratory data (e.g. natriuretic peptide blood concentrations).

Prognostic enrichment strategies aims at identifying patient subgroups with high event-rate in the course of the clinical study; those procedures considerably reduce the sample sizes needed to show a treatment effect, also increasing the power of the study [START_REF] Fda | Enrichment strategies for clinical trials to support determination of effectiveness of human drugs and biological products guidance for industry[END_REF].

Hospitalization for HF is associated with high event-rates in terms of mortality and HF readmissions, independently of left ventricular ejection fraction (LVEF) [START_REF] Bello | Influence of previous heart failure hospitalization on cardiovascular events in patients with reduced and preserved ejection fraction[END_REF][START_REF] Solomon | Influence of nonfatal hospitalization for heart failure on subsequent mortality in patients with chronic heart failure[END_REF]; additionally, an inverse relationship between time from HF hospitalization to randomization and event-rates was also observed.

Higher concentrations of B-type natriuretic peptide (BNP) and N-terminal pro-BNP (NT-proBNP) [START_REF] Ibrahim | Natriuretic Peptides as Inclusion Criteria in Clinical Trials: A JACC Heart Failure Position Paper[END_REF] are associated with higher rates of fatal and non-fatal events during follow-up [START_REF] Hartmann | Prognostic impact of plasma N-terminal pro-brain natriuretic peptide in severe chronic congestive heart failure: a substudy of the Carvedilol Prospective Randomized Cumulative Survival (COPERNICUS) trial[END_REF][START_REF] Anand | Prognostic value of baseline plasma amino-terminal pro-brain natriuretic peptide and its interactions with irbesartan treatment effects in patients with heart failure and preserved ejection fraction: findings from the I-PRESERVE trial[END_REF], with a steeper increase in cardiovascular compared to non-cardiovascular events [START_REF] Savarese | Utilizing NT-proBNP for Eligibility and Enrichment in Trials in HFpEF, HFmrEF, and HFrEF[END_REF]. On the other hand, there is no agreed threshold concentration for using these peptides in this way and some comorbidities (e.g. atrial fibrillation) also influence their concentration [START_REF] Savarese | Utilizing NT-proBNP for Eligibility and Enrichment in Trials in HFpEF, HFmrEF, and HFrEF[END_REF].

Diuretics (especially loop diuretics) play a pivotal role in relieving congestion and related symptoms in patients with HF [START_REF] Faris | Diuretics for heart failure[END_REF], with a class I recommendation for this indication according to the latest HF guidelines [START_REF] Yancy | ACCF/AHA Guideline for the Management of Heart Failure[END_REF][START_REF] Ponikowski | ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC[END_REF]. However, many studies have demonstrated that loop diuretic use, especially at high doses, is independently associated with reduced survival in HFrEF patients [START_REF] Eshaghian | Relation of loop diuretic dose to mortality in advanced heart failure[END_REF][START_REF] Martins | Prognostic implications of diuretic dose in chronic heart failure[END_REF][START_REF] Testani | Interaction between loop diureticassociated mortality and blood urea nitrogen concentration in chronic heart failure[END_REF][START_REF] Dini | Effects on survival of loop diuretic dosing in ambulatory patients with chronic heart failure using a propensity score analysis[END_REF][START_REF] Cubbon | Prospective development and validation of a model to predict heart failure hospitalisation[END_REF][START_REF] Damman | Loop diuretics, renal function and clinical outcome in patients with heart failure and reduced ejection fraction[END_REF][START_REF] Ahmed | Heart failure, chronic diuretic use, and increase in mortality and hospitalization: an observational study using propensity score methods[END_REF]. Thus, higher loop diuretic dosages identify patients with HF at particularly high risk of mortality and dose of diuretic could be considered as another approach to augmenting event rates in clinical trials. However diuretic dose has not been compared to alternative approaches to enriching for risk (such as requiring history of hospitalization/elevated natriuretic peptides).

In the present study we examined the association between loop diuretic use (and diuretic dose) and outcomes and compared these to other current enrichment criteria, using data from the Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure (EMPHASIS-HF) [START_REF] Zannad | Eplerenone in Patients with Systolic Heart Failure and Mild Symptoms[END_REF].

Methods

Study design and participants

The design, patient eligibility criteria, study procedures and main results of EMPHASIS-HF have been reported [START_REF] Zannad | Eplerenone in Patients with Systolic Heart Failure and Mild Symptoms[END_REF]. In brief, in this randomized double-blind trial, patients with NYHA functional class II HF and LVEF no greater than 30% (or, if >30 to 35%, a QRS duration of >130 msec on electrocardiography) were randomly assigned to receive eplerenone (up to 50 mg daily) or placebo, in addition to recommended therapy.

Enrollment criteria in EMPHASIS-HF

In EMPHASIS-HF, all patients either had to have a hospitalization for a cardiovascular reason within 6 months or documentation of elevated plasma natriuretic peptide concentrations (i.e. BNP concentration of at least 250 pg/ml or NT-proBNP of at least 500 pg/ml for males and 750 pg/ml for females, as assessed within 15 days of randomization) [START_REF] Zannad | Eplerenone in Patients with Systolic Heart Failure and Mild Symptoms[END_REF]. Cardiovascular hospitalization was defined as follows: heart failure (first or subsequent HF hospitalization), acute myocardial infarction, angina pectoris (unstable), cardiac arrhythmia (atrial fibrillation, atrial flutter, supraventricular arrhythmias, or ventricular arrhythmias), stroke/cerebral vascular accident, or other cardiovascular causes (e.g. hypotension, peripheral vascular disease).

Assessment of diuretic use

Use of diuretics was considered part of standard therapy in EMPHASIS-HF, if clinically indicated to minimize fluid retention [START_REF] Zannad | Rationale and design of the Eplerenone in Mild Patients Hospitalization And SurvIval Study in Heart Failure (EMPHASIS-HF)[END_REF]. Drug name and dose were collected at baseline and during follow-up on case report forms. Furosemide-equivalent doses were calculated, with bumetanide 1 mg or torsemide 20 mg considered equivalent to 40 mg of furosemide [START_REF] Devore | Loop diuretic dose adjustments after a hospitalization for heart failure: insights from ASCEND-HF[END_REF].

Study outcomes

The primary outcome in the trial was the composite of time to first occurrence of death from cardiovascular causes or hospitalization for HF [START_REF] Zannad | Eplerenone in Patients with Systolic Heart Failure and Mild Symptoms[END_REF]. Secondary outcomes were the individual components of the primary outcome, all-cause death, cardiovascular hospitalization, and the composite of death or hospitalization for a cardiovascular reason. Adjudication of the outcomes was carried out by an independent committee according to pre-specified criteria [START_REF] Zannad | Eplerenone in Patients with Systolic Heart Failure and Mild Symptoms[END_REF].

Statistical analysis

For the present analysis, patients were grouped into 3 subgroups according to the main enrichment criterion met at baseline: i) HF-related or, ii) non-HF related (i.e. due to other cardiovascular causes) prior cardiovascular hospitalization, iii) elevated natriuretic peptide blood concentrations. Timing of prior hospitalization for HF or for other cardiovascular causes before enrollment (i.e. within 6 months according to inclusion criteria) was categorized as follows: i) <30 days or ii) 30-180 days prior to randomization. Additionally, patients were grouped according to furosemide-equivalent dose as follows: i) no baseline loop diuretic, ii) furosemideequivalent 1 to 40 mg, iii) furosemide-equivalent >40 mg [START_REF] Damman | Loop diuretics, renal function and clinical outcome in patients with heart failure and reduced ejection fraction[END_REF][START_REF] Ferreira | Reduced Diuretic Dose in Patients Treated With Eplerenone: Data From the EPHESUS Trial[END_REF]. Patients were also grouped according to loop and thiazide diuretic use [i.e. 1) no baseline diuretic, 2) thiazide use, 3) furosemide 1-40 mg, 4) furosemide 1-40 mg + thiazide use, 5) furosemide >40 mg, and 6) furosemide >40 mg + thiazide use], and to additional furosemide dosage subgroups (i.e. no loop diuretic, 1-20 mg, 21-40 mg, 41-80, and >80 mg).

Continuous variables are expressed as mean (± standard deviation) or median (25th-75th percentiles); categorical variables as numbers and percentages. Baseline characteristics were defined in the whole cohort according to the respective enrichment criteria at baseline (i.e. prior HF or cardiovascular hospitalization, elevated natriuretic peptides), and furosemide-equivalent dose. Characteristics were compared among enrichment criteria subgroups, between timing categories within hospitalization subgroups, and among furosemide-equivalent subgroups.

Additionally, proportions of furosemide-equivalent dose categories were defined according to enrichment criteria at baseline and their timing. Comparisons of baseline characteristics were performed by using Student's t-test, Mann-Whitney, ANOVA, and chi-square test for trend, as appropriate.

Risk probabilities for the primary outcome according to enrichment criteria, furosemideequivalent categories, and furosemide-thiazide combinations were calculated in distinct analyses using the Kaplan-Meier method and plotted as survival curves; respective associations with the primary outcome were assessed by univariable Cox proportional hazards models and the subgroup with the lowest event rate were taken as reference. Additionally, associations of enrichment criteria and loop diuretic use with primary and secondary outcomes were also assessed. Multivariable Cox analyses were also performed. Multicollinearity was checked using R function "check_multicolinearity" from Perfomance package, and obtained variance inflation factors indicated no significant collinear relationship. The treatment effect of eplerenone according to enrichment criteria (and their timing), furosemide-equivalent dose, and loopthiazide diuretic combinations on primary and secondary outcomes were assessed in separate analyses by introducing an interaction term within univariable models. Harrell's C-statistics for time-to-event data were used to assess the ability of furosemide to predict the primary outcome, in the total cohort, and in subgroups according to study enrichment criteria.

Associations were expressed as hazard ratios and their 95% confidence interval (HR, 95% CI). A P-value <0.05 was considered statistically significant. Statistical analyses were performed using SAS software, version 9.4 (SAS Institute, Cary, North Carolina) the R software (R Foundation for Statistical Computing).

Results

Patient characteristics

Of the 2737 patients randomized in EMPHASIS-HF, 2722 (99.5%) and 2715 (99.2%) had information available for the prespecified enrichment criteria and furosemide-equivalent dose, respectively, at baseline. The main baseline characteristics are outlined in Table 1 andTable 2. The overlap between furosemide subgroups and selected prognostic enrichment criteria are illustrated in Fig. S1 in Supplementary material.

When compared to patients with a prior hospitalization (HF-related or for other cardiovascular causes), the subgroup enrolled on the basis of elevated natriuretic peptide blood concentrations were more likely to be male, and had a worse clinical profile, including a higher prevalence of diabetes and lower diastolic blood pressure and LVEF at randomization (all Pvalues <0.03) (Table 1). Patients in the subgroup enrolled on the basis of a prior HF hospitalization were more likely to be on a loop diuretic (furosemide-equivalent dose 1-40, >40 mg, and >40 mg + thiazide/thiazide-like diuretic), and less likely to be on a beta-blocker compared to the other patients (all P-values <0.01). Finally, the subgroup with a prior non-HF related cardiovascular hospitalization was more likely to have HF of an ischemic etiology, to be on an thiazide/thiazide-like diuretic, or to have worse renal function as compared to other subgroups (all P-values <0.03).

In the subgroup with a prior HF hospitalization, patients with HF hospitalization <30 days were more likely to have HF due to an ischemic cause, to be on an angiotensin-converting enzyme inhibitors, an angiotensin II receptor blockers or a thiazide/thiazide-like diuretic, to have lower systolic blood pressure and higher LVEF as compared to those with a less recent HF hospitalization; they were also less likely to be on a loop diuretic (furosemide-equivalent dose 1-40 mg) compared to the other HF hospitalization subgroup (all P-values <0.04). There were few imbalances in baseline risk factor relative to the timing of non-HF related cardiovascular hospitalization before randomization (Table 1)

Patients treated with a loop diuretic at baseline (especially those with furosemideequivalent dose >40 mg) were older, more likely to be obese, diabetic, and have an implantable device, but less likely to have an ischemic etiology or to be on a thiazide/thiazide-like diuretic, compared to patients not treated with a loop diuretic at baseline. Patients treated with a loop diuretic also had lower blood pressure and LVEF, and a higher heart rate, compared to those not treated with a loop diuretic (all P-values <0.04) (Table 2).

Patients with loop diuretic at baseline were more likely to have had a previous HF hospitalization when compared to patients not treated with loop diuretic [66.7% (438/657) for furosemide >40 mg, and 58.4% (824/1411) for furosemide 1-40 mg, versus 34.3% (222/647) in patients without diuretics, P-value <0.0001) (Table 2, Fig. S1 in Supplementary Material). With regard to non-HF related cardiovascular hospitalization, the opposite trend was observed [18.4% (121/657) for furosemide >40 mg, and 32.7% (400/1411) for furosemide 1-40 mg, versus 58.8% (317/647) in patients without diuretics, P-value <0.0001]. Differences in terms of elevated natriuretic peptide at baseline were not statistically significant across furosemide subgroups (Pvalue =0.2) (Table 2).

Impact of conventional prognostic enrichment criteria and loop diuretic use on outcomes

After 2 years of follow-up, the risk of cardiovascular death or HF hospitalization was highest among patients with a prior HF hospitalization: 28.5% [95% CI 24.7-32.1%] in those with hospitalization <30 days and 27.5% (95% CI 23.9-30.9%) in those with hospitalization 30-180 days before randomization (Fig. 1A). Lower event rates were observed in patients enrolled using natriuretic peptide (24.0%, 95% CI 17.0-30.5%) or non-HF related cardiovascular hospitalization criteria (20.0% [95% CI 14.2-25.4%] and 14.8% [95% CI 11.5-17.9%] for hospitalization <30 days and 30-180 days before randomization, respectively) (Fig. 1A). When taking patients randomized within 30-180 days of non-HF related cardiovascular hospitalization as reference, a prior HF hospitalization within 30 days (HR 2.04, 95% CI 1.60 to 2.62), or within 30-180 days (HR 1.82, 95% CI 1.42 to 2.33) were both associated with significantly higher risks of the primary outcome (Fig. 2A).

Similarly, taking the subgroup without loop-diuretic at baseline as reference, both patients with a furosemide-equivalent dose >40 mg (HR 3.16, 95% CI 2.43 to 4.11) and 1-40 mg (HR 2.06, 95% CI 1.60 to 2.65) displayed a significantly higher risk of the primary outcome (Figs 1B and2A). Importantly, patients with a furosemide-equivalent dose >40 mg had a very high-risk for event (32.9% at 2 years) which was comparable to or higher than that of patients with a HF hospitalization <30 days (28.5% at 2 years). Similar results were observed by multivariable analyses for both original study inclusion criteria and loop-diuretic subgroups (Fig. S2 in Supplementary material). Additionally, the prognostic accuracy of furosemide use as assessed by Harrell's C-index is statically significant in the total cohort as well as in risk subgroups according to original study enrichment inclusion criteria, with superimposable results (Table 1

in

Supplementary material)

When taking into account subgroups according to loop and thiazide diuretic combinations, thiazide/thiazide-like diuretic use does not seem to modify the risk of adverse outcome conferred by loop diuretic alone, for both furosemide >40 mg (thiazide =32.7% vs. no thiazide 33.0%, HR ≃3.3), and furosemide 1-40 mg (thiazide =27.9% vs. no thiazide 24.4%, HR ≃2.2). The risk associated with thiazide diuretic use alone is comparable to that of patients taking no diuretics (Figs 1C and2B). Finally, a fair stepwise increase in the risk of primary outcome was observed when considering furosemide 1-20, 21-40, 41-80, and >80 mg subgroups (Fig. 1D) Without taking into account timing of hospitalization or loop-diuretic dose, a prior HF hospitalization (non-HF related cardiovascular hospitalization subgroup as reference; HRs >1.15, all P-values <0.001) and loop diuretic use (no baseline loop diuretic as reference; HRs >1.70, all P-values <0.0001) were both significantly associated with the primary and all secondary outcomes (Fig. S3 in Supplementary material). Recent (versus less recentconsidered as reference) non-HF related cardiovascular or HF hospitalization were overall not significantly associated with worse prognosis. (Fig. S3 in Supplementary material).

Effect of eplerenone according to conventional prognostic enrichment criteria and baseline loop-diuretic use

According to enrichment criteria categories, the treatment effect of eplerenone on the primary outcome was significant in both patients randomized within 30 days of an HF hospitalization (HR 0.53, 95% CI 0.40 to 0.70) as well as in patients with natriuretic peptide criteria (HR 0.54, 95% CI 0.30 to 0.95) (Fig. 3A); no significant interaction between treatment effect of eplerenone and enrichment criteria was observed (interaction P-value =0.20) (Fig. 3A).

Both patients with a furosemide-equivalent dose >40 mg (HR 0.65, 95% CI 0.50 to 0.86) and 1-40 mg (HR 0.63, 95% CI 0.51 to 0.79) significantly benefitted from eplerenone treatment with respect to the primary outcome; as for the enrichment criteria analysis, the interaction did not reach statistical significance (interaction P =0.64) (Fig. 3A). Similar results were observed when considering loop-diuretic/thiazide diuretic combinations (interaction P =0.51; Fig. 3B) Overall, interaction analyses between treatment effect of eplerenone and enrichment criteria, loop diuretic (use and dosage), or timing of prior cardiovascular hospitalization (non-HF-related) were not significant for all studied primary and secondary outcomes (Table 2 in Supplementary materials).

Discussion

In this post hoc analysis of the EMPHASIS-HF study, we found that, among patients with HFrEF and mild symptoms, loop diuretics usage (especially at high doses) identified participants with a 2-3 fold greater risk of cardiovascular death or HF hospitalization, which is a similar or greater increment in risk than that conferred by a well-established risk-enrichment criteria such as prior HF hospitalization. The higher risk related to loop diuretic use was consistent for all secondary endpoints, and the treatment effect of eplerenone was not influenced by this background diuretic use or dose.

Prognostic enrichment strategies in heart failure clinical trials

For event-driven studies, prognostic enrichment strategies usually involve identification of patients with a higher probability of having a disease-related endpoint. This approach is intended to permit a smaller sample size as a result of the higher event rate, but assumes that the proportional reduction in events with treatment is maintained [START_REF] Fda | Enrichment strategies for clinical trials to support determination of effectiveness of human drugs and biological products guidance for industry[END_REF]. These risk-enhancing variables usually include clinical and laboratory measurements, medical history, genomic and proteomic measurements.

The concept that a recent hospitalization for HF can identify a high-risk patient population is well-described [START_REF] Solomon | Influence of nonfatal hospitalization for heart failure on subsequent mortality in patients with chronic heart failure[END_REF][START_REF] Bello | Influence of previous heart failure hospitalization on cardiovascular events in patients with reduced and preserved ejection fraction[END_REF], and confirmed in recent HF studies [START_REF] Vaduganathan | Prior Heart Failure Hospitalization, Clinical Outcomes, and Response to Sacubitril/Valsartan Compared With Valsartan in HFpEF[END_REF]. Findings from the Candesartan in Heart failure: Reduction in Mortality and morbidity (CHARM) Program (enrolling 7599 HF patients with or without systolic dysfunction) showed that the magnitude of increased risk of cardiovascular death or HF hospitalization in HFrEF with a prior HF hospitalization before randomization was approximately 60%, and that the time interval between hospitalization and randomization was inversely associated with adverse outcome [START_REF] Bello | Influence of previous heart failure hospitalization on cardiovascular events in patients with reduced and preserved ejection fraction[END_REF]. Another post hoc analysis on the same cohort taking into account HF hospitalizations occurring during study follow-up found similar results in terms of mortality [START_REF] Solomon | Influence of nonfatal hospitalization for heart failure on subsequent mortality in patients with chronic heart failure[END_REF]. Due to differences in statistical methodology between our study and the above post hoc analyses from the CHARM Program (i.e. different reference category, comparison among multiple enrichment criteria), a direct comparison cannot be made. However, even in a worstcase scenario as in the present study (i.e. a prior cardiovascular but not HF-related hospitalization as reference category), our results demonstrated that HF hospitalization within 6 months prior to randomization was associated with a 75% higher risk for the combined outcome, with an inverse relationship between timing of hospitalization and risk of adverse outcome (Fig.

in Supplementary material).

On the other hand, the assumption that a previous HF hospitalization would carry higher risk in HF trials was not confirmed in the TOPCAT trial, showing marked regional differences in terms of primary combined endpoint event-rates between patients randomized from Eastern Europe compared with those enrolled from the Americas (respectively, 14.7 vs. 2.4 per 100 patient-years) [START_REF] Pfeffer | Regional variation in patients and outcomes in the Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist (TOPCAT) trial[END_REF]. This suggest that, although HF hospitalization is generally seen as an objective enrollment criterion, non-adjudicated qualifying hospitalization can lead to inclusion of different patient populations, and subsequent treatment effect heterogeneity [START_REF] Pfeffer | Regional variation in patients and outcomes in the Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist (TOPCAT) trial[END_REF].

With regard to eplerenone treatment effect, a previous post hoc analysis of EMPHASIS-HF showed that the beneficial effect of eplerenone on outcomes was unaffected by the timing of the qualifying cardiovascular hospitalization [START_REF] Girerd | Clinical benefits of eplerenone in patients with systolic heart failure and mild symptoms when initiated shortly after hospital discharge: analysis from the EMPHASIS-HF trial[END_REF]. Similarly, we found no significant overall interaction between eplerenone treatment effect and enrichment criteria.

Diuretic therapy as enrichment factor in heart failure with reduced ejection fraction clinical trials

Loop diuretics are used for relieving congestive HF symptoms and signs, with 80% of HF patients being prescribed this medications [START_REF] Kapelios | Loop diuretics for chronic heart failure: a foe in disguise of a friend?[END_REF]. Although diuretics have long been acknowledged as having positive effects on chronic HF patients, several retrospective studies have highlighted that their use, especially in high doses, is associated with adverse outcome [START_REF] Kapelios | Loop diuretics for chronic heart failure: a foe in disguise of a friend?[END_REF].

As suggested by the current European Guidelines [START_REF] Ponikowski | ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC[END_REF], diuretics might be temporarily discontinued in selected asymptomatic patients without signs of congestion. To this purpose, the Rede Brasileira de Estudos em Insuficiência Cardíaca (ReBIC trial), a multicentre double-blind randomized study which enrolled a cohort of 188 apparently euvolaemic HF outpatients (LVEF ≤45%) on stable low dose of furosemide (40 up to 80 mg/day), recently demonstrated that diuretic withdrawal do not significantly impact on the self-perception of dyspnea and use of additional diuretics up to 90 after randomization [START_REF] Rohde | Short-term diuretic withdrawal in stable outpatients with mild heart failure and no fluid retention receiving optimal therapy: a double-blind, multicentre, randomized trial[END_REF]. However, the study was underpowered to assess the effect of such a strategy on hard clinical endpoints, and larger trials with long-term follow-up are needed.

Despite growing data, the causal relationship between diuretics use and adverse outcome have been challenged on the grounds that a high diuretic dose more likely reflects the severity of the disease rather than a true risk factor among patients with HF and systolic dysfunction (i.e.

"the sicker the patient, the higher the diuretic dose") [START_REF] Mielniczuk | The association between high-dose diuretics and clinical stability in ambulatory chronic heart failure patients[END_REF].

In this respect, Pellicori et al, in a cohort of 1190 HF outpatient with mixed LVEF, demonstrated that loop diuretics did not independently predict adverse outcome at long-term follow-up by multivariable analyses, but rather identifies patients with more advanced HF and level of congestion, which may account for their worse prognosis [START_REF] Pellicori | Cardiac Dysfunction, Congestion and Loop Diuretics: their Relationship to Prognosis in Heart Failure[END_REF].

In any case, the primary aim of our study was not focused on adding further evidence on the prognostic impact of diuretic therapy (which was already demonstrated in several studies as reported above), but rather to directly compare the baseline risk associated with loop-diuretic therapy with that of other baseline factors usually adopted as prognostic enrichment criteria (i.e.

prior HF hospitalization or natriuretic peptide blood concentrations).

Although diuretic dose may be a powerful, simple prognostic enrichment criteria in HFrEF trials, care should be taken to avoid investigators deliberately prescribing the dose required to fit the inclusion criteria, or at least reporting that they have done so. This is also the case for history of HF hospitalization as highlighted above. This may potentially be mitigated by a policy of quality control and data ascertainment. Our results demonstrate that the risk associated with loop-diuretic at least matches or even exceeds that associated with history of HF hospitalization.

On the other hand, it should be noted that "greater risk" does not equal "greater modifiable risk", and a proportion of patients with more advanced HF may be refractory to the benefits of a particular therapy. Clinical trialists should keep from enrolling patients with very high event rates, but rather target intermediate risk populations (the so-called "sweet-spot"), associated with larger treatment effects [START_REF] Cleland | Cardiac resynchronization therapy: are modern myths preventing appropriate use?[END_REF][START_REF] Anand | Prognostic value of baseline plasma amino-terminal pro-brain natriuretic peptide and its interactions with irbesartan treatment effects in patients with heart failure and preserved ejection fraction: findings from the I-PRESERVE trial[END_REF].

Finally, we showed how the stepwise increase in the risk of adverse outcome associated with furosemide use appears to be unaffected by the concomitant use of thiazide; indeed, the risk associated with a given dosage of furosemide (i.e. furosemide >40 and 1-40 mg) is quite comparable to that of respective subgroups contemporarily taking thiazide diuretics (Fig. 1C).

Of note, the risk-rate of adverse outcome associated with thiazide use alone is comparable to that of patients without diuretics at baseline (about 12.0% at 2-year follow-up); that risk is, respectively, about half and one third of that observed in subgroups with furosemide 1-40 and >40 mg (Fig. 1C). This HFrEF subgroup, not taking loop diuretics regularly (or taking only thiazide diuretics) represents about 25% of our total cohort, and similar proportions are observed in more contemporary study [START_REF] Vardeny | peptide; SBP, systolic blood pressure; DBP: diastolic blood pressure; HR, heart rate; LVEF, left ventricular ejection fraction; eGFR. Estimated glomerular filtration rate; HF, heart failure; ICD, implantable cardioverter defibrillator; BMI, body mass index: MI, myocardial infarction; ACE, angiotensin converting enzyme; ARB, Angiotensin II receptor blockers[END_REF]. Further studies are needed to assess whether is still suitable to include that low-risk subgroup in forthcoming HFrEF trial design.

Limitations

This is a post hoc analysis of a randomized clinical trial that was not powered to identify differences in terms of outcomes according loop diuretic use. Additionally, in EMPHASIS-HF, elevated natriuretic peptides were requested only in the absence of a recent cardiovascular hospitalization [START_REF] Zannad | Eplerenone in Patients with Systolic Heart Failure and Mild Symptoms[END_REF], otherwise their concentration was not routinely

Conclusions

Dose of loop diuretics (especially at high doses) identifies a subset of HF patients with high risk of adverse clinical outcomes, a risk similar or greater in magnitude than the risk conferred by other well-established prognostic enrichment factors, namely HF hospitalization and raised natriuretic peptide concentrations. We believe that including diuretic dose as an additional enrichment criterion can be useful in designing future HF trials

Figure captions

Supplementary materials

  HF: heart failure LVEF, left ventricular ejection fraction BNP, B-type natriuretic peptide and NT-proBNP, N-terminal pro-BNP EMPHASIS-HF, Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure HR, hazard ratio 95% CI, 95% confidence interval CHARM, Candesartan in Heart failure: Reduction in Mortality and morbidity ReBIC, Rede Brasileira de Estudos em Insuficiência Cardíaca

Fig. 1 A

 1 Fig. 1 A-B-C-D: Kaplan Meier curves for enrichment criteria -Survival curves for

Fig

  Fig. 2A-B: Enrichment factors and risk of primary outcome -Association of enrichment criteria

Fig. 3A -

 3A Fig. 3A-B: Effect of eplerenone according to enrichment criteria -Forest plot for treatment

Fig. 1

 1 Fig. 1 Venn diagram showing the overlap between furosemide subgroups (>40 mg, 1-40 mg) and

Fig. 2 Fig. 3

 23 Fig. 2 Multivariable Cox proportional hazards models for study enrichment criteria and loop-

Figure 1 Figure 3

 13 Figure 1

Table 1 Patient characteristics according to enrichment criteria (history of HFH within 30 days or between 30 and 180 days prior to randomization, history of CVH within 30 days or between 30 and 180 days prior to randomization, and elevated natriuretic peptide concentrations) History of HFH (1) History of non-HF related CVH (2)

 1

	Elevated
	natriuretic
	peptides (3)

Acknowledgements: the EMPHASIS HF trial was sponsored by Pfizer. SC, NG, PR, FZ are supported by the RHU Fight-HF, a public grant overseen by the French National Research Agency (ANR) as part of the second "Investissements d'Avenir" program (reference: ANR-15-RHUS-0004),

Funding: none

Conflicts of interest/Competing interests: Dr. Girerd received board fees from Novartis and honoraria from Servier. Dr. Rossignol received personal fees (consulting) from Novartis, Relypsa, AstraZeneca, Grünenthal, Stealth Peptides, Fresenius, Vifor Fresenius Medical Care Renal Pharma, Vifor, and CTMA; lecture fees from Bayer and CVRx; and is cofounder of CardioRenal. Dr Zannad received steering committte or advisory board fees from Amgen, AstraZeneca, Bayer, Boehringer, Boston Scientific, Cardior, CVRx, Janssen, Livanova, Merck, Mundipharma, Novartis, NovoNordisk and Vifor Fresenius. Dr Pitt received personal fees from Bayer, KDP pharmaceuticals, Astra Zeneca, Sanofi, Relypsa/Vifor, scPharmaceuticals, stealth peptides, tricida, personal fees from G3 pharmaceuticals. Dr McMurray received fees for his consulting or trial committee work with Abbvie, Amgen, AstraZeneca/Medimmune, Bayer, Bristol Myers Squibb, DalCor, GlaxoSmithKline, Merck, Novartis, Resverlogix, Sanofi-Aventis and Stealth Therapeutics. Dr Swedberg received personal fees from Novartis, AstraZeneca, Pfizer, and Novartis. Dr. Van Veldhuisen received board membership fees or travel expenses from Novartis, Corvia Medical, ARCA Biopharma and Johnson & Johnson. All other authors have no conflicts of interest to declare.


E M Brouwer-Brolsma

D Lucassen

M G De Rijk

A Slote- Graaf

C Perenboom

K Borgonjen

E Siebelink

E J M Fes- Kens

Jeanne H M De Vries

Dietary intake assessment: from traditional paper-pencil questionnaires to technology-based tools

Keywords: Technology-based dietary intake assessment, app, sensors, biomarkers, FFQ, recall, food record, dietary history

Self-reported methods of recall and real-time recording are the most commonly used approaches to assess dietary intake, both in research as well as the healthcare setting. The traditional versions of these methods are limited by various methodological factors and burdensome for interviewees and researchers. Technology-based dietary assessment tools have the potential to improve the accuracy of the data and reduce interviewee and researcher burden. Consequently, various research groups around the globe started to explore the use of technology-based tools. This paper provides an overview of the: 1) most-commonly used and generally accepted methods to assess dietary intake; 2) errors encountered using these methods; and 3) web-based and app-based tools (i.e., Compl-eat TM , Traqq, Dutch FFQ-TOOL TM , and "Eetscore") that have been developed by researchers of the Division of Human Nutrition and Health of Wageningen University during the past years.

1

Assessing dietary intake: Why?

Scurvy was a major cause of disability and mortality among long-distance sailors for decades [START_REF] Carpenter | The discovery of vitamin C[END_REF]. In 1497, the Portuguese explorer Vasco da Gama lead an expedition to India and reported that crew members with scurvy recovered days after eating fresh oranges. Yet, another 150 years passed before scurvy was finally acknowledged as being caused by malnutrition [START_REF] Carpenter | The discovery of vitamin C[END_REF]. Fortunately, our understanding of how diet influences the human body evolved more rapidly during the past decades, and nutrient-related diseases considerably decreased. Accurate dietary assessment played an important role in these developments by generating quantitative information on the intake of foods, energy, and/or nutrients. The demand for quantitative information on dietary intake is still high, now more and more focusing on the exploration of diet-related determinants of today's challenges such as obesity and (age-related) non-communicable diseases (NCD) [START_REF]Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults[END_REF][START_REF]Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015[END_REF]. More specifically, around 39%, 40%, 39% and 9% of the population is faced with one or more cardiometabolic risk factors, e.g., overweight [4], hypertension [5], hypercholesterolemia [6], and/or hyperglycaemia, respectively [7].

Consequently, many studies nowadays focus on the identification of modifiable dietary factors affecting the development of obesity and NCD risk. Nutritional epidemiologists for instance focus on potential associations between dairy consumption and body weight development or diabetes risk using data of large observational cohort studies [START_REF] Brouwer-Brolsma | Dairy shows different associations with abdominal and BMI-defined overweight: Cross-sectional analyses exploring a variety of dairy products[END_REF][START_REF] Brouwer-Brolsma | Dairy product consumption is associated with pre-diabetes and newly diagnosed type 2 diabetes in the Lifelines Cohort Study[END_REF]. Dietary intake is estimated and included in the model as the exposure factor and various health parameters (e.g., body weight, waist circumference, fasting blood glucose and insulin and/or self-reported disease prevalence) are assessed and included in de model as the outcome. In addition, potentially relevant information is obtained on a large range of characteristics related to demographics, lifestyle, medical (family) history, etc. Subsequently, statistical modelling results in e.g., βs showing whether or not an increase in dairy intake is associated with an increase or decrease in body weight, or risk estimate indicating whether or not diabetes risk is associated with a certain dairy intake level (e.g., 2 glasses of milk per day) relative to a reference level (e.g., no milk consumption). Dietary intake assessment is also an important component of dietary intervention studies. By modifying the consumption of a nutrient, food or diet in a controlled way and monitoring the potential impact on a selected health parameter, intervention studies are key to provide more certainty on whether or not there is actual causality between a nutrient, product or dietary pattern and a certain health outcome [START_REF] Staudacher | The challenges of control groups, placebos and blinding in clinical trials of dietary interventions[END_REF]. Dietary assessment is also performed by various national organisations in order to monitor the intake of foods and nutrients of the general population, which serves the formulation and evaluation of food policy [START_REF] Huybrechts | Global comparison of national individual food consumption surveys as a basis for health research and integration in national health surveillance programmes[END_REF]. Finally, a very important non-research related application of dietary assessment is the health-care setting where it is used to prevent or treat diseases caused by malnutrition or disease-related malnutrition. Dietary assessment allows the health-care professional to diagnose and provide feedback on the nutritional status of the patient and to educate the patient to improve dietary habits.

2

Assessing dietary intake: How?

Currently, self-report methods are the most commonly used dietary assessment methods, which can be roughly divided in methods of recall and methods of real-time recording.

Methods of recall.

In research, 24-hour recalls and food frequency questionnaires (FFQ) are the most commonly used methods of recall. In the health-care setting, the dietary history method is the most commonly-used approach.

24-hour recall.

The 24-hour recall is an open-ended method to generate detailed information on all foods and drinks consumed during the previous 24 hours (i.e., actual intake), usually starting with breakfast on the previous day. On the individual level, data of 2-3 24-hour recalls can be used to gain insight in the habitual intake of commonly consumed foods; ≥3 days are needed to capture the day-to-day variation of a variety of nutrients and foods that are episodically consumed such as vitamin A, vitamin C, cholesterol, and fish [START_REF] Willett | Nutritional Epidemiology[END_REF]. The required observation period for interviewees with a stable food pattern is usually shorter than the required observation period for interviewees with a varied food pattern due to less day-to-day variation. At our department, 24h-recalls are often carried-out by trained dietitians, either face-to-face or by telephone. In general, the interview can be completed in approximately 30 minutes, whereas food coding by the dietitian requires another 30-60 minutes. Our dietitians perform the 24-hour recall according the multiple-pass method [START_REF] Moshfegh | The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes[END_REF][START_REF] Blanton | The USDA Automated Multiple-Pass Method accurately estimates group total energy and nutrient intake[END_REF]. Due to the workload related to this method it is expensive to use face-to-face or phone-based 24-hour recalls in research, which limits its use to small-scale studies. Fortunately, recent technological innovations lead to the development of various self-administered web-based 24-hour recalls all over de world. Obviously, it is of key importance that these new tools are just as accurate as the dietitian-guided recalls. So far, validation studies of web-based recalls show promising results, but also clues for further improvements [START_REF] Touvier | Comparison between an interactive web-based self-administered 24 h dietary record and an interview by a dietitian for large-scale epidemiological studies[END_REF][START_REF] Subar | The Automated Self-Administered 24-hour dietary recall (ASA24): a resource for researchers, clinicians, and educators from the National Cancer Institute[END_REF][START_REF] Foster | Validity and reliability of an online self-report 24-h dietary recall method (Intake24): a doubly labelled water study and repeated-measures analysis[END_REF][START_REF] Arab | Eight self-administered 24hour dietary recalls using the Internet are feasible in African Americans and Whites: the energetics study[END_REF][START_REF] Greenwood | Validation of the Oxford WebQ Online 24-Hour Dietary Questionnaire Using Biomarkers[END_REF][START_REF] Wark | Validity of an online 24-h recall tool (myfood24) for dietary assessment in population studies: comparison with biomarkers and standard interviews[END_REF][START_REF] Timon | Comparison of a Web-Based 24-h Dietary Recall Tool (Foodbook24) to an Interviewer-Led 24h Dietary Recall[END_REF][START_REF] Meijboom | Evaluation of dietary intake assessed by the Dutch self-administered web-based dietary 24-h recall tool (Compl-eat) against intervieweradministered telephone-based 24-h recalls[END_REF].

Dietary history method.

The dietary history method is the most commonly used method in the clinic, but less often used in the research setting. Similar to the 24-hour recall, the dietary history is an open-ended method to generate detailed information (i.e., type and amount) of all foods and drinks consumed, and is usually performed by a dietitian. The difference between the two methods is the addressed time-window. Where the 24-hour recall focusses on the previous day, the dietary history aims to assess a typical weekly or monthly pattern. Therefore, a 24-hour recall or food record can be a first step of a dietary history, but additional information on foods, drinks, and meals consumed on other days is warranted to obtain insight in the habitual intake. Information on habitual intake can be obtained by requesting for alternatives for the foods reported during the 24-hour recall; this process may be supported by addressing time and location of food consumption, differences between week days and weekends, cooking methods, etc. Clearly, the dietary history is a comprehensive and time-consuming method and may require up to 30-90 minutes to complete depending on the aim of the interview [START_REF] Moran Fagundez | Diet history: Method and applications[END_REF]; the use of photographs, food models or food packages may aid the procedure. Perceptibly, interviewees with irregular eating patterns are a challenge [START_REF] Bloemberg | The reproducibility of dietary intake data assessed with the cross-check dietary history method[END_REF].

Food Frequency questionnaire.

A Food Frequency Questionnaire (FFQ) is a fixed-food list -with or without portion size descriptions -inquiring for the consumption frequency of foods and beverages over the past month, past three months, or year (i.e., habitual intake). FFQs can be interviewer-based and self-administered. In general, an extensive FFQ that addresses macronutrients and the majority of the micronutrients can be completed in approximately 45 minutes. FFQs are primarily designed to rank interviewees according to their intakes and not to estimate absolute intakes. Nevertheless, in case of nutrients or foods with a large day-to-day variability (e.g., fish and alcohol), an FFQ may be more accurate than other methods also in terms of absolute intakes. Important benefits of an FFQ are that the administration and processing is very efficient. We can easily process several thousand FFQs at once and the output is relatively easy to convert to computer ready-data, making the FFQ a very practical method for use in large-scale studies. However, in contrast to a recall, dietary history or food record, the use of validated FFQs requires intensive preparation before it can be send to the interviewees. The first step involves the identification of food items that are contributing most to the relevant energy and nutrient intakes in the target population, which obviously depends on the research questions to be addressed. To identify these food items, researchers in the Netherlands currently use the results of the Dutch National Food Consumption Survey (DNFCS) [START_REF] Van Rossum | The diet of the Dutch : Results of the first two years of the Dutch National Food Consumption Survey 2012-2016[END_REF] -collected through two 24-h recalls -and generally aim to cover at least 80% of the absolute intake level and between-person variability of each nutrient under study [START_REF] Brouwer-Brolsma | A National Dietary Assessment Reference Database (NDARD) for the Dutch Population: Rationale behind the Design[END_REF]. Thus, each FFQ is tailored depending on the research question(s) and the population of interest. It should be emphasized that this process requires the availability of detailed food consumption data for the population under study, which are not (yet) available for many low-and middle income countries [START_REF] Huybrechts | Global comparison of national individual food consumption surveys as a basis for health research and integration in national health surveillance programmes[END_REF]. The second step involves the validation of the FFQ, which is ideally performed using validated recovery markers/techniques such as urinary nitrogen (for protein), potassium, sodium, and doubly labelled water, which are able to estimate absolute nutrient intakes [START_REF] Jenab | Biomarkers in nutritional epidemiology: applications, needs and new horizons[END_REF]. Blood carotenoids and n-3 fatty acids can be used to assess the relative validity (i.e. ranking) for the intake of fruit/vegetables and fish intake (concentration markers), respectively [START_REF] Brevik | Six carotenoids in plasma used to assess recommended intake of fruits and vegetables in a controlled feeding study[END_REF][START_REF] Al-Delaimy | Plasma carotenoids as biomarkers of intake of fruits and vegetables: individuallevel correlations in the European Prospective Investigation into Cancer and Nutrition (EPIC)[END_REF][START_REF] Saadatian-Elahi | Plasma phospholipid fatty acid profiles and their association with food intakes: results from a crosssectional study within the European Prospective Investigation into Cancer and Nutrition[END_REF]. However, no other markers are available yet [START_REF] Brouwer-Brolsma | Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance[END_REF]. Although the duplicate portion technique could serve as an alternative method for the use of validated biomarkers [START_REF] Trijsburg | Comparison of duplicate portion and 24 h recall as reference methods for validating a FFQ using urinary markers as the estimate of true intake[END_REF], validation studies are often conducted using other self-reported dietary assessment methods (sharing correlated errors) as the reference method (e.g. 24h-recalls, food records) [START_REF] Cade | Development, validation and utilisation of food-frequency questionnaires -a review[END_REF]. Besides this validation step, FFQs also require continuous updating due to new research questions and continuously changing availability of products. Thus, all in all, the development and maintenance of FFQs is a skilled task, time-consuming, and expensive. Fortunately, also this research area substantially developed in terms of automatization during the past years [START_REF] Kristal | Evaluation of web-based, self-administered, graphical food frequency questionnaire[END_REF][START_REF] Fallaize | Online dietary intake estimation: reproducibility and validity of the Food4Me food frequency questionnaire against a 4-day weighed food record[END_REF][START_REF] Labonte | Validity and reproducibility of a web-based, self-administered food frequency questionnaire[END_REF][START_REF] Wise | Design and analysis of food frequency questionnaires--review and novel method[END_REF][START_REF] Molag | Towards Transparent Development of Food Frequency Questionnaires[END_REF].

2.2

Methods of real-time monitoring.

Food record.

Food records are open-ended and generate detailed information (i.e., amount and type) on all foods and drinks consumed during the recording period. Similar to the 24-hour recall, a one day food record provides information on actual food and nutrient intake; 2-3 day food records provide information on the habitual intake of commonly consumed foods on the individual level. More days are needed to cover the nutrients and foods that are less commonly consumed [START_REF] Willett | Nutritional Epidemiology[END_REF]. The completion time of a one-day food record is approximately 30 minutes distributed over the day. In theory, multiple (i.e., 7 day) weighed food records are the most accurate self-reported dietary assessment method; the so-called "gold standard" [START_REF] Cameron | Manual on Methodology for Food Consumption Studies. Methods for Data Collection at an Individual Level[END_REF]. In case of weighed food records, the interviewee is instructed to weigh all foods and drinks consumed, ideally using scales with an accuracy up to 1 gram. Following a demonstration on the weighing and reporting of consumed foods (i.e., food type such as white bread vs. whole-wheat bread, food brands, recipe details) the interviewee receives a simple notebook. A disadvantage of dietary records is that they are prone to reactivity bias, very intrusive for interviewees and also time-consuming and labour-intensive for dietitians due to the food coding.

Weighed food records can be very useful in dietary studies, but weighed food records are not feasible for use in large-scale studies. The non-weighed food record largely follows the same procedure, but is less intrusive as food quantity is estimated, using e.g., standard portion-sizes and household measures. Obviously, this procedure requires more from the dietitian in terms of the interpretation of the portion size estimates and is thus less precise compared to the weighed food record. Fortunately, also for the food record, technological inventions have led to promising innovations, including the use of mobile devices. Whereas the more basic apps still collect dietary intake data through descriptive text [START_REF] Eldridge | Evaluation of New Technology-Based Tools for Dietary Intake Assessment-An ILSI Europe Dietary Intake and Exposure Task Force Evaluation[END_REF], other apps are also exploring the potential of before and after photography, which provides additional information on consumed portion sizes and potentially undocumented foods [START_REF] Boushey | New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods[END_REF].

Duplicate portions.

Similar to the 24-hour recall and food record, the duplicate portion method is openended and provides information on actual intake in case of a 24-hour collection period; ≥3 days may provide information on the habitual intake of commonly consumed foods and nutrients on the individual level. Distinct from the other methods, the duplicate portion method involves the collection of a second identical portion of all foods and drinks consumed -whether in combination with a weighed food record or not -in a cool box. Cool boxes are collected the following day; foods are weighed, homogenised in a blender, freeze dried and chemically analysed for nutrient composition [START_REF] Trijsburg | Comparison of duplicate portion and 24 h recall as reference methods for validating a FFQ using urinary markers as the estimate of true intake[END_REF][START_REF] Trijsburg | BMI was found to be a consistent determinant related to misreporting of energy, protein and potassium intake using self-report and duplicate portion methods[END_REF]. Clearly this method is very intrusive, labour-intensive and expensive, and therefore it is not often used. However, the duplicate portion method may be valuable when local food composition data are lacking, food composition tables do not contain information on specific compounds, validating other self-report dietary assessment methods or biomarkers, or exploring determinants associated with misreporting of dietary intake.

Nutrient and food calculations.

Except for the duplicate portion method, average daily nutrient intakes for the 24-hour recall, dietary history, FFQ and food record are usually calculated by multiplying the consumption frequency with portion sizes (in grams) and nutrient content as indicated in the Dutch food composition table [START_REF]NEVO-tabel[END_REF]. Note that, depending on the design of the FFQ, a weighed estimate of multiple food codes may be assigned to an item due to the fixed nature of the questionnaire.

3

True vs. measured diet: sources of measurement error.

Studies exploring diet-disease associations often show mixed findings [START_REF] Gijsbers | Consumption of dairy foods and diabetes incidence: a dose-response meta-analysis of observational studies[END_REF][START_REF] Schwingshackl | Food Groups and Risk of Hypertension: A Systematic Review and Dose-Response Meta-Analysis of Prospective Studies[END_REF]; varying from null associations, beneficial associations to adverse associations. Inconsistencies may relate to various factors, including study population (e.g., healthy vs. health-compromised population), variation in the exposure (e.g., population with high intakes of a certain food or nutrient vs. population with a low intake) or outcome (e.g., low vs. high prevalence of a certain disease) under study, the covariates considered (e.g. inadequate vs. satisfactory correction for covariates) or the applied statistical approach (e.g., may affect statistical power to detect potential associations). Methodological issues related to the assessment of the exposure (i.e., dietary factor) are also commonly discussed. Indeed, it is indisputable that above described methods have their limitations that introduce measurement error, which can be "intake-related" (reflecting the correlation between the error and true intake) or "person-specific" (errors related to the interviewee's personal characteristics) [START_REF] Kipnis | Structure of dietary measurement error: results of the OPEN biomarker study[END_REF]. Besides, errors can be systematic/differential or random/non-differential [START_REF] Kipnis | Structure of dietary measurement error: results of the OPEN biomarker study[END_REF]. To be more specific, a shared factor for all methods of recall (i.e., recall, dietary history and FFQ) is its sensitivity to memory-related bias. To illustrate, dietary estimates obtained by dietary history have been shown to overestimate the consumption of healthy foods and underestimate the consumption of snacks, drinks and alcoholic beverages (e.g., socially desirable responses). Moreover, although the dietary history aims to obtain information on the habitual diet, the estimated diet may be more likely to reflect the past 7 days rather than the diet over a longer period. Other shared sources of errors for these three methods as well as the non-weighed food record include the inaccurate estimation of portion sizes and errors in food composition tables. An additional source of measurement error for the FFQ is the large supply of available foods, which cannot be fully reflected in a fixed-food list. Additionally, reporting's obtained through food record as well as duplicate portion method may be influenced by the fact that interviewees are made aware of their habits while recording/collecting. To limit this source of error it is therefore important to emphasize that interviewees should not change their usual intake at the time of recording/collecting (reactivity bias). The duplicate portion method is least influenced by abovementioned sources of error: there is no memory-related bias, no bias due to errors in food consumption tables, and errors in portion sizes are also unlikely. Still, interviewees may forget to collect foods resulting in underestimated food intakes [START_REF] Trijsburg | Comparison of duplicate portion and 24 h recall as reference methods for validating a FFQ using urinary markers as the estimate of true intake[END_REF]. So in the end, dietary assessment will give you more or less an indication of what people eat, but it is very difficult to get a very precise estimate.

Assessing dietary intake: Which method to use?

The dietary assessment method to choose eventually depends on your research question and target population [START_REF] Cade | DIET@NET: Best Practice Guidelines for dietary assessment in health research[END_REF]. To select the most appropriate and cost effective method for a specific research question it is important to weigh the benefits and the weaknesses, e.g., available tools, resources and expertise, interviewee burden, researcher burden, costs, and validity and reproducibility. Considerations may relate to the range of foods or nutrients of interest, how the data will be analysed and presented (i.e., group vs. individual level and absolute intakes vs. relative intakes), and to the targeted time-frame (i.e., actual vs. habitual intake and recall vs. real-time recording). In terms of the target population important considerations may relate to the sample size, age of the interviewees (e.g., young children and older adults may experience difficulties when working with some of the tools), educational level/literacy, motivation, ethnicity, disabilities (e.g., vision or hearing problems), country, and available resources and expertise (e.g., internet access or not, availability of dietitians).

5

Innovations.

It may be clear that each tool has it strengths and it weaknesses. Up to 15-20 years ago, above presented methods were completely paper-pencil based, which shifted more and more towards web-based and smartphone-based tools throughout the past decade. The current pace of technological development is very valuable to improve our methods, i.e., reduce sources of error, increase user-friendliness, and decrease workload of dietitians and/or researchers. Due to the absence of a dietitian/researcher, data obtained through web-based/smartphone-based tools are for instance expected to be less biased by social desirable answers. Web-based and smartphone-based tools are also assumed to be less burdensome for the interviewees as they can complete the dietary assessment at a time and location that is convenient for them.

Compl-eat TM .

New technological opportunities allowed us to develop a self-administered Dutch webbased dietary 24-hour recall tool, entitled Compl-eat™ [START_REF] Meijboom | Evaluation of dietary intake assessed by the Dutch self-administered web-based dietary 24-h recall tool (Compl-eat) against intervieweradministered telephone-based 24-h recalls[END_REF]. Contrary to the traditional method, the web-based tool is not guided by a research dietitian. At 6.00 AM, the interviewee receives an invite to complete the recall through e-mail; the invite remains effective until midnight that same day. The tool is introduced by two short instruction videos explaining how to: 1) select food items from the food list (2 min 16 s) and 2) report details (type and amount) of the consumed foods (2 min 26 s). Portion sizes can be reported in commonly-used household measures, standard portion sizes or in grams/litres. Compl-eat™ does not contain images. Identical to the traditional 24h-recall, interviewees are requested to report their dietary intake of the previous day, starting in the morning after waking up till the next morning. Moreover, comparable to the traditional 24h-recall, the web-based tool is based on the multiple-pass method, ensuring proper guidance while reporting the consumed foods [START_REF] Moshfegh | The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes[END_REF][START_REF] Blanton | The USDA Automated Multiple-Pass Method accurately estimates group total energy and nutrient intake[END_REF]. Compl-eat™ contains an extensive food list based on the Dutch food composition table (NEVO) [START_REF]NEVO-tabel[END_REF], including most commonly-used synonyms as well as previously entered foods and recipes. This food list is flexible and can be easily modified in order to be tailored to specific research questions or updated to include new food items. In theory, this food list can be replaced with non-Dutch food lists. Compl-eat™ also comprises a recipe module, which facilitates the reporting of a complete dish by selecting or modifying a standard recipe. Besides, the interviewee has the option to enter all ingredients of an original recipe in combination with the consumption amount of the meal. Yield and retention factors (i.e., retained weight and nutrients after cooking) are automatically taken into account. Interviewees also have the possibility to include notes to clarify their input.

After each eating occasion, interviewees receive prompts to report on commonly omitted foods (i.e., sugar and/or milk in coffee/tea, oils and fats used in the preparation of dishes, snacks/candies and fruits). Generally, all web-based 24-hour recalls are checked by research dietitians for completeness, unusual portion sizes and notes entered by the interviewee. Identified errors and notes are processed according to a standardised protocol, using standard portion sizes and recipes. Interviewees are not contacted for clarifications. Examples of errors include the report of 125 cups of coffee instead of one cup of 125 g. Notes may relate to a food consumed, but could not be identified in the food list. The computation module of Compl-eat™ subsequently calculates food, food groups, and energy and nutrient intakes where different output formats can be selected. Interviewees require on average 40-45 minutes to complete the web-based recall (including login time, watching the instruction videos and entering the food items), which is 10-15 minutes more compared to the traditional recall method. However, the dietitians can process the recalls in 5-10 minutes, whereas approximately 90 minutes are needed to complete the interview and coding according to traditional method.

Traqq.

Recently, the development of the app called "Traqq" was initiated. Traqq can serve as a recall and food record, and can be used to collect data on one or more pre-specified full days. Besides, Traqq can be programmed to send random notifications over a longer period of time. In case of the food record module, interviewees are able to enter consumed foods throughout the day. In case of the recall module, the interviewee receives a notification on the smartphone prompting to complete the recall. By ticking the notification/opening the app, the interviewee obtains access to an extensive food list based on the Dutch food composition table (1463 items) with additional synonyms (1019 items) [START_REF]NEVO-tabel[END_REF]. If desired, this food list can be adjusted to fit different research purposes. Following the selection of a food item, the interviewee is prompted to select a portion size. Portion sizes can be reported in household measures (e.g., cups, spoons, glasses), standard portion sizes (e.g., small, medium, large), and weight in grams. Traqq also contains a "My Dishes" option where the interviewee can select all ingredients of an original recipe in combination with the quantity of the meal consumed. Yield and retention factors (i.e., retained weight and nutrients after cooking) are automatically taken into account. The recall closes after submission of the entered foods; data are stored on a secured server. The validation study of Traqq is currently ongoing with the first results expected early 2020. Screenshots of Traqq are displayed in Figure 1.

5.3

The Dutch FFQ-TOOL TM .

The Dutch FFQ-TOOL TM is a data-driven web-based computer system developed to generate (Figure 2) and process tailored FFQs (Figure 3) -i.e., for nutrients of interest and population under study -by standardized, reproducible, relatively fast and flexible procedures [START_REF] Molag | Towards Transparent Development of Food Frequency Questionnaires[END_REF]. The FFQ-tool has three main functionalities, i.e., 'selection of food items', 'question generation', and 'nutrient and food calculations'. The selection of food items is a semi-automated process. The FFQ-tool uses data from the DNFCS [START_REF] Van Rossum | The diet of the Dutch : Results of the first two years of the Dutch National Food Consumption Survey 2012-2016[END_REF] to tailor the FFQ to the nutrients and population of interest, which is comparable to the procedure used to develop paper-based FFQs. Generally, researchers aim to cover about 80% of the absolute intake level and 80% of the between-person variability of each nutrient under study [START_REF] Eussen | A national FFQ for the Netherlands (the FFQ-NL1.0): development and compatibility with existing Dutch FFQs[END_REF][START_REF] Sluik | A national FFQ for the Netherlands (the FFQ-NL 1.0): validation of a comprehensive FFQ for adults[END_REF]. The FFQ-tool indicates to which extent an item contributes to the total intake or the variation in intake for the nutrient(s) of interest for each aggregation level. Depending on the research question, the researcher subsequently selects the most suitable aggregation level and related food items. Thereafter, the selected food items are automatically translated to standard questions. Once the FFQ is completed, food, and energy and nutrient intake is computed through the computation module of the FFQ-TOOL TM , which is facilitated by attached (Dutch) food composition tables. 5.4 Eetscore.

The "Eetscore" is a self-administered web-based screener to assess habitual diet quality during the previous month. In contrast to above described methods and associated tools, the "Eetscore" is a relatively short FFQ specifically developed to fulfil the demand for a shorter and less burdensome questionnaire. It is not the primary aim to obtain quantitative food or nutrient intakes when administrating the "Eetscore". The "Eetscore" can be completed in approximately 10-15 minutes and therefore interviewee and researcher burden as well as the associated costs are relatively low. The "Eetscore" is also the only tool providing immediate personal dietary advice after submission of the questionnaire. However, if desired, the "Eetscore" can also be administered without the advice module. The "Eetscore" is based on the Dutch Health Diet-index (DHD-index). The DHDindex was developed in 2012 [START_REF] Van Lee | Evaluation of a screener to assess diet quality in the Netherlands[END_REF] by the Division of Human Nutrition and Health of the Wageningen University and based on the Dutch dietary guidelines of 2006 [START_REF]Health Council of the Netherlands: Guidelines for a healthy diet 2006[END_REF].

The first version of the Eetscore FFQ was developed in 2015 and called the Dutch Healthy Diet-FFQ (DHD-FFQ), reflecting the nine (nutrient-based) dietary components of the DHD-index [START_REF] Van Lee | Evaluation of a screener to assess diet quality in the Netherlands[END_REF]. In 2017, the DHD-index was adapted to the Dutch dietary guidelines 2015 [START_REF]Health Council of the Netherlands: Guidelines for a healthy diet 2015[END_REF] which are food-based instead of nutrient-based -and called the Dutch Healthy Diet 2015-index (DHD15-index) [START_REF] Looman | Development and evaluation of the Dutch Healthy Diet index 2015[END_REF]. The DHD15-index includes fifteen components, including vegetables, fruit, whole-grain products, legumes, nuts, dairy, fish, tea, fats and oils, coffee, red meat, processed meat, sweetened beverages and fruit juices, alcohol, and salt. For each component an interviewee can score from 0 to 10; the total score of the DHD15-index ranges from 0 to 150. The scoring depends on the component type, which can be an adequacy component, moderation component, optimum component, qualitative component and ratio component. Adequacy components are foods which require an intake level above a certain cut-off level, including vegetables, fruit, wholegrain products, legumes, nuts, fish and tea. Moderation components are foods that need to be avoided, including red meat, processed meat, sweetened beverages and fruit juices, alcohol, and salt. Optimum components are foods that have been shown to reach an optimal level of intake that is considered most healthy (i.e., nshaped), namely dairy. Qualitative components are foods of which the type matters, i.e., preferably filtered coffee and not unfiltered coffee. In case of ratio components, the scores depend on the replacement of less healthy products by more healthy alternatives, i.e., grain products and fats and oils. In addition to these 15 components of the DHD15-Index, the "Eetscore" comprises one additional component, i.e., the unhealthy choices component. The unhealthy choices component was added based on the guidelines of the Netherlands Nutrition Centre aiming to get insight in dietary intake beyond the Dutch dietary guidelines [54]. Similar to the other methods, the "Eetscore" is likely to be biased by memory-related error. At present, the "Eetscore" is considered adequate for use for interviewees with a Dutch food pattern aged 19 to 69 years. Besides, several patient-specific versions as well as versions suitable for individuals with a lower socioeconomic-status and children are being developed, but these have not been tested yet.

5.5

Sensor-based wearable dietary assessment methods.

Sensor-based wearable dietary assessment tools are assumed to overcome many of the measurement error related to the self-report nature of the above described dietary assessment tools. In current literature, the detection of food intake using sensor-based technology has been most extensively described, primarily focussing on the detection of food intake via sounds of chewing and swallowing (acoustics) [START_REF] Bi | AutoDietary: A Wearable Acoustic Sensor System for Food Intake Recognition in Daily Life[END_REF][START_REF] Lopez-Meyer | Detection of periods of food intake using Support Vector Machines[END_REF][START_REF] Olubanjo | Detecting food intake acoustic events in noisy recordings using template matching[END_REF][START_REF] Päßler | Acoustical method for objective food intake monitoring using a wearable sensor system[END_REF], wrist/arm motion (inertial) [START_REF] Ye | Assisting Food Journaling with Automatic Eating Detection[END_REF][START_REF] Xu | Automatic Eating Detection using head-mount and wrist-worn accelerometers[END_REF][START_REF] Amft | Detection of eating and drinking arm gestures using inertial body-worn sensors[END_REF], skeletal muscle activity and skull vibrations (physiological) [START_REF] Farooq | A novel approach for food intake detection using electroglottography[END_REF], and/or change in electric charge in response to chewing and swallowing (piezoelectric) [START_REF] Kalantarian | A Wearable Nutrition Monitoring System[END_REF]. Sensor-based food type classification appears to be more challenging than food intake identification and has been explored less extensively. Amft and colleagues tested the accuracy of sound-based recognition for apple, potato chips, and lettuce and showed a 94% average accuracy of food classification based on chewing sequences; the mean weight prediction error was lowest for apples (19.4%) and largest for lettuce (31%) (acoustic) [START_REF] Amft | Bite weight prediction from acoustic recognition of chewing[END_REF]. The use of pictures and/or videos (visual) may seem a more straightforward approach in this field [START_REF] Sun | eButton: A Wearable Computer for Health Monitoring and Personal Assistance[END_REF], but correct automatic identification of foods is also still a huge challenge due to the large variety of available foods, complexity of many prepared foods, and diverse conditions to capture the foods (e.g., lighting, position) [START_REF] Puri | Recognition and volume estimation of food intake using a mobile device[END_REF]. In terms of portion size estimation, the use of camera's is developed somewhat more [START_REF] Puri | Recognition and volume estimation of food intake using a mobile device[END_REF][START_REF] Jia | Accuracy of food portion size estimation from digital pictures acquired by a chest-worn camera[END_REF][START_REF] Junqing | A pervasive Dietary Data Recording System[END_REF]. Still, current methods do not allow the use of sensors for detailed quantification of food, energy and nutrient intake for use in nutrition and health research yet. Therefore, in future studies we aim to contribute to this work by piloting various independent sensors to examine whether the combination of two or more sensors can provide a valuable addition to the currently used dietary assessment methods.

Biomarkers

Finally, even though not directly related to the technology-based work described above, work within the division of human nutrition and health also focusses on the identification of nutritional biomarkers as a complementary or alternative measure of dietary intake. Biological markers for dietary intake are considered more objective than the self-reported dietary intake methods, e.g., not affected by memory, social desirability and/or errors in food composition tables. As mentioned earlier, there are few well-validated nutritional biomarkers, but metabolomic techniques now provide a unique opportunity to measure up to thousands of metabolites at once providing valuable information on the food metabolome using a variety of body tissues [START_REF] Brouwer-Brolsma | Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance[END_REF][START_REF] Michielsen | Biomarkers of food intake for cocoa and liquorice (products): a systematic review[END_REF][START_REF] Michielsen | Disentangling the Effects of Monounsaturated Fatty Acids from Other Components of a Mediterranean Diet on Serum Metabolite Profiles: A Randomized Fully Controlled Dietary Intervention in Healthy Subjects at Risk of the Metabolic Syndrome[END_REF].

Conclusion

The methods to assess diet substantially enhanced during the past decades, predominantly in terms of cost-and time-effectiveness, labour-intensiveness and interviewee and researcher burden. However, novel tools still share various methodological issues with the traditional self-report methods. New technology-based opportunities will help to further improve current tools (e.g., by updating app-based recalls such as Traqq with photo, video and/or chat functionalities to facilitate better food identification and portion size estimations), develop new wearable sensor-based tools to quantify food, energy, and nutrition intake, identify novel biomarkers, and potentially even integration of the various approaches.

Figure 1 .

 1 Figure 1. Screenshots of Traqq.

Figure 2 .

 2 Figure 2. Overview of the Dutch FFQ-TOOL TM to develop and process FFQs.Figure adapted from PhD-thesis Marja Molag entitled "Towards Transparent Development of Food Frequency Questionnaires. Scientific basis of the Dutch FFQ-TOOL TM : a computer system to generate, apply and process FFQs"[38].

  Figure 2. Overview of the Dutch FFQ-TOOL TM to develop and process FFQs.Figure adapted from PhD-thesis Marja Molag entitled "Towards Transparent Development of Food Frequency Questionnaires. Scientific basis of the Dutch FFQ-TOOL TM : a computer system to generate, apply and process FFQs"[38].

Figure 3 .

 3 Figure 3. Software and databases in the Dutch FFQ-TOOL TM to generate and process FFQs.Figure adapted from PhD-thesis Marja Molag entitled "Towards Transparent Development of Food Frequency Questionnaires. Scientific basis of the Dutch FFQ-TOOL TM : a computer system to generate, apply and process FFQs" [38].

  Figure 3. Software and databases in the Dutch FFQ-TOOL TM to generate and process FFQs.Figure adapted from PhD-thesis Marja Molag entitled "Towards Transparent Development of Food Frequency Questionnaires. Scientific basis of the Dutch FFQ-TOOL TM : a computer system to generate, apply and process FFQs" [38].


Or Vernik

Barak Fishbain

Mathematical Estimation of Particulate Air Pollution Levels by Multi-angle Imaging

Keywords: Air pollution monitoring, Multi-angle imaging, Filtered Back Projection

Air pollution control and mitigation are important factors in wellbeing and sustainability. To this end, air pollution monitoring has a significant role. Today, air pollution monitoring is mainly done by standardized stations. The spread of those stations is sparse and their cost hinders the option of adding more. Thus, arises the need for cheaper and available means to assess air pollution. In this article, a method for assessing air pollution levels by means of multi angle imaging is presented. Specifically, the focus is on estimating images' blur as an indication for PM (Particulate Matter) ambient levels. The suggested method applies back-projection Radon transform. By back projection methodology, particles' concentration at each voxel in a 3D space is reconstructed from photos taken from a few different angles.

Introduction

Exposure to PM is known to be one of the predominant factors in morbidity and mortality, causing the premature death of millions of people a year. This is especially true in developing countries with growing industry [START_REF] Apte | Addressing global mortality from ambient pm2.5[END_REF]. Thus, measuring and monitoring PM pollution is a very important task the world needs to deal with in order to ensure public health.

Currently, PM monitoring is standardly done by Air Quality Monitoring (AQM) stations that are considered accurate [START_REF] Moltchanov | On the feasibility of measuring urban air pollution by wireless distributed sensor networks[END_REF]. Due to their size and cost, the stations are sparsely dispersed and so we get a low-resolution concentration map. This limitation is typically addressed by interpolation schemes. However, the interpolation is a complicated task as PM concentrations are characterized by high spatial variability and may present different behaviors for different fractions and geographical areas [START_REF] Pinto | Spatial variability of pm2.5 in urban areas in the united states[END_REF]. These drawbacks have lead researchers to seek other approaches such as Micro Sensing Units (MSUs) for air pollution monitoring [START_REF] Castell | Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?[END_REF][START_REF] Fishbain | An evaluation tool kit of air quality micro-sensing units[END_REF][START_REF] Lerner | Optimal Deployment of a Heterogeneous Environmental Sensor Network[END_REF][START_REF] Moltchanov | On the feasibility of measuring urban air pollution by wireless distributed sensor networks[END_REF] , either high-resolution methods or less costly and portable monitors. Those methods can be used for taking measurements, validating new technologies or giving hints in interpolating existing in-situ measurements.

Here we focus on visual means for assessing PM levels in the atmosphere. To this end, an image processing technique for evaluating the extinction coefficient using visibility cameras was suggested by Graves and Newsam [START_REF] Graves | Using visibility cameras to estimate atmospheric light extinction[END_REF]. The extinction coefficient is a measure that quantifies local radiance attenuation and is used as a standard for measuring atmospheric visibility. Using this measure, an image-processing method to extract a quantitative measurement of atmosphere transmission (the ability of radiation to pass through the atmosphere) from standard photos was presented. The transmittance has a closed form relationship with the extinction coefficient (inversely related), that then can be computed. The research here aims at improving this notion by looking at a 3D volume with changing concentrations at each voxel, as opposed to the method above, which assumes a homogeneous area.

Methods for retrieving PM by multi-angle imaging are in use by satellites. Instruments such as Multi-angle Imaging SpectroRadiometer (MISR) and Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI) are currently applied for remote aerosols sensing [START_REF] Diner | Multiangle imaging spectroradiometer (misr) instrument description and experiment overview[END_REF][START_REF] Diner | The airborne multiangle spectropolarimetric imager (airmspi): a new tool for aerosol and cloud remote sensing[END_REF]. However, these methods have low temporal resolution, as it takes a satellite few hours (or few days) to complete their orbit (latitude dependent), but more importantly, these devices measure the full vertical atmospheric column, which makes it less relevant to the amount of pollution at ground level that can indicate health hazards [START_REF] Etzion | Analysis of image color and effective bandwidth as a tool for assessing air pollution at urban spatiotemporal scale[END_REF]. On top of these, this method is expensive and cannot be easily deployed.

The underlying assumption here is that due to the particles' optical properties of scattering, different concentrations of particles will cause the light field to scatter differently [START_REF] Etzion | Analysis of image color and effective bandwidth as a tool for assessing air pollution at urban spatiotemporal scale[END_REF]. The higher the concentration of scatterers is, the more refractions the light will go through. Refracted light impairs human visibility and expression for this phenomenon is evident in standard photos [START_REF] Graves | Using visibility cameras to estimate atmospheric light extinction[END_REF]. A photo acquires a snapshot of the light field coming from all angles, refracting by the objects and particles in the scenery and eventually hits the camera lens. Particles suspended in the air cause a level of blurriness in the acquired photo. Having this relationship between blurriness and amount of scatterers in the air leads us to the approach of estimating the particles' concentration by measuring image blurriness.

The blur of an image is positively correlated with the integral of the attenuation (extinction) coefficient over the Line Of Sight (LOS) to the object. Thus, by measuring the blurriness of one image we cannot infer the concentration at each voxel. The intensity of the light's direct transmission is attenuated by the scattering (absorption by particulate matter is negligible) and is computed by:

I = I 0 e -LOS β(l) dl . (1)
Where, I 0 is the initial intensity of the radiation source. Our objective then is to find β, which is strongly related with the PM concentration denoted n, by:

β(x) = σ • n(x) . (2)
Where, n(x) is the PM concentration at position x in space and σ is the extinction cross section. σ is depended upon the light's wavelength and the particle's shape and size, thus for our purposes it will be assumed constant. Assuming we know the values of the extinction coefficient integral from a large number of angles (having a correlation with the blurriness measure), the inverse problem is mathematically solvable by the Radon transform [START_REF] Yaroslavsky | Digital holography and digital image processing: principles, methods, algorithms[END_REF].

Radon transform is widely used in Computational Tomography (CT) applications, allowing us to reconstruct the object being scanned from its measured projections. The classically used form of the Radon transform and that we are going to describe, is the 2D Radon. a projection is the integral on the extinction coefficient which equals to:

p(y) = β(x, y) our objective dy = -ln I(y) I 0 assumed known . (3)
The most effective way for reconstructing β from the projections is by using Filtered Back Projections (FBP) that is equivalent to the Inverse Radon Transform (IRT) but less computationally costly. The Radon Transform:

p θ (r) = β(r • cos θ -s • sin θ, r • sin θ + s • cos θ)ds . (4)
FBP:

I(x, y) = π 0 p(r, θ) * q(r)dθ . (5)
q(r) is the LPF, for example Ram-Lak filter [START_REF] Bernal | Use of filtered back-projection methods to improve ct image reconstruction[END_REF].

Relying on these principals, this research will define a method for threedimensional PM concentrations reconstruction by multi-angle imaging. The proposed method will be visibility cameras based, aimed to be a simple, cheap and portable technique for air pollution assessment.

Monte-Carlo Simulation

To illustrate the potential of the suggested method, a simulation of the image acquisition process of the light field in a 3D volume, taken from few different angles is presented. The simulation allows for the reconstruction of PM suspended at each voxel in the volume.

We relate to the physical behavior of light propagating through a volume containing PM in different concentrations as a random process [START_REF] Levis | Airborne three-dimensional cloud tomography[END_REF]. The light, taken in its particulate sense of photons, passes a medium, which has spatially variable optical depth (a measure of the light ability to propagate through the medium) denoted by τ . At each stage, τ is sampled from the optical depth Cumulative Density Function (CDF):

F (τ ) = τ 0 e -τ dτ = 1 -e -τ . (6)
Using Monte-Carlo method, we get a random optical depth sampled from its CDF. For this, we use the uniform distribution U[0,1] CDF for sampling a random number u, and get τ by:

τ = F -1 (u) , u = rand() . (7)
By using the random τ we sampled, we can determine l, the distance the ray propagates until the next diffraction, by the relationship:

τ = l 0 β(x, y, z)dl = l 0 σ • n(x, y, z)dl . ( 8
)
Where β is the extinction coefficient, σ is the extinction cross section and n is the PM concentration at each voxel with its coordinates denoted by {X, Y, Z}. l is found by numeric integration.

Once l is found, the scattering angle after the collision has to be determined. The angle is computed in a similar fashion, assuming randomness in the process and relying on Mie scattering theory under the assumption of spherical particles [START_REF] Hansen | Light scattering in planetary atmospheres[END_REF]. The Mie Theorem provides a physical solution for the scattering of an electromagnetic wave by spherical uniform particles about the size of the light wavelength. Using Monte-Carlo, we will sample a random number from the CDF of the Mie scattering angle on the intersection plane [START_REF] Levis | Airborne three-dimensional cloud tomography[END_REF] and a fully random [0,2π) zenith angle. The found angles, will give us the new direction of the ray's propagation.

We repeat this process of finding new distance to the next collusion, new direction and the intensity at each stage, until the ray exits our volume at some point. This will be done for each ray in the packet of rays entering from each radiated voxel. For now, the image acquisition process is done by summing the values of the exiting rays' intensities for each pixel at the volume's boundaries (visualization of the simulation shown at figure 1).

The received photos (each received from different angle) are used to estimate the level of pollution by applying the Blur Metric (BM) suggested by Frederique Crete [START_REF] Crété-Roffet | The blur effect: Perception and estimation with a new no-reference perceptual blur metric[END_REF]. The BM estimation of the image blurriness is based upon the notion that once an image is blurred, blurring it again will result in smaller differences than blurring a sharp image. We thus receive a value between zero and one indicating the effective blurriness of the image from which we can deduce the general level of pollution (amount of scaterrers).

Preliminary Results

As for now, we have created a volumetric grid containing random, uniform distributed PM concentration at each voxel (Figure 2a). In order to create a more realistic distribution we smoothed the outcome with a 3D box filter (Figure 2b).

We then simulated with Monte-Carlo method the rays enter the volume at specific points and angle and diffracting by the particles. The ray's entrance angle determines which faces of the cube are going to be affected by the radiation. The code is designed to plot random number of rays track as demonstrated in figure 3. For each voxel in the face that the radiation intersects with, we simulate a beam that hits the voxel and propagating through the volume until exiting from the grid boundaries. All rays start with some initial intensity, which will be reduced by the collisions with the aerosols in the volume by the following connection:

I af ter = I bef ore • ω . ( 9
)
Where, ω is the single scattering albedo (the attenuation in intensity) (SSA) of PM and I is the intensity. For better understanding of the results we repeated our experiment, this time instead of all rays having the same initial we used a black and white image of 'Lena' [START_REF] Munson | A note on lena[END_REF] that will filter our rays when entering the upper face of the volume. The rays are now coming in a straight angle from above. The results are a highly noisy image of the original Lena at the bottom plane (figure 5). Repeating the same initial conditions only with growing levels of PM concentrations and measuring the blurriness of the image using our blur metric, gives us a strong correlation between the effective image blur and the level of pollution as we can see in figure 1. Those results will be better examined, evaluated and validated as we continue our work. Table 1. the measure of blurriness increases with the rise in PM pollution level as we can see in different ranges we examined and different scattering simulations.

Conclusions

The preliminary results indicate a certain connection between image blur and pollution level. As for now, this study's concept is theory based. We have reason to believe that the results will be highly correlated with real-life measurements. The system discussed here is integral based. Hence, it tends to be stable and presents small perturbation at the system's output as a result of small perturbation at its inputs. Therefore, we expect this theoretical exercise to show similar results in real-life applications. Albeit, this is still a work in progress, the study needs to continue and establish the found correlation. The model is not yet fully built and there are no concrete reconstruction results to test at this stage.

At next stage, a full back projection (FBP) based reconstruction scheme will be used for finding the original concentrations in space, having only the images as input. Currently, the most simplified model is used. We aim to gradually add more layers of accuracy, better modelling of the physical phenomena, using enhanced air pollution dispersion modelling tools (e.g. GRAL) [START_REF] Ottl | Application of the lagrangian dispersion model gral to assess the air quality in the city of graz[END_REF],adding effects of light polarisation and effects of ground and background reflections. Once the model is complete, sensitivity analysis will be done as well as validating concentrations against ground truth values and cross validation. Future work will also aim at testing the scenario simulation in real life. Our proposed method has the potential to be cheaper, more feasible and with higher spatial and temporal resolution than existing standard methods (remote sensing, AQM stations, etc.). Those advantages add up to the simplicity of the method which may be deployed by anyone with the possession of commodity cameras.

Fig. 1 .

 1 Fig. 1. Sun rays hit the medium and scattered until exiting the grid boundaries. Image is received on the bottom plane as a result of rays intersecting the plane.

Fig. 2 .

 2 Fig. 2. Initial uniform random values in the range [0,10] (a) and the smoother version with smaller spatial gradients in concentration (b).

Fig. 3 .

 3 Fig. 3. on the left, simulation of random rays entering the experiment volume with same angle, and scattering until exiting the volume. On the right, same simulation zoomed in; we can see the red arrow indicating entrance point and angle and the blue arrows indicating new directions after scattering.

Fig. 4 .

 4 Fig. 4. received images at the X-Y plane (the floor of the volume). Sun light is coming from the top left corner direction to all three affected faces. The image on the left was acquired with 100 rays per pixel and presented with low resolution. The image on the right has higher spatial resolution (x5 than the left image) and 500 rays per pixel.

Fig. 5 .

 5 Fig. 5. from left to right. 1. Lena's original B&W image. 2. Bottom plane received image. 3. Using LPF on the received image.

Acknowledgments

The authors would like to thank Holodovsky Vadim and Schechner Y. Yoav, for sharing their code for Mie scattering, that has helped to push the paper forward in terms of accuracy.