Léonard Depotte

Maryline Caroux

Joseph Gligorov

Florence Canouï-Poitrine

Yazid Belkacemi

Alexandre De

La Taille

Christophe Tournigand

Emmanuelle Kempf

Association between overweight, obesity, and quality of life of patients receiving an anticancer treatment for prostate cancer: a systematic literature review

Keywords: Prostatic Neoplasms, Health-related quality of life, Radiotherapy, Prostatectomy, Obesity

Background Prostate cancer (PCa) and obesity are two ever-increasing public health issues that can independently impair the quality of life (QOL) of affected patients. Our objective was to evaluate the impact of overweight and obesity on the QOL of patients with PCa receiving an anticancer treatment.

Methods

We performed a systematic review of the literature using PubMed, Embase, Cochrane Library and Web of Science databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. The search equation targeted studies that included PCa patients who had a body mass index (BMI) greater than 25 kg/m 2 , who were receiving anticancer therapy, and whose QOL was analyzed according to validated or non-validated scores.

Results

Of 759 identified articles, we selected 20 studies published between 2000 and 2019 of 12,529 patients treated for PCa, including 5549 overweight or obese patients. QOL assessment was performed using nine validated scales and two non-validated questionnaires. Of seven studies on radiotherapy, six found obesity to have a negative impact on patients' QOL (especially urinary, sexual, and bowel-related QOL). Thirteen studies assessed the QOL of patients who underwent radical prostatectomy, with a BMI > 25 kg/m 2 having no observed impact. In obese patients under 65 years of age and without comorbidities, nerve-sparing surgery appeared to limit the deterioration of QOL. Four studies on brachytherapy found discordant results. One study showed greater QOL impairment in obese patients receiving first-generation hormone therapy than in those with normal or decreased BMI. No study evaluated the QOL of overweight or obese patients receiving other types of systemic treatment. Conclusion Based on the published data, the level of evidence for an association between QOL and overweight or obesity in patients treated for PCa is not high. Prospective cohort studies including this type of patient population are warranted to answer this topical public health issue.

Background

Prostate cancer (PCa) is the second most common form of cancer in men. Nearly 1.5 million were diagnosed with this disease in 2020 [START_REF] Sung | Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 Cancers in 185 countries[END_REF]. PCa is also the sixth leading cause of cancer death in men, being responsible for 375,000 deaths worldwide in 2020. Depending on stage and aggressiveness as well as on patient age, vulnerabilities, and comorbidities, the treatment options differ. Each is associated with a distinct toxicity profile. Various curative therapies are offered to men with a survival probability of more than 10 years and localized or locally advanced cancer. These are active surveillance, radical prostatectomy, brachytherapy, cryotherapy, and external radiotherapy with or without hormone therapy.

Since the 1980s, quality of life (QOL) has become a major objective in the medical management of oncology patients [START_REF] Aaronson | The European organization for research and treatment of cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology[END_REF]. In most clinical trials today, it is a key endpoint for treatment approval. Despite recent improvements in radiotherapy and surgical techniques, local treatment of PCa often leads to impaired QOL due to sexual, urinary, and gastrointestinal toxicity. Moreover, anxiety disorders, depression, and fatigue are general adverse effects that can be found regardless of the treatment regimen. Chemical castration by hormone therapy can lead to weight gain or vasomotor symptoms. Because of the relative indolence of PCa, heterogeneity and toxicity of PCa treatments, and clinical condition of patients, QOL is of considerable importance.

In 2018, more than half of American adults reported having a health problem or chronic disease, including obesity [START_REF] Boersma | Prevalence of multiple chronic conditions among US adults, 2018[END_REF]. The World Health Organization recognizes obesity as a "global pandemic," with a tripling in worldwide prevalence since 1975. In 2016, nearly 40% of people over 18 were overweight and one in eight adults were obese [START_REF]Obesity and overweight[END_REF]. Obesity interacts with many chronic diseases, including PCa. Some studies have shown that an elevated body mass index (BMI) is associated with a risk of prostate cancer-specific mortality and biochemical recurrence in PCa patients [START_REF] Cao | Body Mass index, prostate cancer-specific mortality, and biochemical recurrence: a systematic review and meta-analysis[END_REF]. Moreover, according to the World Cancer Research Fund, obesity may increase the risk of advanced PCa [START_REF]Prostate cancer|What causes prostate cancer?|WCRF International[END_REF]. However, the influence of obesity on the QOL of patients treated for PCa has only been studied in small sample populations with variable levels of evidence.

The objective is to assess the association between overweight or obesity and QOL in patients who received a treatment for PCa.

Methods

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA) [START_REF] Page | The PRISMA 2020 statement: an updated guideline for reporting systematic reviews[END_REF]. It is registered in the PROSPERO Database of the National Institute for Health Research under number 339197 [8].

We conducted research without any time filter based on PubMed, Embase, Cochrane Library and Web of Science databases. We included any English-language original article that focused on the impact of being overweight or obese on the QOL of patients receiving specific anticancer treatment for PCa. All the definitions of the different items used for the search equations are defined in Additional file 1: Appendix 1. We included studies of patients with PCa regardless of histologic type and tumor stage, except studies on best supportive care only. The treatments were categorized as follows: radical prostatectomy, radiotherapy, or brachytherapy with or without hormone therapy, or systemic therapy alone. We used the search terms "prostatic neoplasms," "prostate cancer," "quality of life," "overweight," and "obesity". The search equations we used on Pubmed and Embase databases are described in Additional file 1: Appendix 2. Because of the multitude and heterogeneity of QOL assessment scales in PCa, this literature review included all scales to be as exhaustive as possible. No treatment strategies were excluded. Reviews, editorials, and case reports were not included. Eligibility criteria are summarized in Additional file 1: Appendix 3.

Articles were screened by evaluating the title and abstract for the inclusion criteria. Two care providers (MC, EK) reviewed the remaining full text for relevance. Once the final list of studies was obtained, two independent investigators (MC, LD) conducted a double-blind collection of the items of interest according to a previously defined collection grid (Additional file 1: Appendix 4). In the event of a discrepancy, a third independent investigator who is a specialist in medical oncology and methodology (EK) settled the issue. We assessed the risk of bias of the included studies with the NIH Quality Assessment Tool for Observational Cohort and Cross-sectional Studies [9].

Results

The completed PRISMA 2020 Checklist is shown in Additional file 1: Appendix 5.

Study selection

In all, 759 articles were identified from the PubMed, Embase, Cochrane Library and Web of Science databases using the search equation (Fig. 1). After we excluded irrelevant articles, 179 remained. After reviewing the remaining full-text articles for relevance, a total of 20 were identified for inclusion in this review (Table 1). The combined population of those 20 articles was 12,529 patients with PCa, including 5549 overweight or obese patients. These 20 studies were published between 2000 and 2019.

Study characteristics

The assessment of study bias is summarized in Table 2. The number of patients included per study ranged from 32 [START_REF] Merrick | Permanent prostate brachytherapy-induced morbidity in patients with grade II and III obesity[END_REF] to 1884 [START_REF] Anast | The impact of obesity on health related quality of life before and after radical prostatectomy (data from CaPSURE)[END_REF]. None of the studies were randomized, 10 were retrospective, 10 were prospective longitudinal observational studies, 5 were conducted in multiple centers, and 12 were conducted in the last 10 years, including 6 in the last 5 years. None of the studies evaluated castration-resistant metastatic disease, patients on second-generation hormone therapy, chemotherapy, or metabolic radiotherapy. In total, 10 studies highlighted the impact of age on QOL in patients receiving specific anticancer therapy for PCa.

QOL assessment

The choice of scale depended on the purpose of the study. When QOL was assessed in a general way, the SF-36 or RAND 36 questionnaires were used [START_REF] Anast | The impact of obesity on health related quality of life before and after radical prostatectomy (data from CaPSURE)[END_REF][START_REF] Wiltz | Robotic radical prostatectomy in overweight and obese patients: oncological and validated-functional outcomes[END_REF]. To evaluate the impact of PCa treatments on one or more functional symptoms affecting urinary, sexual, and gastrointestinal QOL, the authors used validated scales like EPIC 26 (Expanded Prostate Cancer Index, 10 studies), UCLA-PCI (University of California Los Angeles Prostate Cancer Index, 4 studies), EORTC QLQ-PR25 (European Organization for Research and Treatment of Cancer-Quality of Life Prostate, 1 study), IIEF (Index of Erectile Function, 4 studies), SHIM (Sexual Health Inventory for Men, 2 studies), IPSS (International Prostate Symptom Score, 5 studies), ICIQ-SF6 (International Consultation Incontinence Questionnaire Short Form, 2 studies), and Vaizey score for rectal symptomatology [1 study]. Three authors used non-validated questionnaires, and three others aimed to improve QOL assessment in patients treated for PCa by developing new instruments [START_REF] Dess | Erectile function after stereotactic body radiotherapy for localized prostate cancer[END_REF][START_REF] Abdollah | A novel tool to assess the risk of urinary incontinence after nerve-sparing radical prostatectomy[END_REF][START_REF] Alemozaffar | Prediction of erectile function following treatment for prostate cancer[END_REF]. The assessment scales and scores used in the reviewed studies are available in Additional file 1: Appendix 7

Body mass assessment

All studies focused on BMI divided into categories. Most studies compared normal weight (BMI > 25 kg/m2), overweight (25-30 kg/m2) and obese (> 30 kg/m2), while others only compared obese versus non-obese patients [START_REF] Dess | Erectile function after stereotactic body radiotherapy for localized prostate cancer[END_REF][START_REF] Limani | Qualité de vie après prostatectomie robotique : impact des indices de masse corporelle et âge sur l'incontinence urinaire[END_REF][START_REF] Koneru | The impact of obesity on patient reported outcomes following stereotactic body radiation therapy for prostate cancer[END_REF] or overweight versus normal weight patients [START_REF] Abdollah | A novel tool to assess the risk of urinary incontinence after nerve-sparing radical prostatectomy[END_REF][START_REF] Ferenc | Physical and psychosocial side-effects of brachytherapy: a questionnaire survey[END_REF]. Three other studies [START_REF] Sanda | Quality of life and satisfaction with outcome among prostatecancer survivors[END_REF][START_REF] Dieperink | Living alone, obesity and smoking: Important factors for quality of life after radiotherapy and androgen deprivation therapy for prostate cancer[END_REF][START_REF] Challapalli | Evaluating the prevalence and predictive factors of vasomotor and psychological symptoms in prostate cancer patients receiving hormonal therapy: Results from a single institution experience[END_REF] only mentioned median BMI and the Taiwanese study [START_REF] Chen | Predictors for lower urinary tract symptoms and the urinary specific quality of life in prostate cancer patients: One-year follow-up[END_REF] did not provide any information on BMI values, categorizing it as either high or normal. Finally, seven studies distinguished between grades of obesity (BMI 30-34.9 kg/m2, 35-40 kg/m2, or greater than 40 kg/m2). This allowed the impact of the grades of obesity to be investigated more precisely.

Patient characteristics

The median age of the patients included in each study ranged from 59 to 69 years. Patient tumor stages were available in 12 studies, with a mean of 75% of patients having T1 disease in 7 studies. When comorbidities were specifically collected [START_REF] Wiltz | Robotic radical prostatectomy in overweight and obese patients: oncological and validated-functional outcomes[END_REF][START_REF] Dess | Erectile function after stereotactic body radiotherapy for localized prostate cancer[END_REF][START_REF] Challapalli | Evaluating the prevalence and predictive factors of vasomotor and psychological symptoms in prostate cancer patients receiving hormonal therapy: Results from a single institution experience[END_REF][START_REF] Garg | Patientreported quality of life recovery curves after robotic prostatectomy are similar across body mass index categories[END_REF][START_REF] Haahr | A retrospective study of erectile function and use of erectile aids in prostate cancer patients after radical prostatectomy in Denmark[END_REF], hypertension was the most frequently encountered comorbidity, followed by diabetes and coronary heart disease. Patients' marital status and level of education or standard of living were recorded in seven studies, five of which were American.

Impact of patient BMI on QOL according to type of anticancer treatment

Only one study [START_REF] Challapalli | Evaluating the prevalence and predictive factors of vasomotor and psychological symptoms in prostate cancer patients receiving hormonal therapy: Results from a single institution experience[END_REF] on hormone therapy included metastatic patients. Most of the studies involved one treatment or a combination of local treatments. Thirteen articles dealt with prostatectomy, eight with radiotherapy, and five with brachytherapy. Five studies evaluated multiple treatments. None focused on systemic chemotherapy alone.

Due to the heterogeneity of the timing of assessment (3 to 60 months) and of the QOL scores used and the variable definitions of overweight and obesity, it was not possible to perform a quantitative analysis. Among the 13 studies of radical prostatectomy, 5 showed that obesity increased the risk of post-prostatectomy urinary disorders, while 5 others did not find any association. Likewise, 3 studies highlighted a negative relationship between sexual disorders and obesity, while 2 others reported the impact of high BMI on post-prostatectomy vitality. The conclusions of the 6 studies that looked at radiotherapy were more unanimous. Obesity and overweight had a negative impact on QOL, 2 observing an effect on sexual function, 3 on urinary function, and 3 on vitality. These adverse events appeared to occur after a long interval after radiation therapy (12 to 60 months) in 4 of them [START_REF] Dess | Erectile function after stereotactic body radiotherapy for localized prostate cancer[END_REF][START_REF] Koneru | The impact of obesity on patient reported outcomes following stereotactic body radiation therapy for prostate cancer[END_REF][START_REF] Dieperink | Living alone, obesity and smoking: Important factors for quality of life after radiotherapy and androgen deprivation therapy for prostate cancer[END_REF][START_REF] Thomas | Lifestyle factors correlate with the risk of late pelvic symptoms after prostatic radiotherapy[END_REF]. Regarding the 4 studies that looked at brachytherapy, 2 found a negative relationship between obesity and QOL on bowel, urinary, and sexual function. Finally, a single 2018 study [START_REF] Challapalli | Evaluating the prevalence and predictive factors of vasomotor and psychological symptoms in prostate cancer patients receiving hormonal therapy: Results from a single institution experience[END_REF] found increased vasomotor symptoms, fatigue, and insomnia in patients on LHRH analogs who had higher BMI.

Discussion

This systematic review of 20 studies involving 12,529 patients with PCa, of whom 5549 were overweight or obese, showed that being overweight was more frequently associated with impaired erectile and urinary function, and decreased vitality after radiotherapy. The results after radical prostatectomy and brachytherapy were more discordant, suggesting a possible effect of obesity and overweight on urinary and sexual function. Severe hormone therapy-related toxicity such as vasomotor symptoms occurred more in overweight or obese patients. The impact of high BMI on QOL has never been studied in patients receiving second-generation hormone therapy, chemotherapy, or metabolic radiotherapy with radium-223.

These results may have some explanations. In 2013, a French study suggested that physical, technical, and dosimetric difficulties in radiotherapy may increase acute and late toxicities in patients with higher BMI [START_REF] Pichon | Obésité et irradiation : difficultés techniques, toxicité et efficacité[END_REF]. In patients undergoing prostatectomy, no study has ever been able to determine the real impact of obesity on QOL. Therefore, some studies recommend prostatectomy in obese patients given the advances in robot-assisted laparoscopic surgery [START_REF] Beyer | Roboterassistierte radikale Prostatektomie[END_REF]. Conversely, others consider obesity to be a predictor of adverse effects on QOL [START_REF] Froehner | Systematic Review and Meta-analysis of Studies Reporting Urinary Continence Recovery After Robot-assisted Radical Prostatectomy[END_REF][START_REF] Knipper | Impact of obesity on perioperative outcomes at robotic-assisted and open radical prostatectomy: results from the national inpatient sample[END_REF]. In this systematic review, overweight and obesity alone do not seem to impair QOL after prostatectomy.

Several confounding factors may be at work. First, the age of the patients in these 20 studies varied significantly. Aging seems to be associated with a higher risk of post-prostatectomy urinary incontinence [START_REF] Abdollah | A novel tool to assess the risk of urinary incontinence after nerve-sparing radical prostatectomy[END_REF][START_REF] Limani | Qualité de vie après prostatectomie robotique : impact des indices de masse corporelle et âge sur l'incontinence urinaire[END_REF][START_REF] Chen | Predictors for lower urinary tract symptoms and the urinary specific quality of life in prostate cancer patients: One-year follow-up[END_REF] and erectile dysfunction [START_REF] Dess | Erectile function after stereotactic body radiotherapy for localized prostate cancer[END_REF][START_REF] Alemozaffar | Prediction of erectile function following treatment for prostate cancer[END_REF][START_REF] Haahr | A retrospective study of erectile function and use of erectile aids in prostate cancer patients after radical prostatectomy in Denmark[END_REF][START_REF] Cozzi | Sexual function recovery after robot-assisted radical prostatectomy: Outcomes from an Italian referral centre and predicting nomogram[END_REF]. In one study, the impact of obesity on QOL was lower in younger patients [START_REF] Freedland | Obesity does not adversely affect health-related quality-of-life outcomes after anatomic retropubic radical prostatectomy[END_REF]. According to the literature, obesity in the elderly and aging tends to favor the appearance of comorbidities and increase complications [START_REF] Quilliot | L'obésité du sujet âgé[END_REF]. But this question remains complex and debated, and some studies seem to show on the contrary better survival outcomes in older, overweight patients treated for cancer [START_REF] Pamoukdjian | Obesity survival paradox in cancer patients: Results from the Physical Frailty in older adult cancer patients (PF-EC) study[END_REF][START_REF] Martinez-Tapia | The obesity paradox for mid-and long-term mortality in older cancer patients: a prospective multicenter cohort study[END_REF].

Second, it has long been known that obesity is a risk factor for certain pathologies, such as hypertension, diabetes, or coronary artery disease [START_REF] Basdevant | L'obésité : origines et conséquences d'une épidémie[END_REF]. These comorbidities and their treatments, independently of weight, can cause erectile dysfunction, reduced libido, and impaired QOL [START_REF] Droupy | Épidémiologie et physiopathologie de la dysfonction érectile[END_REF]. Comorbidities varied across the 20 studies analyzed in our review. Over half of the obese patients in one of our studies had two to four comorbidities or more [START_REF] Anast | The impact of obesity on health related quality of life before and after radical prostatectomy (data from CaPSURE)[END_REF]. The impairment of physical function, vitality, and global QOL postoperatively was greater in these highly comorbid patients. In contrast, fewer comorbidities appear to correlate with a lower impact of overweight and obesity [START_REF] Garg | Patientreported quality of life recovery curves after robotic prostatectomy are similar across body mass index categories[END_REF][START_REF] Cozzi | Sexual function recovery after robot-assisted radical prostatectomy: Outcomes from an Italian referral centre and predicting nomogram[END_REF][START_REF] Montgomery | Obesity adversely affects health related quality of life before and after radical retropubic prostatectomy[END_REF].

Finally, the type of anticancer treatment may have contributed itself to an interpretation bias in some studies. Those that mostly included patients who underwent nerve-sparing surgery concluded that overweight had no impact on postoperative QOL [START_REF] Limani | Qualité de vie après prostatectomie robotique : impact des indices de masse corporelle et âge sur l'incontinence urinaire[END_REF][START_REF] Garg | Patientreported quality of life recovery curves after robotic prostatectomy are similar across body mass index categories[END_REF][START_REF] Freedland | Obesity does not adversely affect health-related quality-of-life outcomes after anatomic retropubic radical prostatectomy[END_REF]. Other specific patients' characteristics may explain the choice between radiotherapy and radical prostatectomy for patients with a localized PCa.

To our knowledge, this study is the first literature review to examine the impact of obesity on the QOL of obese patients treated for PCa. This question is crucial from a public health point of view, as these two pathologies are frequent and increasing worldwide. Half of the studies in our literature review were prospective. This allowed us to obtain reliable, although sometimes contradictory, results.

Our literature review has some limitations. None of the studies focused on new systemic therapeutic strategies for PCa, such as second-generation hormone therapy or metabolic radiotherapy. New studies should be carried out to address this little-known issue. The heterogeneity of the patients' characteristics probably affected their 2. Was the study population clearly specified and defined? 3. Was the participation rate of eligible people at least 50%? 4. Were all the subjects selected or recruited from the same or similar populations (including the same time period)? Were inclusion and exclusion criteria for being in the study prespecified and applied uniformly to all participants?

5. Was a sample size justification, power description, or variance and effect estimates provided? 6. For the analyses in this paper, were the exposure(s) of interest measured prior to the outcome(s) being measured? 7. Was the timeframe sufficient so that one could reasonably expect to see an association between exposure and outcome if it existed? 8. For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome (e.g., categories of exposure, or exposure measured as continuous variable)? 9. Were the exposure measures (independent variables) clearly defined, valid, reliable, and implemented consistently across all study participants? 10. Was the exposure(s) assessed more than once over time? 11. Were the outcome measures (dependent variables) clearly defined, valid, reliable, and implemented consistently across all study participants? 12. Were the outcome assessors blinded to the exposure status of participants? 13. Was loss to follow-up after baseline 20% or less? 14. Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure(s) and outcome(s) QOL, and thus biased our evaluation of its association with overweight and obesity. Finally, the timing of assessment and the scales related to QOL and comorbidities were heterogeneous and may have changed ever since [START_REF] Droupy | Épidémiologie et physiopathologie de la dysfonction érectile[END_REF].

Conclusion

The existence of a dual public health issue of PCa and overweight or obesity led us to conduct this literature review, which included 20 studies on impaired QOL in actively treated patients. Our results highlight that overweight and obesity negatively impacted QOL in patients receiving radiotherapy for PCa, particularly their urinary, sexual, and bowel function, 12 months and more after treatment. The results were more discordant in patients receiving prostatectomy or brachytherapy. In this context of rising obesity and PCa, prospective studies evaluating their interaction and the effectiveness of public health measures to combat obesity are expected.

Fig. 1

 1 Fig. 1 PRISMA study selection flowchart and exclusion criteria

  Anast Dess Latini Thomas Dieperink Montgomery Sanda Wiltz A Merrick Ferenc Alemozaffar Abdollah Haahr Garg Limani Chen Cozzi Koneru Challapalli

Table 1

 1 Main characteristics of the studies included in the systematic review

	Comorbidities Timing and	function	affected by	high BMI	NA Urinary	function after	24 months		Number of Physical func-	comorbidities tion, general	(0-1, 2-4) health, and	vitality after	24 months	Diabetes, Sexual func-	hypertension, tion after	coronaropathy, 60 months	depression	Number of Urinary	comorbidities function after	(0, 1-2, 3 +) 24 months	NA Rectal symp-	toms and	nycturia after	43 months	(median)	NA Urinary symp-	toms and vital-	ity between	12 and	48 months	after treat-	ment	Number of Poorer bowel	comorbidities function after	(0-1, 2-3, 4 +) 24 months, if adjuvant	radiotherapy
	Tumor stage				T1c-T3a				T1-T3					T1c-T3				T1-T3				NA					T1-T3							T1-T2
	Patient age				Mean	(SD): 56.1	(NA)		Mean	(SD): 61.5	(NA)			Median	(IQR): 69	(64, 73)		≤ 65: 810, ≥ 65: 438		Mean (min,	max): 74 (53,	94)			Mean (min,	max): 65.7	(48, 77)					Mean	(SD): 59.2	(NA)
	Nerve-	sparing	status		Bilat-	eral = 257, uni-= 68, = 15 lateral none NA					NA				NA				NA					NA							NA
	BMI	categorization	(kg/m 2 )		≤ 25, 25-30, 30-35			≤ 25, 25-30, 30-35, ≥ 35			≤ 30, 30-40, ≥ 40		≤ 25, 25-30, 30-35			≤ 18.5, 18.5-25, 25-30, ≥ 30			≤ 30, ≥ 30						30-35, ≤ 25, 25-30, ≥ 35
	QOL	evaluation	before	treatment	Yes				Yes					Yes				Yes				No					No							Yes
	QOL scale				UCLA-PCI				UCLA-PCI, SF-36					EPIC-26, IIEF-5				UCLA-PCI				CTCAE, Vaizey	rectal symptoms	score			SF-12, EPIC-26							SF-12, EPIC-26
	Follow-up	(months)			24				24					56				24				43					Maximum	48 months						36
	Number of	patients			340				1884					373				1248				440					317							376
	Design				American,	prospec-	tive, single-	center	American,	retrospec-	tive, multi-	center		American,	prospec-	tive, single-	center	American,	prospec-	tive, multi-	center	English,	retrospec-	tive, single-	center		Danish,	retrospec-	tive, single-	center				American,	prospec-	tive, single-	center
	References Objective				Freedland S. Impact of	[31] obesity on QOL	after prostatec-	tomy	Anast J. [11] Impact of	obesity on QOL	after prostatec-	tomy		Dess R. [13] Impact of	radiotherapy	on erectile	function	Latini D. [38] Impact of	diabetes on	QOL after pros-	tatectomy	Thomas R. [25] Impact of obe-	sity on pelvic	symptoms	post-radiother-	apy	Dieperink K. [20] Study of	QOL after	radiotherapy	and hormone	therapy			Montgomery Impact of	J. [37] obesity on QOL	after prostatec-	tomy
					1				2					3				4				5					6							7

Table 1 (

 1 continued)

	Comorbidities Timing and	function	affected by	high BMI	Number of Vitality and	comorbidities hormonal	function	6 months	or later after	treatment	Diabetes, Urinary	hypertension, and sexual	coronaropathy function	after 12 and	24 months	NA No difference				NA Less urinary	incontinence	at the end of	treatment	NA Sexual func-	tion after	24 months				Charlson Index Urinary	incontinence	if age < 65,	after 3, 6 and	12 months	Hypertension, Sexual func-	diabetes, ASA tion after	score, dyslipi-12 months	demia
	Tumor stage				T1-T2						T1c-T3b					T1c-T2b				NA				T1-T2						≥ T1c		T1-T3b
	Patient age				Median (min,	max): 63 (38,	84)				Mean	(SD): 59.8	(NA)			Mean	(SD): 63.8	(6.5)		Mean	(SD): 66.9	(10.3)		Mean (SD):	66 (NA)					Mean (min,	max): 62.6	(38.9, 80)	Mean (SD): 62	(5.8)
	Nerve-	sparing	status		Yes						Yes					NA				NA				Yes						Yes			Yes
	BMI	categorization	(kg/m 2 )		Median: 28						≤ 25, 25-30, 30-35				≥ 35			19-25, ≥ 25			≤ 25, 25-35, ≥ 35					≤ 25, ≥ 25		≤ 25, 25-30, ≥ 30
	QOL	evaluation	before	treatment	Yes						Yes					Yes				No				Yes						Yes			Yes
	QOL scale				EPIC-26, SCA, SCA-	P, EPIC-Partner					UCLA-	PCI, SF-36, IIEF-	5, IPSS			IPSS, IIEF, R-FAS				Numerical scale				EPIC-26						ICIQ-SF6, IIEF			IIEF-5
	Follow-up	(months)			24						24					28				2				24						12			12
	Number of	patients			1201						945					32				49				1027						1311			704
	Design				American,	prospec-	tive, multi-	center			American,	prospec-	tive, single-	center		American,	retrospec-	tive, single-	center	Polish,	retrospec-	tive, single-	center	American,	prospec-	tive, multi-	center			Italian,	prospec-	tive, single-	center	Danish,	retrospec-	tive, single-	center
	References Objective				Sanda M. [19] Study of QOL	after local	treatment	(prostatectomy,	radiotherapy or	brachytherapy)	Wiltz A. [12] Impact of	obesity on QOL	after prostatec-	tomy		Merrick G. [10] Impact of	obesity on QOL	after prostatic	brachytherapy	Ferenc S. [18] Study of QOL	after brachy-	therapy		Alemozaffar Study of sexual	M. [15] function after	local treatment	(prostatectomy,	radiotherapy or	brachytherapy)	Abdollah F. [14] Study of urinary	incontinence	after prostatec-	tomy	Haahr M. [24] Study of sexual	function after	prostatectomy
					8						9					10				11				12						13			14

Table 1 (

 1 continued)

	References Objective Design Number of Follow-up QOL scale QOL BMI Nerve-Patient age Tumor stage Comorbidities Timing and	patients (months) evaluation categorization sparing function	before (kg/m 2 ) status affected by	treatment high BMI	15 Garg T. [23] Impact of obe-American, 691 36 SHIM, IIQ-7, Blad-Yes ≤ 18.5, 18.5-sity on sexual retrospec-der Health 25, 25-30 Yes Mean (SD): 59.1 T2a-T3b Diabetes, hypertension, No difference	and urinary tive, single-Questionnaire (6.4) coronaropathy	function after center	prostatectomy	16 Limani K. [16] Impact of BMI Belgian, 272 24 ICIQ-UI SF, EORTC Yes ≤ 30, on QOL after retrospec-QLQ PR25 ≥ 30 Yes Mean (SD): 63 (6) NA NA No difference	prostatectomy tive, single-	center	17 Chen S. [22] Study of urinary Taiwanese, 131 12 IPSS Yes NA NA Mean T1-T3 NA Urinary	function after prospec-(SD): 68.77 function after	local treatment tive, multi-(9.29) 3 months	(prostatectomy center	or radiother-	apy)	18 Cozzi G. [30] Study of erec-Italian, 643 12 EPIC Yes ≤ 25, 25-30, tile function retrospec-≥ 30 Yes < 60: 26%, 60-70: T1-T3 Charlson Index No difference	1 year after tive, single-54%, > 70:	prostatectomy center 20%	19 Koneru H. [17] Impact of American, 266 24 EPIC-26 Yes ≤ 25, 25-30, 30-35 obesity on retrospec-, 35-40, ≥ 40 QOL after tive, single-NA Median (min, max): 69 (44, 94) NA Charlson Index Sexual func-tion after 24 months	radiotherapy center and fatigue	after	18 months	20 Challapalli A. Study of English, 250 9 Vasomotor symp-No Median BMI: 28 NA Mean (SD): T1-T4, N0-N1, Hypertension, Vasomotor	[21] vasomotor prospec-toms scale 74 (NA) M0-M1 diabetes, symptoms	symptoms dur-tive, single-myocardial after 9 months	ing hormone center infarction	therapy	ASA score = American Society of Anesthesiologists; BMI = Body Mass Index; CTCAE = Common Terminology Criteria for Adverse Events; EORTC QLQ-C30 = European Organization for Research and Treatment of Cancer Quality of Life Questionnaire; EPIC = Expanded Prostate Cancer Index; EPIC-Partner = Expanded Prostate Cancer Index for Partners; EQ-5D-5L = 5-Level 5-Dimension EuroQol scale; FACT-P = Functional Assessment of = Incontinence Impact Questionnaire; NA = Short-= Prostate Cancer; = Standard Deviation; SF-12 = Not Applicable; PCa = Service Satisfaction Scale for Cancer Care; SCA-P = Service Satisfaction Scale for Cancer Care for Partners; SD = International Consultation on Incontinence Questionnaire -Urinary Incontinence Short Form; IIQ = Rectal Function Assessment Score; SCA Cancer Therapy -Prostate; ICIQ-UI SF QOL = Quality of Life; R-FAS	Form 12

Table 2

 2 Bias analysis

	Y = Yes, N = No, UK = Unknown 1. Was the research question or objective in this paper clearly stated?

Funding

This systematic literature review was not supported by any sponsor.

Availability of data and materials

All data analyzed during this study are published articles available online.

Supplementary Information

The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s12955-023-02093-2.

Acknowledgements

We would like to warmly thank Mrs. ALLORY Sylviane, from the UPEC (Université Paris-Est Créteil), for her precious help in the realization of the research equation that we used in this systematic literature review.

Authors contributions

LD had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: LD, MC, EK. Acquisition of data: LD, MC. Analysis and interpretation of data: LD, MC, EK, FCP. Drafting of the manuscript: MC, LD, EK. Critical revision of the manuscript for important intellectual content: LD, MC, EK, CT, YB, ADT, FCP. Statistical analysis: None. Obtaining funding: None. Administrative, technical, or material support: EK. Supervision: EK. Other: None. All authors read and approved the final manuscript.

Declarations

Ethics approval and consent to participate Not applicable.

Consent for publication

Not applicable.

Competing interests

None.

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Tiphaine Casy
email: tiphaine.casy@univ-rennes1.fr

Alexandre Tronchot
email: alexandre.tronchot@chu-rennes.fr

Herve Thomazeau
email: herve.thomazeau@chu-rennes.fr

Xavier Morandi
email: xavier.morandi@chu-rennes.fr

Pierre Jannin
email: pierre.jannin@univ-rennes1.fr

Arnaud Huaulmé
email: arnaud.huaulme@univ-rennes1.fr

Hervé Thomazeau

estimation to evaluate postural skills during orthopedic surgery simulations

Keywords: 2D human pose estimation, Orthopedic Surgery, Process Assessment, Simulation training

Introduction

Simulation-based learning technique have been used in different fields of medicine for many years [START_REF] Satava | Historical Review of Surgical Simulation-A Personal Perspective[END_REF]. One of the oldest simulation models is a clay nasal reconstruction model from ancient India that dates back to 600 BC [START_REF] Badash | Innovations in surgery simulation: a review of past, current and future techniques[END_REF]. Thanks to technological advances, medical simulators have improved in realism and number of simulated procedures [START_REF] Satava | Historical Review of Surgical Simulation-A Personal Perspective[END_REF][START_REF] Badash | Innovations in surgery simulation: a review of past, current and future techniques[END_REF]. Laparoscopic surgery is the specialty that most requires of simulation-based training for many reasons including the reduction of tutoring time by experts and the development of technical skills [START_REF] Sutherland | Surgical Simulation[END_REF][4][START_REF] Brewin | Full immersion simulation: validation of a distributed simulation environment for technical and non-technical skills training in Urology[END_REF]. Indeed, simulation has many advantages such as improved ethics, perfect reproducibility, and acquisition of technical skills without endangering the patient's health [START_REF] Badash | Innovations in surgery simulation: a review of past, current and future techniques[END_REF][START_REF] Sutherland | Surgical Simulation[END_REF][4]. Concerning technical skills, simulators record the execution time, gesture accuracy, and correct use of the laparoscope [START_REF] Brewin | Full immersion simulation: validation of a distributed simulation environment for technical and non-technical skills training in Urology[END_REF][START_REF] Narazaki | Robotic surgery training and performance[END_REF][START_REF] Smith | Assessing laparoscopic manipulative skills[END_REF]. These competencies have been shown to be insufficient, lacking non-technical skills aspects such as communication, stress management and gesture [START_REF] Smith | Assessing laparoscopic manipulative skills[END_REF][START_REF] Agha | The role of non-technical skills in surgery[END_REF][START_REF] Sharma | Non-technical skills assessment in surgery[END_REF]. Technical and non-technical skills are indissociable, as shown by Fecso et al., using statistical correlations [START_REF] Fecso | Relationship between intraoperative non-technical performance and technical events in bariatric surgery[END_REF].

Another important skill is ergonomic self-awareness, to avoid musculoskeletal pain caused by repetitive surgeries.

The most studied ergonomic factors are the movement and posture of the surgeon's head, shoulder, and neck [START_REF] Azari | Quantifying surgeon maneuevers across experience levels through marker-less hand motion kinematics of simulated surgical tasks[END_REF][START_REF] Meltzer | Measuring Ergonomic Risk in Operating Surgeons by Using Wearable Technology[END_REF].

Surgeon's posture can be detected using cameras and/or electromyographic sensors (EMGs) [START_REF] Farella | A Wireless Body Area Sensor Network for Posture Detection[END_REF][START_REF] Xu | Human Posture Recognition and fall detection Using Kinect V2 Camera[END_REF][START_REF] Nisky | A framework for analysis of surgeon arm posture variability in robot-assisted surgery[END_REF][START_REF] Dalager | Surgeons' posture and muscle strain during laparoscopic and robotic surgery[END_REF]. These technologies allow analysing the surgeon's ergonomic dynamics by estimating postural angles and muscle tension [START_REF] Athanasiadis | An analysis of the ergonomic risk of surgical trainees and experienced surgeons during laparoscopic procedures[END_REF][START_REF] Lobo | Estimation of surgeons' ergonomic dynamics with a structured light system during endoscopic surgery[END_REF] and by providing information to limit musculoskeletal pain in the lower back, neck and shoulders. Some studies have analysed the various parameters that influence the surgeon's posture with the aim of proposing solutions to reduce pain and improve the overall surgical ergonomic [START_REF] Dalager | Surgeons' posture and muscle strain during laparoscopic and robotic surgery[END_REF][START_REF] Athanasiadis | An analysis of the ergonomic risk of surgical trainees and experienced surgeons during laparoscopic procedures[END_REF][START_REF] Berguer | A comparison of surgeons' posture during laparoscopic and open surgical procedures[END_REF]. These methods are based on data collected using EMGs and/or Inertial Measurement Units (IMU) directly attached to the surgeon's body. The camera-based method described by Berguer et al. [START_REF] Berguer | A comparison of surgeons' posture during laparoscopic and open surgical procedures[END_REF] uses reflective markers visible thanks to incandescent bulbs to capture the surgeon's posture. However, these devices may hinder the surgeon's movements, creating a possible bias, and are time-consuming to attach. Overall, the data obtained with these different devices are similar: movement frequency, angle calculation between body joints, and muscles activity.

Human pose estimation (HPE) algorithms have been developed and improved since the 80's and have been used to detect and monitor surgeons' posture detection [START_REF] Sarafianos | 3D Human pose estimation: A review of the literature and analysis of covariates[END_REF][START_REF] Aggarwal | Human motion analysis: a review[END_REF][START_REF] Gavrila | The Visual Analysis of Human Movement: A Survey[END_REF]. This technology has been rapidly implemented in different domains such as surveillance [START_REF] Gavrila | The Visual Analysis of Human Movement: A Survey[END_REF], athletics, and medical applications [START_REF] Aggarwal | Human motion analysis: a review[END_REF]. The HPE algorithm was the Pictorial Structure, using color and regression algorithms applied on 2 dimensional (2D) pictures [START_REF] Fischler | The Representation and Matching of Pictorial Structures[END_REF]. The democratization of deep learning has increased HPE accuracy and performance. For instance, the 'DeepPose' tool (2014) has with a HPE accuracy of 60% [START_REF] Khan | A Review of Human Pose Estimation from Single Image[END_REF][START_REF] Liu | 2-D Human Pose Estimation from Images Based on Deep Learning: A Review[END_REF][START_REF] Toshev | DeepPose: Human Pose Estimation via Deep Neural Networks[END_REF]. Since then many other algorithms have been developed to improve posture detection in different situations. Deep learning HPE methods have been used to address several challenges including multi-person detection and realtime pose estimation [START_REF] Cao | Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields[END_REF][START_REF] Cao | OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields[END_REF][START_REF] Chen | Monocular Human Pose Estimation: A Survey of Deep Learning-based Methods[END_REF]. For multi-person detection, two major approaches exist: "top-down" and "bottom-up". In "top-down" approaches, first people are detected and separated and then the body joints are detected. "Bottom-up" approaches move from joints to people [START_REF] Cao | Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields[END_REF][START_REF] Cao | OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields[END_REF][START_REF] Chen | Monocular Human Pose Estimation: A Survey of Deep Learning-based Methods[END_REF][START_REF] Dang | Deep learning based 2D human pose estimation: A survey[END_REF][START_REF] Tanugraha | Understanding OpenPose (with code reference)-Part 1[END_REF]. The most popular deep learning HPE tool is OpenPose because it allows multi-person pose detection, is the most documented method, and is an open-source algorithm [START_REF] Tanugraha | Understanding OpenPose (with code reference)-Part 1[END_REF][START_REF] Lichtman | An Overview of Human Pose Estimation with Deep Learning[END_REF]. It can also be used for real-time posture detection [START_REF] Cao | Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields[END_REF][START_REF] Cao | OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields[END_REF]. This "top-down" algorithm was trained to recognize different body joint dataset which is useful for adapting joint detection in function of the available images or videos [START_REF] Cao | OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields[END_REF][START_REF] Tanugraha | Understanding OpenPose (with code reference)-Part 1[END_REF][START_REF] Lichtman | An Overview of Human Pose Estimation with Deep Learning[END_REF][START_REF] Viswakumar | Human Gait Analysis Using OpenPose[END_REF].

The purpose of the present work was to observe different postural behaviours and to correlate their frequency with surgical expertise. These postural behaviours include those arising from discomfort hesitation, and those due to the surgical tool inference with the desired movement (i.e. "interfering movement"). Our hypothesis was that the number of interfering movements was higher for "novice" than for "expert" surgeons. To test this hypothesis, we developed an original and innovative mobility score to analyse and compare the surgeons' movements during a simulated surgical intervention. We also created a comprehensive heatmap that illustrates the median mobility scores. This representation is helpful to focus the analysis on exercises with the most differences among surgeons during simulation-based learning.

Materials and Methods

To test our hypothesis, a cohort of surgeons with different level of expertise were monitored while using a virtual reality arthroscopic simulator using a convenient non-invasive human pose detection method.

Virtual Reality Arthroscopic simulation training protocol

Sixty surgeons were recruited over 9 months (November 2020 to July 2021) for a controlled prospective observational study:

-36 "novices": junior residents (one or two years post-graduation); -12 "intermediate": < 100 arthroscopies as principal operator per year or < 5 years after the postgraduate diploma in orthopaedic surgery; -12 "experts": > 100 arthroscopies as principal operator per year and > 5 years after the postgraduate diploma in orthopaedic surgery.

These criteria to define the expertise level were previously used in a similar study [START_REF] Tronchot | Validation of virtual reality arthroscopy simulator relevance in characterising experienced surgeons[END_REF]. The cohort was multicentric and mainly composed of right-handed men. Women were under-represented in the "intermediate" and "experts" groups (Tab. 1). Informed consent was obtained from all participants. The Fundamentals of Arthroscopy Surgery (FAST) and KNEE modules from the VirtaMed AG (Zurich) ArthroS™ arthroscopy simulator were used for the study. The FAST module was used for basic exercises, and KNEE was used for more complex tasks [START_REF] Anetzberger | Ten hours of simulator training in arthroscopy are insufficient to reach the target level based on the Diagnostic Arthroscopic Skill Score[END_REF]. A standardised experimental set-up consisting of nine different exercises was proposed to each surgeons to evaluate all the technical arthroscopic competences. These exercises included also a simulated arthroscopic meniscectomy that was performed three times consecutively at the end of the session [START_REF] Tronchot | Validation of virtual reality arthroscopy simulator relevance in characterising experienced surgeons[END_REF]. These exercises were selected because they require precise surgical skills during real arthroscopic interventions. Each participant was recorded during the session using a frontal standard RGB camera (recording frequency of 30 Hertz and a resolution of 240 x 320 pixels). Recording was done using a Python script (version 3.7) on a dedicated laptop (16GB RAM, Intel core i7). Each recorded video was anonymized using a standard procedure to enable blind analysis.

Tab. A simplified version of OpenPose [START_REF] Viswakumar | Human Gait Analysis Using OpenPose[END_REF] was used to detect the participants' joints in the videos of their training session. This algorithm could be adapted using the detection confidence threshold as parameter to return the orthonormal coordinates of each joint 1 . The detection confidence threshold was automatically optimised to detect a precise list of body joints. Indeed, the simulator module hides the participants' lower body part (Fig. 1) that therefore cannot be detected by the algorithm in the input RGB images.

Fig. 1 Camera view of a surgeon using the KNEE module. The lower limbs and head are not visible or hidden 1 https://github.com/quanhua92/human-pose-estimation-opencv

Despite the confidence threshold parameter optimization, the resulting detection was considered too noisy. To filter and smooth the signal, a Savitzky-Golay filter was applied on abscissa and ordinates values of each detected joint [START_REF] Sadeghi | Optimum window length of Savitzky-Golay filters with arbitrary order[END_REF]. Two parameters were needed for this algorithm: the length of the sliding window and the polynomial degree that represents the data distribution. Both are explained in the following to subsections.

-

Length of the window

This parameter is essential to obtain a filtering close to the original data without making up information. There is no strict mathematical rule for this and the sliding window length is highly data dependent. To ensure that data were not over-smoothed, the window length was constrained as follow:

1 t ∑ t t=0 abs(x(t) -x(t) ′ ) > √ σ x 2 2 (1)
where 𝜎 𝑥 2 is the standard deviation of the original data, and x(t) and x(t)' are the original and Savitzky-Golay values, respectively, at the time t.

-Polynomial degree A third degree polynomial was found to best fit the original data after testing polynomial degrees from 2 to 5. Fig. 2 presents the denoising process with the Savitzky-Golay filter and these parameters.

Analysis of the 2D coordinates

The final joint coordinates were visualised using a virtual skeleton (Fig. 3.a and a movie in Supplementary Material). From this representation an original approach was developed to visualise and analyse posture as a movement heatmap (Fig. 3.b) and to calculate a novel mobility score.

-

Movement heatmap

The movement heatmap was created in two steps: i) partitioning of the camera coordinate space into a series of 10*10 pixel squares, and ii) computing the frequency at which each joint appeared in each squares. When a joint was included in one of the squares, its corresponding coefficient in the matrix was incremented by one. This step was repeated for each coordinate present in the exercise coordinate list (each time step). At the end of the process, the matrix is represented by a grey-scale picture, from light (low frequency) to dark (high frequency). This representation provides a global view of the movements performed by a surgeon during simulator exercises (Fig.

𝑀𝑆 = 1 - |𝑚𝑎𝑥 𝑡ℎ𝑒𝑜𝑟𝑦 -(𝑚𝑎𝑥 𝑜𝑏𝑠 -𝑄3)×4| 𝑓𝑟𝑎𝑚𝑒𝑠-𝑠𝑞𝑢𝑎𝑟𝑒𝑠 (2)
where frames and squares are the total number of frames that constitute the exercise video and the total number of incremented coefficients, respectively. The MS represents the distribution of joint coordinates in the global environment and ranges between 0 and 1. A score close to 0 indicates few movements, whereas values, close to 1 indicate a large number of joint movement. The MS was calculated for each surgeon, exercise, and joint combination. Importantly, the MS is height and camera position independent.

Statistics

As the MS did not follow a normal distribution (significant Shapiro-Wilk test), the Mann Whitney test was used to compare MS values among the expertise groups. Differences were considered significant if the p-value was < 0.05.

Results

To facilitate comparison and highlight differences in the three expertise groups, the median MS values of each implicated joint in the different exercises were represented using a grey scale intensity (Fig. 4). Several differences can be seen between the three groups. For instance, the median MS values for the left shoulder of "Novice 1" (upper part of Fig. 4) indicated that this surgeon moved a lot during the simulation exercises (MS between 0.9 and 1.0 for more than 80% of exercises (Fig. 4)). This movement profile was close to that of the "novices" group, but with higher scores for all exercises, with the exception of "image centering" and "probing".

To obtain an overview of the three expertise groups for all exercises, the mean MS for each group was calculated by grouping all joints and exercises: 0.823 (standard deviation: 0.22), 0.816 (standard deviation: 0.22), and 0.820 (standard deviation: 0.25) for the "novice", "intermediate" and "expert" groups, respectively. No significant difference was observed among these three mean global MS (p>0.05). When focusing on the individual joints, wrists and left elbow were moved frequently during each exercise. Moreover, the MS profiles for the same exercise (e.g. "telescoping" and "periscoping") were different in the three expertise. Overall, the MS profiles of the three expertise groups suggested that "novice" and "expert" surgeons had the median in the same gradient for many exercises compared with "intermediate" moving globally less than the others. Fig. 4 Upper part: representation of the left shoulder score for one "novice" surgeon for all exercises. Lower part, "mobility heatmap": median mobility score for each exercise and joint in the three expertise groups On the basis of the MS profile, the next analysis focused on a subset of joint-exercise pairs where the MS differences among expertise levels were most pronounced. This subset included exercises that required the most technical skills and therefore are more relevant for surgical training. This subset included both shoulders for "periscoping", "guided diagnostic'' and "guided meniscectomy 1" and the left shoulder for "probing". Fig. 5 shows boxplots of these scores, allowing for deeper visual analysis. Differences between expertise groups were most visible for "periscoping" where the "expert" group having significantly lower right shoulder mobility (p = 0.0215, p = 0.0379 compared with the novice and intermediate group, respectively) (Tab. 2). Similarly, the MS for left shoulder in the "guided diagnostic" exercise (p = 0.0392, p = 0.0193) and "guided meniscectomy 1" for the left shoulder (p = 0.0174, p = 0.0113) were higher in the expert group than the novice and intermediate groups. This analysis also emphasised the MS heterogeneity within the "expert" and "novice" groups, particularly for the "probing" exercise, as indicated by the large number of outliers.

Comparison of the median MS for each examined joint-exercise pair with the Mann Whitney test highlighted at least one significant difference between expertise groups. Overall, the "novice" and "intermediate" groups showed similar performance resulting in only one significant differences, for the "probing" exercise. Fig. 5 Boxplots of the right and left shoulder MS in the "periscoping", "guided diagnostic" and "guided meniscectomy 1" exercises and of the left shoulder MS for "probing". Blue, orange, and green boxes correspond to the "novice" (N), "intermediate "(I), and "expert" (E) groups respectively

Tab. 2 Comparison of median MS in function of the expertise level with the

To qualitatively understand these differences among expertise groups the videos were visually analysed to detect interfering movements. "Novice" surgeons had interfering movements and hesitation movements close to their chest that sometimes interfered with each other leading to non-smooth displacements. The "intermediate" expertise level group was the most heterogeneous. Compared with the "novice" group the frequency and amplitude of interfering movements were decreased in the "intermediate" group, and overall their movements were more similar to those of expert surgeons. In the "expert" group, interfering movements were rarer but participants often physically or verbally interacted with the work environment or the study operator (i.e. scratched themselves, pointed to the simulator screen). Our clinical partners were not surprised by these observations especially for the "novice" group, and confirmed they were common in the operating room.

Discussion

This study wanted to assess surgical postural skills in line with other studies in this domain. Previous studies analysed surgical ergonomics to estimate risks [START_REF] Dalager | Surgeons' posture and muscle strain during laparoscopic and robotic surgery[END_REF][START_REF] Athanasiadis | An analysis of the ergonomic risk of surgical trainees and experienced surgeons during laparoscopic procedures[END_REF][START_REF] Carbonaro | A Wearable Sensor-Based Platform for Surgeon Posture Monitoring: A Tool to Prevent Musculoskeletal Disorders[END_REF], or to compare open and laparoscopic surgical procedures [START_REF] Berguer | A comparison of surgeons' posture during laparoscopic and open surgical procedures[END_REF]. The most common methods rely on physical markers or sensors directly placed on the surgeon, such as Inertial Measurement Units (IMU), electromyographic sensors, or reflective bulbs [START_REF] Dalager | Surgeons' posture and muscle strain during laparoscopic and robotic surgery[END_REF][START_REF] Athanasiadis | An analysis of the ergonomic risk of surgical trainees and experienced surgeons during laparoscopic procedures[END_REF][START_REF] Berguer | A comparison of surgeons' posture during laparoscopic and open surgical procedures[END_REF][START_REF] Carbonaro | A Wearable Sensor-Based Platform for Surgeon Posture Monitoring: A Tool to Prevent Musculoskeletal Disorders[END_REF], that can be cumbersome. Concerning marker-less assessment, some studies used OpenPose to assess the surgeon's cognitive skills [START_REF] Dias | Psychophysiological Data and Computer Vision to Assess Cognitive Load and Team Dynamics in Cardiac Surgery[END_REF] or to perform automatic surgical procedure recognition [START_REF] Kishi | Convolutional Neural Network based on Temporal Pose Features for Surgical Procedure Recognition[END_REF]. Conversely, no study used marker-less methods to assess the surgeon's postural skills by comparing postural behaviour variability in function of the expertise level. Our study employed OpenPose and a novel quantification method to measure postural behaviours of different automatically detected joints in different surgical exercises. This allowed us to compare surgeons in a height-agnostic manner and independently of the camera positioning. Our study included several strengths such as: its multicentric data collection (sixty surgeons across nine French national hospitals) accessibility due to inexpensive and lighting recording equipment; and procedural reproducibility allowed by the simulator.

Shoulders showed the most significant differences among groups, whereas wrists displayed the highest MS for most exercises. This was explained by the impact of joint movements on the other joints. Indeed, when the shoulder had an accelerated movement, the impact on the elbow was amplified and even more on the wrist. The same scheme was observed when the elbow had an accelerated movement. This information explained why the biggest MS differences among groups and exercises concerned the shoulders and not the elbows and even less the wrists.

Mobility scores comparison highlighted significant differences between the "expert" group and the "novice" or "intermediate" groups (Tab. 2.) but not for all exercise-joint pair. This could be explained by the presence of outliers with extreme values within each expertise group, particularly for the right shoulder in the "novice" group during the periscoping exercise. The presence of outliers, above and below the median indicates that MS comparison was not fully adapted to study the postural skills and that this metric alone does not sufficiently describe interfering movements. In future this analysis will be paired with a gold standard ergonomic assessment because even expert clinicians often lack postural self-awareness skills, thus increasing the risk of injury [START_REF] Dalager | Surgeons' posture and muscle strain during laparoscopic and robotic surgery[END_REF][START_REF] Athanasiadis | An analysis of the ergonomic risk of surgical trainees and experienced surgeons during laparoscopic procedures[END_REF]. This was noted by our clinical collaborators especially concerning ergonomic differences resulting in using the endoscope and surgical instruments with both the dominant and non-dominant hands depending on the surgical side (i.e. left vs right knee).

Our qualitative results (interfering movements) can be explained by the different levels of knowledge and technical skills depending on the surgeon's expertise level, as shown by Morineau et al. [START_REF] Morineau | Decision Making During Preoperative Surgical Planning[END_REF]. They found that "intermediate" surgeons activated more conflicts and controls than "expert" and "novice" surgeons and this explained the reduced work amplitude for "intermediate" surgeons. Controls and conflicts were slightly lower in the "expert" than in the "intermediate" group and simulation exercises were less taxing than real surgery [START_REF] Morineau | Decision Making During Preoperative Surgical Planning[END_REF].

Interfering movements could also be explained by unintentional "gamification" that might have biased the last two repetition of the "guided meniscectomy" exercise [START_REF] Kapralos | An Overview of Virtual Simulation and Serious Gaming for Surgical Education and Training[END_REF]. Indeed, surgeons wanted to increase the score returned by the simulator (by reducing the operation time) without worrying about their posture and surgical movements. More precise sub-group analyse will be necessary to understand these cognitive aspects that could allow defining a quantitative link between cognitive state and postural behaviour. Moreover, the combination of cognitive and postural domains could redefine the expertise groups and may represent another approach to understand surgical posture, which we intend to investigate in the future.

Our current study has several limitations. Specifically, information was lacking about the lower limbs due to the simulator and camera position. Moreover, the absence of depth information from the monoscopic camera set-up led to reduced appreciation of three-dimensional movements [START_REF] Tronchot | Validation of virtual reality arthroscopy simulator relevance in characterising experienced surgeons[END_REF][START_REF] Anetzberger | Ten hours of simulator training in arthroscopy are insufficient to reach the target level based on the Diagnostic Arthroscopic Skill Score[END_REF]. The OpenPose joint detection could also be improved technically. This might lead to the removal of the parameterized filtering algorithm, and the increase of the overall method robustness. Lastly, it would be more pertinent to do the HPE in real-time to provide educational feedback to trainees. However, our 2D based method has many financial and utilisation advantages allowing a future leading to potentially more widespread use in the surgical theatre without interfering with the surgery itself. This would allow its use not only for training but also for continuous ergonomic analysis.

Conclusion

The study hypothesis was partially verified. Interfering movements were observed also in surgeons with higher expertise level, but they were different in the three groups. Exercises have been carefully selected, examing those that require precise technical skills reflective of real arthroscopic interventions and display the most differences observed using the global heatmap (Fig. 4).. The chosen 2D method with a standard camera was a non-invasive way to detect the surgeons' postures and therefore, may be used directly in operating room. The creation of movement heatmap and the corresponding MS provided interesting information about the physical skills of arthroscopic surgeons. Our approach highlighted several qualitative and quantitative differences in postural behaviour that reflect the surgical expertise level. In the future, this approach may be used for training purposes, and also for measuring and improving surgical ergonomics in the operating room.

Bibliography

Fig. 2

 2 Fig. 2 Graphical representation of the camera coordinates of the neck-body joint of one surgeon during the "periscoping" exercise in function of time (in millisecond; ms). Original signal before (in blue) (a) and after denoising (in red) (b) using a Savitzky-Golay filter with automatic window size and a third degree polynomial 2.3. Analysis of the 2D coordinates

  3.b).

Fig. 3

 3 Fig. 3 Representation of the surgeon's pose estimation by the simplified OpenPose algorithm (a); movement heatmap linked to the surgeon posture (b) -Mobility scoreThe movement heatmap showed the physical extent of joint motion in relation to the global environment. It was used to compute a mobility score (MS) that takes into account the theoretical maximum (maxtheory) value of the coefficient (when all joint coordinates are in the same 10*10 pixel square during the entire exercise) and the observed reached maximum (maxobs), defined by the maximum coefficient value (i.e. the one with the most joint coordinates during the whole exercise). The third quartile (Q3) takes into account the coefficient value distributions. The MS was calculated with the following formula:

1

  Description of the surgeon cohort

	Expertise level Number	Mean age (min/max)	Hospital localisation	Man/Woman	Right/Left handed
	Novice	36	25.17 (24/29)	Angers, Brest, Nantes, Rennes, Tours	26/10	21/5
	Intermediate	12	32.5 (30/39)	Angers, Lyon, Nantes, Rennes, Tours	11/1	12/0
	Expert	12	56.72 (39/70)	Angers, Bordeaux, Brest, Lille, Nantes, Paris, Rennes	11/1	11/1
	2.2.

Detection of the surgeons' posture

  Mann-Whitney test. Significant differences ( p-value < 0.05) are highlighted in grey

	Exercise	Body joint	Novice VS	Novice VS Expert	Intermediate VS
			Intermediate		Expert
	"Periscoping" Right Shoulder	0.2672	0.0215	0.0379
		Left Shoulder	0.4429	0.1024	0.1473
	"Guided	Right Shoulder	0.3164	0.0392	0.0193
	diagnostic"
		Left Shoulder	0.0854	0.2293	0.0538
	"Guided	Right Shoulder	0.3657	0.4659	0.3721
	meniscectomy
	1"
		Left Shoulder	0.3708	0.0174	0.0113
	"Probing"	Left Shoulder	0.0288	0.2677	0.1551