Chantal Al Sabbagh

Johanne Seguin

Elena Agapova

Dounia Kramerich

Vincent Boudy

Dr Nathalie Mignet
email: nathalie.mignet@u-paris.fr

Thermosensitive hydrogels for local delivery of 5-fluorouracil as neoadjuvant or adjuvant therapy in colorectal cancer

Keywords: Critical micelle concentration, CMT: Critical micelle temperature, CRC: Colorectal cancer, CT26-luc: Luciferase-positive murine colon carcinoma cell line, HPLC-UV: High performance liquid chromatography with ultraviolet detection, IT: Intratumoral, P407: Poloxamer P407, P188: Poloxamer P188, PBS: Phosphate buffer saline solution, PEO: Poly(ethylene oxide), PPO: Poly(propylene oxide), SC: Subcutaneous, Tsol-gel Thermosensitive hydrogels, Poloxamers, 5-Fluorouracil, Colorectal CT26 cancer model, Local drug delivery

Spurred by high risk for local tumor recurrence and non-specific toxicity of systemic chemotherapy, clinicians have recently granted a growing interest to locoregional therapeutic strategies. In this perspective, we recently developed a multipurpose thermosensitive hydrogel based on reversible thermogelling properties of poloxamers P407 and P188, a bioadhesive excipient and antineoplastic effect of 5-fluorouracil (5-FU) for the local treatment of colorectal cancer (CRC) in ectopic CT26 murine models. Antitumor efficacy was assessed in mice following intratumoral (IT) injection mimicking neoadjuvant therapy and subcutaneous (SC) application after tumor excision simulating adjuvant therapy. Rheological characterization disclosed that P407/P188/alginate 20/2/1% w/v thermosensitive hydrogel is an injectable free-flowing solution at ambient temperature that undergoes a SOL-GEL transition at 26.0°C ± 0.6°C and thereby forms in situ a non-flowing gel at physiological temperature. The generated gel presented an elastic behavior and responded according to a shear-thinning fluid upon shear rate. Although delayed by the addition of alginate 1% w/v, 5-FU is released mainly by diffusion mechanism. The local delivery of 5-FU from P407/P188/alginate/5-FU 20/2/1/0.5% w/v hydrogel in the preclinical tumor models led to a significant tumor growth delay. These results demonstrated that poloxamer-based thermosensitive hydrogels provide a simple and efficient means for local chemotherapeutics delivery.

Introduction

Colorectal cancer (CRC) is the third most commonly diagnosed cancer (10.2% of the total cancer cases worldwide) and the second most lethal cancer worldwide with almost 880792 deaths in 2018 according to the World Health Organization [START_REF]Cancer fact sheets-All cancers, International Agency for Reserach on Cancer WHO[END_REF][START_REF] Ferlay | Global cancer observatory: cancer today[END_REF]. Patients with locally advanced (stage II-III) rectal cancer are treated with neoadjuvant chemoradiotherapy before surgery in order to reduce tumor size and improve disease-free survival [START_REF] Peeters | The TME trial after a median follow-up of 6 years: increased local control but no survival benefit in irradiated patients with resectable rectal carcinoma[END_REF][START_REF] Georgiou | Extended lymphadenectomy versus conventional surgery for rectal cancer: a meta-analysis[END_REF][START_REF] Benson | Rectal cancer, version 2.2015[END_REF]. Moreover, according to the 1990 NIH consensus recommendations, the treatment of colon cancer patients with stage III disease (lymph node involvement) has consisted of surgery aiming to excise tumor followed by adjuvant systemic chemotherapy to eradicate micrometastases and prevent recurrence [START_REF] Carrato | Adjuvant treatment of colorectal cancer[END_REF][START_REF] Hines | Prevalence and survival benefit of adjuvant chemotherapy in stage III colon cancer patients: Comparison of overall and age-stratified results by multivariable modeling and propensity score methodology in a population-based cohort[END_REF]. Each year, approximately 230,000 patients with colon cancer are eligible for adjuvant chemotherapy [START_REF] Benson | American Society of Clinical Oncology recommendations on adjuvant chemotherapy for stage II colon cancer[END_REF]. The benefits of 5-fluorouracil (5-FU)-based chemotherapy in reducing the risk of relapse and prolonging survival in patients are wellestablished [START_REF] André | Improved overall survival with oxaliplatin, fluorouracil, and leucovorin as adjuvant treatment in stage II or III colon cancer in the MOSAIC trial[END_REF]. However, the administration of 5-FU by systemic route results in short plasmatic half-life (11.4 min after bolus intravenous administration) and drug clearance from plasma within 1 hour as a consequence of a very rapid metabolism by the dihydropyrimidine dehydrogenase or uracil reductase enzymes [START_REF] Macmillan | Pharmacokinetics of fluorouracil in humans[END_REF]. Hence, this implies low drug concentration in tumor tissue and reduced overall efficacy. In addition, severe non-specific toxicities are reported as a consequence of the high doses of chemotherapeutic drugs administered systemically.

Therefore, tumor-targeting strategy such as local delivery of chemotherapeutic drugs is thought to provide a site-specific drug delivery and a better control of the on-site drug concentration, thus improving both safety and efficacy. A study carried out by Yi et al. on 5-FU-loaded polyethylene glycol hydrogel showed an optimized 5-FU pharmacokinetic with an elimination half-life of 0.9 hours, 6-fold longer than the free solution of 5-FU, both administered subcutaneously. The 5-FU-loaded polyethylene glycol hydrogel group showed a significant tumor growth inhibition in comparison to the untreated group and a significant enhanced tumor inhibition rate compared to the free solution of 5-FU group in mice bearing xenografted tumor [START_REF] Yi | Pharmacokinetic properties and antitumor efficacy of the 5-fluorouracil loaded PEG-hydrogel[END_REF].

Hydrogels are characterized by a hydrophilic polymer network capable to swell in the presence of water or physiological fluids leading to a three-dimensional structure [START_REF] Peppas | Hydrogels in pharmaceutical formulations[END_REF][START_REF] Klouda | Pluronic block copolymers as novel polymer therapeutics for drug and gene delivery[END_REF].

Thermosensitive hydrogels are composed of polymers responsive to a thermal stimulus.

Temperature change alters the interaction between hydrophilic and hydrophobic chains in the polymer with water molecules, thus inducing a phase transition of the polymeric solution from a solution (SOL state) to a gel (GEL state). This transition occurs in situ and it is commonly known as SOL-GEL transition. Accordingly, in situ-forming thermosensitive hydrogels have attracted increasing attention as local drug delivery systems for locoregional chemotherapy [START_REF] Wang | Drug release behavior from in situ gelatinized thermosensitive nanogel aqueous dispersions[END_REF][START_REF] Wang | 5-FU-hydrogel inhibits colorectal peritoneal carcinomatosis and tumor growth in mice[END_REF][START_REF] Ju | Thermosensitive micelles-hydrogel hybrid system based on poloxamer 407 for localized delivery of paclitaxel[END_REF][START_REF] Cho | Thermosensitive poly-(d, l-lactide-co-glycolide)-block-poly (ethylene glycol)-block-poly-(d, l-lactide-co-glycolide) hydrogels for multi-drug delivery[END_REF][START_REF] Ci | Tumor regression achieved by encapsulating a moderately soluble drug into a polymeric thermogel[END_REF][START_REF] Chen | Thermosensitive injectable hydrogel for simultaneous intraperitoneal delivery of doxorubicin and prevention of peritoneal adhesion[END_REF][START_REF] D.-Y. Fan | Injectable hydrogels for localized cancer therapy[END_REF][START_REF] Mao | Thermosensitive hydrogel system with paclitaxel liposomes used in localized drug delivery system for in situ treatment of tumor: better antitumor efficacy and lower toxicity[END_REF]. They allow an easy administration of injectable fluid solution that forms a semi-solid gel in response to physiological temperature as soon as it is in contact with tumor tissue. Thus, they have the potential to (a) deliver chemotherapeutic drugs locally to the tumor site leading to low dose requirements, (b) provide controlled and sustained drug release within tissues, (c) ensure drug diffusion into cells, (d) reduce multiple drug administration cycles, and (e) reduce systemic toxicities due to reduced systemic drug diffusion [START_REF] Wolinsky | Local drug delivery strategies for cancer treatment: gels, nanoparticles, polymeric films, rods, and wafers[END_REF][START_REF] Fakhari | Engineered in-situ depot-forming hydrogels for intratumoral drug delivery[END_REF].

Poloxamers are tri-block copolymers of poly(ethylene oxide)-poly(propylene oxide)poly(ethylene oxide) (PEO-PPO-PEO) which exhibit excellent thermosensitive properties [START_REF] Fakhari | Engineered in-situ depot-forming hydrogels for intratumoral drug delivery[END_REF][START_REF] Schmolka | Artificial skin I. Preparation and properties of pluronic F-127 gels for treatment of burns[END_REF]. They are non-toxic and FDA approved [START_REF] Rowe | Pharmaceutical Handbook of pharmaceutical excipients[END_REF]. Below their critical micelle concentration (CMC) and critical micelle temperature (CMT), poloxamers are in the form of individual block copolymer molecules (unimers) in solution. Above their CMC and CMT, copolymers self-assemble giving rise to a process defined as "micellization". An increasing temperature reaching their critical SOL-GEL transition temperature (Tsol-gel) results in the rearrangement of micelles and gel formation [START_REF] Goldstein | On the theory of lower critical solution points in hydrogen-bonded mixtures[END_REF].

Owing to its hydrophilic character, 5-FU represents an appropriate candidate to be incorporated into poloxamer hydrogel. A comparative study between 5-FU suppository and poloxamer-based in situ-gelling enema showed that enema provided higher rectal 5-FU concentrations for up to three hours compared to suppositories [START_REF] Wang | Development of in situ gelling and bio adhesive 5-fluorouracil enema[END_REF]. This could be mainly explained by a larger release area and a longer retention time of 5-FU in gelling enema formulation. Both suppositories and enema resulted in low 5-FU blood concentration compared to intravenous administration. In this sense, many topical and aerosolized formulations of 5-FU have been developed to treat local tumors [START_REF] Wang | 5-FU-hydrogel inhibits colorectal peritoneal carcinomatosis and tumor growth in mice[END_REF][START_REF] Paek | Poloxamer 188 and propylene glycol-based rectal suppository enhances anticancer effect of 5-fluorouracil in mice[END_REF][START_REF] Rokhade | Novel hydrogel microspheres of chitosan and pluronic F-127 for controlled release of 5-fluorouracil[END_REF]. Furthermore, intratumoral (IT) delivery of chemotherapeutic drugs constitutes an attractive strategy owing to its capacity to introduce the cytotoxic drugs directly into the tumor, hence limiting the systemic absorption, reducing the toxicity and increasing the overall efficacy [START_REF] Ju | Thermosensitive micelles-hydrogel hybrid system based on poloxamer 407 for localized delivery of paclitaxel[END_REF][START_REF] Lin | Novel thermo-sensitive hydrogel system with paclitaxel nanocrystals: High drug-loading, sustained drug release and extended local retention guaranteeing better efficacy and lower toxicity[END_REF].

Injectable thermosensitive hydrogels provide an efficient means for IT administration.

Consequently, alternative neoadjuvant and adjuvant treatments aiming to reduce tumor size prior to surgery and prevent recurrence after surgical excision of tumor, respectively, or treat small-sized tumor, thereby bypassing surgery, are highly required. Not only should said treatments increase life expectancy, but they are also expected to improve patient comfort by limiting chemotherapy toxicities. The aim of this work was to develop a multipurpose thermosensitive hydrogel capable to incorporate 5-FU for the local treatment of CRC by: 1) reducing tumor size prior to surgery, 2) preventing tumor recurrence after surgical resection in ectopic tumor models in mice. We have used Poloxamer P407 (P407) as thermosensitive gelling agent to prepare thermosensitive hydrogels. Poloxamer P188 (P188) was added to increase P407 Tsol-gel and reduce gelling time [START_REF] Chang | Rheological evaluation of thermosensitive and mucoadhesive vaginal gels in physiological conditions[END_REF]. Alginate and chitosan were included as natural, biocompatible and biodegradable polymers to impart adhesive, thickening and shearthinning properties [START_REF] Cho | Poloxamer/cyclodextrin/chitosan-based thermoreversible gel for intranasal delivery of fexofenadine hydrochloride[END_REF][START_REF] Cafaggi | Preparation and evaluation of a chitosan salt-poloxamer 407 based matrix for buccal drug delivery[END_REF][START_REF] Davidovich-Pinhas | Alginate-PEGAc: A new mucoadhesive polymer[END_REF]. Alginate is a linear, water-soluble polysaccharide copolymer composed of longer homo-polymeric regions of mannuronate and guluronate, potentially separated by regions of alternating structure mannuronate-guluronate. It is an anionic bioadhesive polymer which is known for its ability to create hydrogen bonds with mucin-type glycoproteins through carboxyl-hydroxyl interactions. Chitosan is a linear polysaccharide composed of D-glucosamine and N-acetyl-D-glucosamine units. As a polycationic biopolymer, chitosan is bioadhesive and readily binds to negatively charged surfaces such as mucosal membranes. Medium MW chitosan was utilized because it confers low viscosity to the hydrogel (the viscosity of a chitosan solution primarily depends proportionally on the average molecular weight of the polymer), it increases slightly the Tsol-gel [START_REF] Cho | Poloxamer/cyclodextrin/chitosan-based thermoreversible gel for intranasal delivery of fexofenadine hydrochloride[END_REF] and impart a mucoadhesion with no significant difference with low and high MW chitosan [START_REF] Hurler | Potentials of chitosan-based delivery systems in wound therapy: Bioadhesion study[END_REF]. Resulting formulations were carefully characterized in terms of thermogelling and rheological behaviors. 5-FU release from thermosensitive hydrogel was studied at 37°C in a flow-cell device. 5-FU release and hydrogel erosion were also tested in vitro. Finally, in vivo antitumor efficacy was assessed in two colorectal CT26 cancer model in BALB/c mice.

Materials and Methods

2.1.Materials

Poloxamer P407 (P407; Kolliphor ® P407; PEO98-PPO67-PEO98; MW 12.6 kDa) and poloxamer P188 (P188; Kolliphor ® P188; PEO80-PPO30-PEO80; MW 8.4 kDa) were purchased from BASF France. Sodium alginate (Protanal ® LF 10/60 FT; M:G ratio 25:75) was a gift from FMC Biopolymer (Little Island, Ireland). Chitosan chloride (Protasan TM UP CL 113; Ultrapure chitosan chloride salt; Deacetylation degree 75-90%; MW < 200 kDa) was supplied by NovaMatrix ® , FMC Biopolymer (Sandvika, Norway). 5-Fluorouracil (5-FU; MW 130.08 Da) was obtained from Acofarma (Madrid, Spain). Water used here was deionized "water for injection" obtained from C.D.M. Lavoisier (Paris, France). Phosphate buffer saline solution (PBS; pH 7.3; 0.01 M) was provided by Gibco, Life technologies (Saint Aubin, France). Drug and excipients were of European Pharmacopoeia grade whereas solvents were of analytical grade.

2.2.Thermosensitive hydrogel preparation

P407/P188-based hydrogel preparation

Thermosensitive hydrogels were prepared on a volume basis. Concentrations of all the components reported here are expressed as weight/volume percentage (% w/v). P407 and P188 were used and hydrogels are represented below as P407/P188 hydrogels. Hydrogels were prepared according to the "cold" method described by Schmolka [START_REF] Schmolka | Artificial skin I. Preparation and properties of pluronic F-127 gels for treatment of burns[END_REF]. Briefly, appropriate amounts of P407 and P188 powders were added to a volume of water. Dispersion was left under magnetic stirring overnight at 5°C ± 3°C until clear solution was obtained.

Water was then added to adjust the final volume of the hydrogel placed in an ice bath. After homogenization, resulting hydrogels were stored at 5°C ± 3°C for further studies. Three P407/P188 thermosensitive hydrogels were prepared yielding final concentrations of 17/1, 20/2 and 20/5% w/v, respectively.

Bioadhesive-contained hydrogel preparation

Two bioadhesive polymers i.e. alginate and chitosan, were investigated. For that purpose, concentrated solution of alginate or chitosan was first prepared by slowly adding appropriate amount of the bioadhesive powder to vigorously stirred water in order to avoid lumping.

Mixture was then stirred until complete hydration occurs and a clear viscous solution was obtained (1 hour). Afterwards, appropriate amounts of P407 and P188 powders were added and subsequent steps were precisely followed as described in the section above. Obtained hydrogels contained P407/P188 at 17/1, 20/2 and 20/5% w/v, respectively, and a bioadhesive polymer at a final concentration of 0.25, 0.5 or 1% w/v.

5-FU-loaded hydrogel preparation

In order to prepare 5-FU-loaded hydrogel, appropriate amount of 5-FU powder was weighed and added to a precise volume of P407/P188/alginate 20/2/1% w/v hydrogel. Mixture was protected from light and the drug was solubilized by magnetic stirring at 5°C ± 3°C yielding a final concentration of 0.5% w/v (5 mg/mL) 5-FU. After complete solubilization, the resulting hydrogel was stored at 5°C ± 3°C for further studies. P407/P188/alginate/5-FU 20/2/1/0.5% w/v hydrogel presented a pH value of 6.6 (supplementary Fig. S1).

2.3.Rheological characterization

Rheological analyses were performed using a rheometer (MCR102, Anton Paar, Germany) in a cone-and-plate geometry with a diameter of 50 mm (cone angle 1°). Samples were kept at 5°C ± 3°C until measurement. A solvent trap was used to minimize evaporation and to keep a solvent saturated atmosphere surrounding the sample. Measurements were performed in at least triplicate. Error bars were sometimes omitted to retain clarity.

Oscillation mode studies

Oscillatory studies allow to determine the viscoelastic properties of hydrogels by subjecting the sample to a sinusoidal shear stress. The hydrogel (730 µL) was placed on the pre-cooled Peltier plate (15°C) immediately prior to testing and submitted to a temperature sweep in the range of 15-45°C at a heating rate of 1°C/min. A Peltier controller unit was used to control the sample temperature with an accuracy of 0.1°C. The test was carried out at a controlled strain γ of 0.2% and constant frequency of 2 Hz. These parameters were determined prior to the test to define the linear viscoelastic regime where the stored elastic energy (storage or elastic modulus G') remained invariant and the sample did not undergo structural modifications (non-destructive dynamic conditions). The changes of G' modulus and the viscous dissipated energy (loss or viscous modulus G") were thus investigated. Oscillatory rheology provides the most sensitive measurement of the main parameters Tsol-gel, G' and G" moduli and the loss factor tangent δ (tanδ = G"/G').

Rotational mode studies

Rotational studies allow to determine the dynamic viscosity (η) and shear stress (τ) of hydrogels by subjecting the sample to constant or ascending shear rate. Herein, viscosity (η) was measured at 10 -1 s -1 shear rate at constant or gradient of temperature in the range of 15-45°C, while shear stress (τ) was obtained at a shear sweep between 10 -3 and 10 4 s -1 at 5°C and 37°C.

2.4.Hydrogel erosion

Hydrogel erosion study was performed in vitro at 37°C using a membrane-free release model. PBS (pH 7.3; 0.01 M) was used as release medium. Experiment met the sink conditions. In detail, under ice bath, 1 mL of the hydrogel was introduced into 20 mL transparent vials and placed at 5°C ± 3°C for 10 minutes in order to homogenize the distribution of the hydrogel at SOL state in the bottom of the vial. Afterwards, vials were placed in an incubator set at 37°C and allowed to gel for 30 minutes. Subsequently, 5 mL of pre-warmed (37°C) release medium, were gently layered over the surface of the gel and vials were stored in an orbital shaker/incubator (Orbital Shaker, Forma Scientific, Ohio, USA) and shaken at 50 rpm at 37°C. At specific time points (0, 0.5, 1, 3, 6, 24, 48 and 96 hours), 200 µL of the release medium were sampled and replaced with an equal volume of pre-warmed (37°C) fresh release medium. The concentrations of dissolved poloxamers in samples were measured by the colorimetric method of Baleux and the times required to erode 50% (T50%) or 80% (T80%) of the hydrogels were calculated. All measurements were conducted in triplicate and mean values ± standard deviations were reported.

2.5.Hydrogel erosion and 5-FU release

P407/P188/alginate/5-FU 20/2/1/0.5% w/v hydrogel erosion and 5-FU release from the hydrogel were conducted simultaneously in vitro at 37°C using a membrane-free release model. PBS (pH 7.3; 0.01 M) and water were used as release media. The experimental protocol was precisely followed as described in the section above. The concentrations of dissolved poloxamers and released 5-FU were measured by the colorimetric method of Baleux and HPLC-UV, respectively, in samples withdrawn at specific time points (0, 0.25, 0.5, 1, 3, 6, 9, 19 and 24 hours). In parallel, a solution of 5-FU (0.5% w/v) kept in the orbital shaker/incubator at 37°C was used as control to monitor the stability of 5-FU in the experiment conditions. All measurements were conducted in triplicate and mean values ± standard deviations were reported.

2.6.Poloxamer quantification by the colorimetric method of Baleux

To quantify dissolved poloxamers in the release medium, samples were centrifuged for 10 min at 14,000g in order to separate dissolved poloxamers from possible hydrogel fragments.

After centrifugation, supernatants were collected and assayed by the colorimetric method described by Baleux [START_REF] Baleux | Colorimetric determination of silver of nonionic polyoxyethylene surface using iodo-iodated solution[END_REF]. Briefly, 25 µL of potassium iodide (KI3) reagent was added to 1 mL of diluted supernatant. After homogenization, optical density was quickly measured at 440 nm to avoid photobleaching phenomenon of KI3 and the formed PEO-KI3 complex. A solution of 1 mL of water and 25 µL of the reagent has served as a reference. Results were calculated from linear regressions of P407 and P188 generated by dissolving known amounts of these copolymers in water in the concentration ranges of 0.05-20 μg/mL (supplementary Fig. S2). The cumulative percentage of hydrogel eroded was expressed as the weight percentage of dissolved poloxamers as a function of time.

2.7.5-FU quantification by HPLC-UV

The amount of released 5-FU occurring simultaneously with the hydrogel erosion was measured by high performance liquid chromatography with ultraviolet detection (HPLC-UV).

To this end, samples were diluted with appropriate volume of water to destroy poloxamer micelles. After 3 min of vortex, drug was separated from poloxamers and alginate through 0.5 mL Amicon Ultra centrifugal filters (cut-off 3 kDa, Millipore Corporation, Molsheim, France) by centrifugation at 14,000g for 40 min using a tabletop Eppendorf MiniSpin ® plus (Hamburg, Germany). Subsequently, ultrafiltrates free of polymers were collected and 5-FU was assayed by HPLC using a LC-20AD XR HPLC system (Shimadzu, Japan) connected to a Waters μBondapak ® C18 column (Guyancourt, France) (reversed phase, 300 mm X 3.9 mm i.d., 10 μm). Chromatographic conditions were the following: Isocratic elution, mobile phase of deionized water whose pH was adjusted to 4.5 with trifluoroacetic acid (0.001% v/v), flow rate 0.6 mL/min with column temperature maintained at 25°C, an injection volume of 20 μL and an UV detection at 266 nm. Results were calculated from linear regression of 5-FU generated by dissolving known amounts of the drug in water in the concentration range of 5-50 μg/mL. The cumulative percentage of 5-FU released over time was expressed as the weight percentage of 5-FU.

2.8.In vitro 5-FU release in T-cell for flow-through dissolution

This study was meant to determine in vitro 5-FU release behavior from poloxamer hydrogel and the consecutive effect of addition of alginate 1% w/v on drug release rate. Two hydrogels were tested: P407/P188/5-FU 20/2/0.5% w/v and P407/P188/alginate/5-FU 20/2/1/0.5% w/v. T-cell for flow-through dissolution (membrane-free model) provided by the company Sotax (Switzerland) was utilized and water was used as the release medium. Experiment met the sink conditions. In detail, 150 µL of each hydrogel was introduced in the pit of the cell, placed in an incubator at 37°C and allowed to gel for 30 minutes. Subsequently, the cell was reinserted in the flow-cell system where the release medium flows continuously at 37°C. At specific times (0, 1, 2, 3, 4, 5, 6, 24 and 48 hours), 500 µL of the release medium were sampled and replaced with an equal volume of pre-warmed (37°C) fresh release medium.

Collected samples were analyzed as described in the previous section and the percentage of 5-FU was determined by HPLC-UV at 266 nm. All measurements were run in triplicate, data are expressed as the mean ± standard deviations.

In vivo antitumor efficacy

In vivo experiments were carried out in female BALB/cJRJ mice (Janvier, St Genest de Lisle, France), aged from 6 to 7 weeks and kept under SPF (specific pathogen free) conditions for 1 week before the study with free access to standard food and water. Animal experiments were conducted in compliance with the principles of care and use of laboratory animals of the European and national guidelines and were approved by the institutional ethics committee.

Tumor models development

The CT26.WT murine colon carcinoma cell line was purchased from American Type Culture Collection (ATCC, CRL-2638, LGC Standards, Molsheim, France). The luciferase-positive cell line (CT26-luc) was generated by transfection of CT26.WT cell line with luciferase gene as reporter. CT26-luc cells were cultured at 37°C in a 5% CO2-humidified atmosphere in Dulbecco's Modified Eagle Medium (DMEM, Gibco Life Technologies) supplemented with 10% fetal bovine serum (FBS, Gibco Life Technologies), 1% penicillin/streptomycin and 0.08% of Geneticin (G418 sulfate, Gibco Life Technologies). CRC tumor model was developed as previously described [START_REF] Seguin | Evaluation of nonradiative clinical imaging techniques for the longitudinal assessment of tumour growth in murine CT26 colon carcinoma[END_REF]. Briefly, 10 5 CT26-luc cells in 100 µL of DMEM culture medium were injected subcutaneously into the right and left flanks of the mouse.

Fifteen days later, the size of the subcutaneous (SC) tumor was around 1000 mm 3 . The tumorbearing mouse was sacrificed, the CT26-luc tumor was resected and placed into DMEM culture medium. Tumor was then cut into 20-30 mm 3 fragments and inoculated subcutaneously, through a 12 gauge trocar (38 mm), into the right and the left mouse flanks previously disinfected with alcohol. Those mice were subsequently used for the antitumor efficacy studies. In each mice, both tumors were treated identically.

IT injection of hydrogel in neoadjuvant therapy model

On the eighth day, mice bore a SC tumor of 63.8 mm 3 ± 10.6 mm 3 mean volume. Mice were randomly separated into four groups of five mice each. Mice were anesthetized by intraperitoneal injection of 300 µL of Ketamine (80 mg/kg) and Xylazine (10 mg/kg), and the areas around their two tumors were shaved and disinfected with alcohol (Fig. 6A). During anesthesia, mice were kept at physiological temperature. Mice received a single injection of 60 µL of P407/P188/alginate/5-FU 20/2/1/0.5% w/v (corresponding to 15 mg 5-FU/kg body weight), 5-FU solution (0.5% w/v), P407/P188/alginate 20/2/1% w/v (5-FU-free hydrogel) or water (control group). Formulations were injected into the tumor via a 26Gx1/2'' needle.

SC application of hydrogel after surgical tumor excision (adjuvant therapy model)

Fourteen days after tumor fragment implantation, mice were randomized into two groups of three mice each. Mice were anesthetized and prepared as described in the previous section.

An incision of 1-2 cm was made in the proximity of the tumor and the latter was subsequently resected without leaving macroscopic residuals (Fig. 7A). In the remaining cavity, 100 µL of P407/P188/alginate/5-FU 20/2/1/0.5% w/v (corresponding to 25 mg 5-FU/kg body weight) were applied through a syringe. For the control group, 100 µL of P407/P188/alginate 20/2/1% w/v (5-FU-free hydrogel) were applied. Afterwards, the wound was closed with silk thread 5.0. 5-FU solution and water were not tested here as they cannot be retained in the tumor cavity.

Mice follow up

The viability, status and any visible toxicity changes at the injection sites of the mice were followed throughout the experiments. The body weight of each mouse was checked every other day and recorded as a function of time. Longitudinal monitoring of the tumor growth was performed thrice weekly by optical imaging and by caliper. To this end, 20 min before imaging, mice were injected intraperitoneally with 200 µL of 10 mg/mL luciferin solution (Dluciferin potassium salt, Interchim). Luciferin reacts with luciferase which produces a photon signal detected by the camera (Photon Imager™ Biospace Lab). Mice were thus imaged during 10 min while being under anesthesia with isoflurane. Image analysis was performed with the M3 Vision software developed by Biospace Lab. Likewise, tumor volume was measured with a caliper and the volume was estimated as follows: (length x width 2 )/2. This allowed to determine the time point for the mice killing. Mice were sacrificed as soon as their tumor volume exceeded 1000 mm 3 .

Statistical analysis

Multiple comparison tests for different experiments were conducted. Values represent means ± SD. ANOVA multiple comparison tests (Tukey's test and Bonferoni's test) were performed to determine significant differences. A Student's ttest was also used to compare the viscosity of alginate-containing hydrogel versus the chitosan-containing hydrogel. The level of significance was taken as p ≤ 0.05. Statistical analyses were performed with GraphPad Prism version 5 for Windows (GraphPad Software, La Jolla California USA).

Results and discussion

The unique property of thermosensitive hydrogels makes them efficient drug carrier for local drug delivery. Consequently, such system must meet a set of specifications compatible with the intended use. In the present context, the thermosensitive hydrogel must (a) be a fluid solution (SOL) at ambient temperature, (b) be injectable with a syringe after being combined with 5-FU at the SOL state and this owing to its low viscosity, i.e. < 1 Pa.s, which enables its flow and spreading over the tumor site, (c) exhibit a Tsol-gel around 26°C to 28°C to undergo a rapid SOL-GEL transition once administered in mouse, thus avoiding its dilution in physiological fluids [START_REF] Dumortier | A review of poloxamer 407 pharmaceutical and pharmacological characteristics[END_REF], (d) possess a G' modulus > 10x10 3 Pa and a loss factor tanδ < 1.0 at 37°C to yield a strong elastic gel [START_REF] Almdal | Towards a phenomenological definition of the term 'gel[END_REF][START_REF] Chen | Mechanical, rheological and release behaviors of a poloxamer 407/poloxamer 188/carbopol 940 thermosensitive composite hydrogel[END_REF], (e) provide in situ 5-FU release at the site of injection leading to a local antitumor effect.

3.1.Viscoelastic properties of P407/P188-based hydrogels

P407 is a water-soluble, non-ionic, thermosensitive copolymer with high CMC (2.8x10 -6 M at 37°C) and Tsol-gel due to weak hydrophobicity of PPO block [START_REF] Batrakova | Fundamental relationships between the composition of pluronic block copolymers and their hypersensitization effect in MDR cancer cells[END_REF]. At P407 concentrations below 15% w/v, though above the CMC, SOL-GEL transition does not probably occur [START_REF] Wang | Development of in situ gelling and bio adhesive 5-fluorouracil enema[END_REF][START_REF] Dumortier | Development of a thermogelling ophthalmic formulation of cysteine[END_REF]. Increasing the concentration, the Tsol-gel varies inversely with the concentration with a gel formation arising around 24°C at 20% w/v P407 [START_REF] Bonacucina | Effect of hydroxypropyl β-cyclodextrin on the self-assembling and thermogelation properties of Poloxamer 407[END_REF], thus impairing the characteristic of SOL state at ambient temperatures. Given that high P407 concentration is relevant to strengthen gel network and bioadhesion force [START_REF] Gilbert | Drug release from Pluronic F-127 gels[END_REF], P407 is often mixed to P188 to compensate for this drawback. P188 is more hydrophilic than P407 (hydrophilic-lipophilic balance of 29 vs. 22 at 22°C, respectively) [START_REF] Batrakova | Fundamental relationships between the composition of pluronic block copolymers and their hypersensitization effect in MDR cancer cells[END_REF] with lower molecular weight, thereby increasing the Tsol-gel and shear-thinning behavior of P407 [START_REF] Wang | Development of in situ gelling and bio adhesive 5-fluorouracil enema[END_REF][START_REF] Chang | Rheological evaluation of thermosensitive and mucoadhesive vaginal gels in physiological conditions[END_REF]. Furthermore, it is demonstrated that the combination of P407 (20% w/v) and P188 (2.5 and 5% w/v) resulted in hydrogels presenting suitable Tsol-gel [START_REF] Wang | Development of in situ gelling and bio adhesive 5-fluorouracil enema[END_REF]. Therefore, based on those data, three different P407/P188 ratios were considered: 17/1, 20/2 and 20/5. Viscoelastic properties were determined by oscillatory rheometry and results were illustrated in Fig. 1. Tsol-gel was chosen as the temperature at which both moduli, G' and G", were equal, reflecting similar elastic and viscous properties (G'G" crossover). Fig. 1A showed that, in accordance with the literature [START_REF] Wang | Development of in situ gelling and bio adhesive 5-fluorouracil enema[END_REF][START_REF] Zeng | Influence of additives on a thermosensitive hydrogel for buccal delivery of salbutamol: Relation between micellization, gelation, mechanic and release properties[END_REF], P188 tends to increase P407 Tsol-gel yielding a value of 26.5°C ± 0.3°C for the P407/P188 ratio 20/2 (as regard to 24°C for 20% w/v P407), consistent with the targeted range. G" modulus values were not affected by the variation of P407/P188 ratio (Fig. 1B).

Considering the storage modulus, G' was below 10x10 3 Pa for the P407/P188 ratio 17/1, highly dispersed between 1x10 3 Pa and 13x10 3 Pa for the P407/P188 ratio 20/5, whilst values for the P407/P188 20/2 ratio gathered in the range 11x10 3 to 16x10 3 Pa (Fig. 1C). 5% w/v of P188, thus produced a decrease in G' modulus values compared to those obtained with 2% w/v. Consistently, values of the loss factor tanδ were lower and less dispersed for the P407/P188 20/2 ratio and more importantly below 0.1, reflecting a G' higher than G" at 37°C (Fig. 1D). The relationship between storage modulus G' and loss modulus G" highlight the change of elasticity and viscosity between a weak hydrogel (tanδ > 1.0) and a strong hydrogel (tanδ < 1.0). When the loss factor tanδ is lower than 1.0, the G′ is greater than the G′′ and the material behaves like a strong hydrogel with elastic behavior and not like a viscous liquid.

From the rheology side, a high G′ is one of the inherent characteristics of solid materials [START_REF] Chen | Mechanical, rheological and release behaviors of a poloxamer 407/poloxamer 188/carbopol 940 thermosensitive composite hydrogel[END_REF].

Accordingly, P407/P188 20/2% w/v, made of uncrosslinked copolymers, behaves like a liquid below the Tsol-gel, while above this point, it turns into a gel and provides an elastic semi-solid material at 37°C.

3.2.Effect of bioadhesive polymers on hydrogel properties

To achieve a local drug delivery at the site of the tumor, bioadhesiveness of the hydrogel is an important point to increase its residence time on the injection site. To improve that characteristic, several methods have been exploited based mainly on covalent-cross-linking of chemical group to the poloxmer chains [START_REF] Hoare | Hydrogels in drug delivery: Progress and challenges[END_REF]. Bioadhesive force also increases with gel strength that depends on poloxamer concentration. Moreover, the presence of some bioadhesive polymers may also improve this property [START_REF] Giuliano | Mucosal applications of poloxamer 407based hydrogels: An overview[END_REF]. In this context, two natural bioadhesive polymers were selected, namely alginate and chitosan, and a range of concentration (i.e. 0.25, 0.5 and 1% w/v) was tested. Independently of the concentration, the addition of alginate and chitosan did not modify the rheological properties of P407/P188 hydrogels (supplementary Table S1). Only a slight increase in Tsol-gel in line with previous works [START_REF] Cho | Poloxamer/cyclodextrin/chitosan-based thermoreversible gel for intranasal delivery of fexofenadine hydrochloride[END_REF] was noted at low percentages. In the light of all the above, particularly the highest G' modulus and the lowest loss factor tanδ values obtained with P407/P188 20/2 ratio, the P407/P188 20/2% w/v hydrogel was expected to provide the strongest gel at the injection site and was thereby hereafter studied.

As alginate and chitosan exhibit viscosifying properties, their impact on hydrogel viscosity was therefore determined. Viscosity of P407/P188 20/2% w/v hydrogel was measured as a function of a temperature sweep in the range of 15-45°C at various percentages of bioadhesive, i.e. 0, 0.25, 0.5 and 1% w/v, at 10 -1 sec -1 shear rate (supplementary Fig. S3).

Temperature influenced viscosity with increasing heating resulting in ascending viscosity. This confirmed once again that the phase transition of poloxamer hydrogel was not altered by the addition of bioadhesives. Besides, this highlighted that below the Tsol-gel, hydrogel behaves like a low viscous liquid (η < 1 Pa.s), whereas above this point, it gains in viscosity converting into a viscous gel system at 37°C (1.4x10 3 < η < 1.7x10 3 Pa.s). Moreover, viscosity was determined at constant temperatures, i.e. 15°C and 37°C, corresponding to SOL and GEL states, respectively, and constant shear rate of 10 -1 sec -1 . At the SOL state, the addition of 1% w/v of alginate (0.50 Pa.s) or chitosan (0.18 Pa.s) caused a significant viscosity-enhancing effect compared to the bioadhesive-free hydrogel (0.04 Pa.s) (Fig. 2). However, viscosity enhancement remained markedly below 1 Pa.s. No significant difference was however observed at the GEL state (37°C). It is common knowledge that bioadhesive polymers increase adhesion but decrease syringeability by raising the viscosity. Hence, the observed viscosity rise of our hydrogel at the SOL state maintained the balance between adhesiveness, syringeability and injectability. Viscosity measured at 5°C and 37°C and very low shear rate (i.e. 10 -3 s -1 ) showed no significant difference between any of the tested bioadhesives (supplementary Fig. S4). Finally, hydrogel erosion study was conducted on these hydrogels at 37°C in vitro. No statistical difference was obtained between bioadhesivefree hydrogel and alginate-or chitosan-containing hydrogel in terms of the time required to erode 50% (T50%) or 80% (T80%) of the hydrogels. The values for T50% and T80% were between 14.5 and 23.5 hours, and 23.2 and 45.9 hours, respectively (supplementary Table S2).

Given, on one hand, the comparable results between alginate and chitosan with respect to the resulting viscosity at 37°C and hydrogel erosion kinetics, and, on the other hand, the wide use of alginate in tissue engineering [START_REF] Klöck | Biocompatibility of mannuronic acid-rich alginates[END_REF][START_REF] Lee | Degradable and injectable poly (aldehyde guluronate) hydrogels for bone tissue engineering[END_REF], and the availability of an injectable alginate grade listed in the European pharmacopoeial monograph, we opted for alginate 1% w/v for the further course of the study.

3.3.Viscoelastic and rheological behavior of P407/P188/alginate hydrogel

P407/P188/alginate 20/2/1% w/v hydrogel was characterized by oscillatory and rotational rheometry. G' and G" moduli and dynamic viscosity η were plotted as a function of the temperature (Fig. 3A). G' and G" moduli were constant as long as the temperature was below a critical value where both moduli rose sharply to new steady values characterizing the GEL state. G'G" crossover indicated 26.0°C ± 0.6°C as Tsol-gel. Storage modulus G' was of 15866 Pa ± 1397 Pa whilst loss factor tanδ was of 0.03, both at 37°C. Viscoelastic values were constantly assigned to a strong elastic gel at physiological temperature. In parallel, as temperature increased and hydrogel turned to GEL from SOL, viscosity followed a similar pattern than G' and G" moduli (Fig. 3A, right axis). Viscosity was practically constant (~ 0.5 Pa.s) then it increased abruptly once the temperature was higher than 25°C, reaching a new steady level with 1.6x10 3 Pa.s at 37°C. This brutal thickening of the solution reflects the selfassembling of the copolymers: at low temperatures (< 25°C), interactions are mostly intramolecular and become intermolecular at higher temperatures driving to gel formation.

The shear stress of P407/P188/alginate 20/2/1% w/v hydrogel (5°C and 37°C) with respect to the change in shear rate, in comparison with a Newtonian fluid, was profiled in Fig. 3B. As the shear rate was increased from 10 -3 to 10 4 s -1 , the shear stress rose at 5°C and remained stable at 37°C around 100 Pa. A solution whose shear stress is directly proportional to the shear rate is considered as a Newtonian fluid. Therefore, the hydrogel at 5°C can be assimilated to a Newtonian fluid. However, at 37°C, as expected, the hydrogel turned to a non-Newtonian fluid. Thus, the P407/P188/alginate hydrogel presented a shear-thinning flow at 37°C and this behavior confirmed the formation of gel above the Tsol-gel. This finding is consistent with the shear-thinning characteristics of poloxamer and alginate hydrogels due to the destruction of intermolecular bonds [START_REF] Chang | Rheological evaluation of thermosensitive and mucoadhesive vaginal gels in physiological conditions[END_REF][START_REF] Cuomo | Rheological characterization of hydrogels from alginate-based nanodispersion[END_REF]. The low viscosity and the absence of shearthinning behavior at 5°C revealed its SOL state. Likewise, this Newtonian-fluid behavior at the SOL state could be correlated to a good contact surface of the hydrogel at the injection site leading to a continual coverage and favorable bioadhesion.

3.4.In vitro release studies

Effect of hydrogel erosion on 5-FU release

Prior to choosing the 5-FU concentration to be loaded in the hydrogel, two factors were taken into account: drug solubility at 5°C ± 3°C and drug therapeutic dose. 5-FU has a temperaturedependent solubility (11.9 mg/mL at 20°C) which is considerably lowered at low temperature resulting in its crystallization [START_REF] Barberi-Heyob | Stability of 5fluorouracil solutions according to different parameters[END_REF]. Moreover, 5-FU therapeutic dose in mice is documented to be between 5 and 85 mg/kg body weight [START_REF] Yi | Pharmacokinetic properties and antitumor efficacy of the 5-fluorouracil loaded PEG-hydrogel[END_REF][START_REF] Alishekevitz | Differential Therapeutic Effects of Anti-VEGF-A Antibody in Different Tumor Models: Implications for Choosing Appropriate Tumor Models for Drug Testing[END_REF]. Hence, we opted for a concentration of 5 mg 5-FU/mL hydrogel (0.5% w/v) which provides an adequate drug dose in mice while avoiding insolubility matter at +5°C ± 3°C. It is worth noting that 5-FU (0.5% w/v) addition to the P407/P188/alginate 20/2/1% w/v hydrogel allows to maintain a Tsol-gel in the targeted range, as demonstrated by differential scanning calorimetry (supplementary Fig. S5). In vitro erosion behavior and concomitant 5-FU release from P407/P188/alginate 20/2/1% w/v hydrogel was studied at 37°C using a T-cell for flow-through dissolution. Cumulative 5-FU release and hydrogel erosion were presented on the left and right axis of the Fig. 4A, respectively. Results showed an initial fast release with 50% of 5-FU released in the first one hour and reached a total release after 9 hours. To better understand the release mechanism, the erosion of the hydrogel was also followed by measuring the poloxamer dissolved in the release medium using the Baleux dosage. The calibration curve is given in supplementary Fig. S2. Hydrogel exhibited a slow erosion with 50% of the poloxamers dissolved within 15 hours and a complete erosion measured after 24 hours. These two informations put together indicate that the major mechanism governing 5-FU release is diffusion. Similar results were obtained when water was used as release medium (data not shown). It is worth mentioning that the various mechanisms involved in drug release have been reviewed by Siepmann and Siepmann [START_REF] Siepmann | Mathematical modeling of drug delivery[END_REF]. 5-FU release from hydrogel is thereby reported to be rapid and characterized by a burst effect. Narasimhan and Langer showed that burst release was controlled by the solubility of drug, the drug diffusion coefficient and the initial drug distribution within the polymeric carrier [START_REF] Narasimhan | Zero-order release of micro-and macromolecules from polymeric devices: the role of the burst effect[END_REF]. 5-FU is a small hydrophilic (LogPoctanol/water = -0.89) drug molecule and the hydrogel network is a highly hydrated microscale environment. Thereby, it is expected that 5-FU diffuse freely through the extramicellar water channels of the hydrogels matrix. Our result is thus in agreement with previous works on 5-FU release from poloxamer-based hydrogels where total release was achieved within few hours (90% in 1h [START_REF] Wang | Development of in situ gelling and bio adhesive 5-fluorouracil enema[END_REF]). It is known that the diffusion coefficient of a drug in the hydrogel decreases with increasing P407 content and bioadhesive material content, consistent with a consequent increase in viscosity and gel rigidity. However, more concentrated poloxamer-based hydrogel, i.e. 30% and 35% w/v P407, were reported to be very viscous and have very low syringeability, so they were not suitable carriers for parenteral administrations [START_REF] Derakhshandeh | Thermosensitive Pluronic® hydrogel: prolonged injectable formulation for drug abuse[END_REF]. Relating to what was previously mentioned, a balance between administration and handling easiness, thermogelling and drug release rate from hydrogel is sought.

Meanwhile, 5-FU stability in solution and the hydrogel was monitored over time. 5-FU solution (0.5% w/v) was stable at 37°C along the study and served as a control (Fig. 4A).

When compared with 5-FU solution, the total released amount of 5-FU (97%) (Fig. 4A left axis) and the 5-FU chromatogram at 24 hours time point (Fig. 4B), showed that hydrogel composition did not compromise 5-FU stability at 37°C. Drug was noteworthy stable in both, solution and hydrogel matrices, for at least up to three days (data not shown).

Effect of alginate on 5-FU release

Our hydrogel is meant to be administered intratumorally or to be applied subcutaneously after tumor excision. It is well known that after tissular injection, drug first diffuses from the vehicle then it is transported by convection phenomenon through the blood flow. To simulate the intended application, 5-FU release from hydrogel was carried out using a flow-cell model. Fig. 5 illustrated that in P407/P188 20/2% w/v hydrogel, the release of 50% of the loaded 5-FU occurred within 2.8 hours, whereas, in presence of 1% w/v alginate, the 50% release took place after 6.6 hours. Alginate, though devoid of viscosity-enhancing effect on the P407/P188 20/2% w/v hydrogel at 37°C, was able to delay 5-FU release by two fold. Furthermore, the flow-cell model better mimics the tissular area by submitting the sample to the sole effect of the diffusion mechanism which explains the retardation of 5-FU release obtained here when compared to the Fig. 4A. To further retard release, the initial drug loading amount in hydrogel could be adjusted. In PEG-PCL-PEG hydrogel, doubling 5-FU amount resulted in delaying release from 83% to 66% in 24 hours [START_REF] Wang | 5-FU-hydrogel inhibits colorectal peritoneal carcinomatosis and tumor growth in mice[END_REF], whereas in P407 (25% w/w) hydrogel, an increase in initial 5-FU concentration from 0.1 to 1.0% w/v increased the drug release rate [START_REF] Miyazaki | Pluronic F-127 gels as a vehicle for topical administration of anticancer agents[END_REF]. Drug concentration increase is known to increase the diffusion coefficient of the drug and thereby would arise from the difference in experimental parameters including the administered 5-FU dose, protocol and schedule of the treatment [START_REF] Yi | Pharmacokinetic properties and antitumor efficacy of the 5-fluorouracil loaded PEG-hydrogel[END_REF][START_REF] Wang | 5-FU-hydrogel inhibits colorectal peritoneal carcinomatosis and tumor growth in mice[END_REF][START_REF] Jung | Peri-tumor administration of 5-fluorouracil sol-gel using a hollow microneedle for treatment of gastric cancer[END_REF]. Furthermore, the toxicity expressed in mean body weight loss was lower in the 5-FU hydrogel group (-0.4% ± 2.9 %) as compared to the 5-FU solution group (-3.6% ± 3.0 %) at the end of the study (Table 1). Although not significant, this finding suggests that in the solution group, more drug would reach the systemic circulation. The IT delivery of 5-FU through hydrogel might reduce the chance of systemic absorption and overall increase its efficacy. Drug toxicity is then limited within a localized area where tumor cells lie. Neoadjuvant chemotherapy is prescribed for patients with locally advanced stage of rectal cancer [START_REF] Peeters | The TME trial after a median follow-up of 6 years: increased local control but no survival benefit in irradiated patients with resectable rectal carcinoma[END_REF][START_REF] Georgiou | Extended lymphadenectomy versus conventional surgery for rectal cancer: a meta-analysis[END_REF][START_REF] Benson | Rectal cancer, version 2.2015[END_REF]. The thermosensitive hydrogel presented in this work is low viscous liquid (η < 1 Pa.s) and flowable formulation at ambient temperature, thus allowing an easy administration through syringe or fine catheter. Therefore, the clinical translation of the approach would be the IT injection of the hydrogel formulation containing the 5-FU at the rectal tumor site through an appropriate syringe-needle system [START_REF] Marabelle | Starting the fight in the tumor: expert recommendations for the development of human intratumoral immunotherapy (HIT-IT)[END_REF]. If required, an endoscopic guidance could be applied in order to achieve accurate injection of the target lesion. Hence, tumors which are unresectable due to their big size, would benefit from local neoadjuvant chemotherapy by IT injection of the drug-loaded hydrogel before surgery.

Hydrogel efficacy in the context of adjuvant therapy (after tumor excision)

Herein, the SC tumor was removed and the mice was locally treated at the excision site with the hydrogel. Solutions such as 5-FU or water were not tested here as they cannot be retained in the tumor cavity, the group which received 5-FU-free hydrogel served as a control group.

Mice weight, albeit decreased between day 14 and day 18, was stable afterwards showing a good tolerability for the treatment (Fig. 7B). This rapid weight loss happening on the day of treatment could be consecutive to the surgery procedure itself. Also here no systemic toxic effect was noted. The soft, moist surface, and affinity of the hydrogel with the tissues greatly reduce the stimulation of the mice body. The notable weight loss noted on day 34 in the 5-FUfree hydrogel group (-21.8%) was due to the toxicity of the tumor itself as previously explained. Significant tumor growth delay of fifteen days was obtained in the group treated with 5-FU hydrogel compared to the control group (p ≤ 0.01) (Fig. 7C). Concordant images of one representative mouse of each group were shown in Fig. 7D. Moreover, mice survival was increased in the 5-FU hydrogel-treated group as compared to the 5-FU-free hydrogel group which exhibited a median of survival of 32 days (Fig. 7E). In sum, 5-FU hydrogel has proved to be very efficient in inhibiting CT26 CRC local recurrence when applied locally along with tumor resection surgery.

Conclusion

We developed a P407/P188/alginate/5-FU 20/2/1/0.5% w/v thermosensitive hydrogel which possessed appropriate viscoelastic and physicochemical properties to ensure preclinical efficacy. At ambient temperature, hydrogel existed as free-flowing solution allowing injectability through a syringe and underwent a SOL-GEL transition at 26.0°C ± 0.6°C yielding a strong elastic gel at physiological temperature. While preserving drug stability, hydrogel achieved total 5-FU release between 24 and 48 hours in vitro. In two different local treatment modalities of CRC in mice, hydrogel demonstrated a significant tumor growth delay and local recurrence prophylaxis. After IT injection and post-excision application in neoadjuvant and adjuvant therapies, respectively, hydrogel was found to be efficient in suppressing tumor growth. Accordingly, stable drug release in the vicinity of tumor cells and localized cytotoxicity of 5-FU all contributed to facilitate the antitumor efficacy in mice models. Importantly, drug-free hydrogel, constituting the 5-FU vehicle, showed no toxic effect. P407/P188/alginate/5-FU 20/2/1/0.5% w/v thermosensitive hydrogel, though, represented an efficient local drug delivery system, further optimizations are foreseeable regarding sustaining even greater the release rate, for instance, by adjusting 5-FU initial loading and strengthening the gel network. Tables Table 1. The change in body weight and tumor volume in mice after a single injection on the eighth day of the different formulations in neoadjuvant therapy model.

Figure captions

Fig. 1 Fig. 2 Fig. 3 Fig. 4 (

 1234 Fig. 1 Effect of P407/P188 ratio on the rheological properties of P407/P188 thermosensitive hydrogel: (A) Tsol-gel, (B) loss (viscous) modulus G" at 37°C, (C) storage (elastic) modulus G' at 37°C, (D) loss factor tanδ at 37°C. Measurements were carried out in the linear viscoelastic range. n=13. (2-column fitting) Fig. 2 Viscosity of the thermosensitive hydrogel P407/P188 20/2% w/v upon addition of 1% w/v alginate or 1% w/v chitosan at (A) 15°C (SOL state) and (B) 37°C (GEL state). Viscosity was measured at 10 -1 sec -1 shear rate. n=3 mean ± SD. One way ANOVA with Tukey's multiple comparison test ns P > 0.05, * P ≤ 0.05, **** P ≤ 0.0001. (2-column fitting) Fig. 3 Rheological characterization of P407/P188/alginate 20/2/1% w/v thermosensitive hydrogel. (A) Variation of storage (elastic) modulus G' (left axis), loss (viscous) modulus G" (left axis) and viscosity η (right axis) as a function of a temperature sweep at 1°C/min heat rate. Viscosity was measured at 10 -1 sec -1 shear rate. (B) Rheogram (flow curve) plot showing shear stress τ as a function of shear rate at 5°C (SOL state) and 37°C (GEL state) compared to a Newtonian fluid. (2-column fitting) Fig. 4 (A) In vitro hydrogel erosion (right axis) and simultaneous 5-FU release (left axis) kinetics from P407/P188/alginate/5-FU 20/2/1/0.5% w/v in PBS at 37°C. 5-FU solution in PBS at 37°C was used as control for drug stability. n=3 mean ± SD. (B) Chromatograms of 5-FU eluted at 9.5 min from 5-FU solution and 5-FU hydrogel samples at 24 hours time point.

( 2 -Fig. 5 Fig. 6 Fig. 7

 2567 Fig. 5 Cumulative in vitro release of 5-FU from P407/P188/alginate/5-FU 20/2/1/0.5% w/v hydrogel (1% alginate) compared to release from P407/P188/5-FU 20/2/0.5% w/v hydrogel (w/o alginate) in water at 37°C in T-cell for flow-through dissolution. n=3 mean ± SD. (1-

Formulation

Acknowledgments

SATT Ile-de-France Innov is acknowledged for its financial support. The authors would like to thank the LIOPA optical animal imaging platform, school of Pharmacy (UMS 3612 CNRS) Life Imaging Facility of Paris Descartes University (Plateforme Imageries du Vivant), supported by France Life Imaging (grant ANR-11-INBS-0006), Infrastructures Biologie-Santé and the GDR-AIM.

its release rate. In addition, using poloxamer hydrogels conjugated to nanoparticles encapsulating the 5-FU would be also beneficial to delay the drug release [START_REF] Akash | Recent progress in biomedical applications of Pluronic (PF127): Pharmaceutical perspectives[END_REF].

3.5.

In vivo antitumor efficacy of P407/P188/alginate/5-FU 20/2/1/0.5% w/v hydrogel Subsequent to physicochemical characterization of the hydrogel, antitumor efficacy was assessed on CT26-luc CRC model following two different treatment modalities.

Hydrogel efficacy in the context of neoadjuvant therapy

All the tested formulations were injected in the primary tumor implanted subcutaneously.

Mice weight was stable following the injections (Fig. 6B), thus indicating the absence of systemic toxic effect due to the injected formulation. The drastic weight loss noted on day 18 in the control group (-11.6% ± 6.1%) and in the group which received the 5-FU-free hydrogel (-21.2% ± 2.8%) was due to the toxicity of the tumor itself which is known to be harmful towards mouse at advanced stage (mean tumor volumes 599.9 mm 3 ± 50.3 mm 3 and 574.5 mm 3 ± 62.7 mm 3 , respectively) (Table 1). In addition, significant tumor growth delay was seen in the group which received 5-FU hydrogel starting the day 13, i.e. five days after receiving the treatment, as compared to the control group (p ≤ 0.05) (Fig. 6C, supplementary Tables S3 andS4). The optical images of mice taken on day 15 showed a nearly disparition of the bioluminescence signal of both tumors in mice treated with 5-FU hydrogel compared to mice of the control group and mice which received the 5-FU-free hydrogel (Fig. 6D, supplementary Fig. S6). Since 5-FU-free hydrogel did not induce a reduction of the tumor size, the improved antitumor efficacy of 5-FU hydrogel was proven here to be due to the release of 5-FU. Likewise, in the 5-FU solution group, the mean tumor volume at day 18 was relatively similar to that of the group treated with 5-FU hydrogel (231.4 mm 3 ± 67.6 mm 3 and 275.5 mm 3 ± 36.9 mm 3 , respectively) (Table 1). This discrepancy with some data of the literature showing a superior efficacy of the 5-FU hydrogel compared with the 5-FU solution

Declaration of Competing Interest

The authors declare no conflict of interest.


Buntheng Ly

Sonny Finsterbach

Marta Nuñez-Garcia

Pierre Jais

Damien Garreau

Hubert Cochet

Maxime Sermesant
email: maxime.sermesant@inria.fr

Interpretable Prediction of Post-Infarct Ventricular Arrhythmia using Graph Convolutional Network

Keywords: Graph Neural Network, Ventricular Arrhythmia, Interpretable AI, Cardiac CT

Heterogeneity of left ventricular (LV) myocardium infarction scar plays an important role as anatomical substrate in ventricular arrhythmia (VA) mechanism. LV myocardium thinning, as observed on cardiac computed tomography (CT), has been shown to correlate with LV myocardial scar and with abnormal electrical activity. In this project, we propose an automatic pipeline for VA prediction, based on CT images, using a Graph Convolutional Network (GCN). The pipeline includes the segmentation of LV masks from the input CT image, the short-axis orientation reformatting, LV myocardium thickness computation and midwall surface mesh generation. An average LV mesh was computed and fitted to every patient in order to use the same number of vertices with point-to-point correspondence. The GCN model was trained using the thickness value as the node feature and the atlas edges as the adjacency matrix. This allows the model to process the data on the 3D patient anatomy and bypass the "grid" structure limitation of the traditional convolutional neural network. The model was trained and evaluated on a dataset of 600 patients (27% VA), using 451 (3/4) and 149 (1/4) patients as training and testing data, respectively. The evaluation results showed that the graph model (81% accuracy) outperformed the clinical baseline (67%), the left ventricular ejection fraction, and the scar size (73%). We further studied the interpretability of the trained model using LIME and integrated gradients and found promising results on the personalised discovering of the specific regions within the infarct area related to the arrhythmogenesis.

Introduction

VA is the an abnormal heart rhythm most observed leading to the sudden cardiac death (SCD), ranking among the highest causes of mortality in the developed countries [START_REF] Nielsen | (APHRS)/Latin American Heart Rhythm Society (LAHRS) expert consensus on risk assessment in cardiac arrhythmias: Use the right tool for the right outcome, in the right population[END_REF]. The current gold standard predictor of SCD is still the left ventricular ejection fraction (LVEF), despite a majority of SCDs occurred in patients with preserved LVEF (> 35%). The post-infarction scar on the LV myocardium (LVMYO) is recognised as the anatomical substrate of the VA mechanism. Nonetheless, identifying the precise arrhythmogenesis characteristics of the scar regions is still challenging, thus limiting its application in the clinical practice. Recent study has shown that the LVMYO scar can be located through the analysis of the LV wall thinning in CT imaging [START_REF] Mahida | Cardiac Imaging in Patients with Ventricular Tachycardia[END_REF], as the alternative to the late gadolinium enhancement (LGE) MRI. CT imaging is generally more accessible in terms of machine availability and patient compatibility (i.e. patients with metallic device) compared to MRI. For image processing, CT imaging also have higher image resolution and quantitative image intensity consistency between manufacturers, thus reducing the potential error in the automatic processing pipeline.

In recent years, Deep Learning (DL), notably the convolution neural network (CNN), has made a remarkable impact in medical image processing, ranging from semantic segmentation to diagnosis and outcome prediction. Although, the gridlike property of the CNN can limit its efficacy on the organs with specific 3D anatomy, such as the LVMYO. Our previous work proposed transforming the CT input image into the 2D bullseye representation of the LV thickness to remove the blank voxels of the endocardium [START_REF] Ly | Scar-Related Ventricular Arrhythmia Prediction from Imaging Using Explainable Deep Learning[END_REF]. However, the flattening of the 3D led to the distortion of the 3D heterogeneity of the thickness map, impacting the subsequent fitting of the DL model. On the other hand, graph neural networks have gained more applications in medical image processing and bioinformatics [START_REF] Zhang | Graph Neural Networks and Their Current Applications in Bioinformatics[END_REF], thanks to its adaptability to the specific data geometry.

In this study, we investigated the graph-level classification task using a model built with graph convolutional network (GCN) layers [START_REF] Kipf | Semi-Supervised Classification with Graph Convolutional Networks[END_REF], and the LV thickness map as input. Moreover, we studied the interpretability of the graph model using LIME [START_REF] Ribeiro | Explaining the Predictions of Any Classifier[END_REF] and integrated gradients [START_REF] Sundararajan | Axiomatic Attribution for Deep Networks[END_REF] to locate the specific regions contributed to the VA prediction and to gain better insight of the explicit arrhythmogenic regions from the model perspective.

Method

Our image processing pipeline formulates the 3D CT scan into a graph input. The processing steps were image segmentation, short-axis (SAX) reorientation, LVMYO thickness calculation, LV mid-wall meshing and average mesh fitting. From there, a graph classification network was built using the atlas mesh and the thickness value as input. The image processing pipeline and the model architecture are described in section 2.1 and section 2.2.

Image Processing

The 3D ventricular masks were segmented from the input CT image using a Dual-UNet segmentation model, composing of a "coarse" UNet [START_REF] Ronneberger | U-Net: Convolutional Networks for Biomedical Image Segmentation[END_REF] for ROI segmentation and a "refine" UNet for the cropped input segmentation. The required masks included the epicardium and endocardium of the LV and the epicardium of the RV. Using the LV and RV mask as landmarks, automatic SAX view reorientation was done using the method described in [START_REF] Nuñez-Garcia | Automatic Multiplanar CT Reformatting from Trans-Axial into Left Ventricle Short-Axis View[END_REF]. The SAX ventricular masks were then resampled isotropically at 0.5mm. The LV wall thickness and the mid-wall points were calculated using the Eulerian partial differential method as proposed by [START_REF] Yezzi | An Eulerian PDE Approach for Computing Tissue Thickness[END_REF]. The thickness value was normalised by clipping at 10mm then divided by 10. Then, the surface mid-wall mesh was generated from the mid-wall points using marching cube algorithm and uniformly remeshed using appoximated centroid voronoi diagrams (ACVD) method [START_REF] Valette | Approximated Centroidal Voronoi Diagrams for Uniform Polygonal Mesh Coarsening[END_REF]. Finally, an average mid-wall mesh was generated and fitted to every patient based on the large deformation diffeomorphic metric mapping (LDDMM) framework. The atlas fitting was done using the deterministic atlas function provided by the Deformetrica software [START_REF] Bône | Deformetrica 4: An Open-Source Software for Statistical Shape Analysis[END_REF]. Rigid registration of the meshes was done prior to atlas fitting. As the mesh rotation and size were already registered in the SAX reorientation step, we translated the centre of mass of all the meshes toward a reference from a randomly selected mesh. At inference, the atlas mesh could be directly registered to the new mesh using affine registration. The image process steps are shown in Fig. 1.I.

Graph Convolutional Network Model

We built the model using the GCN layer [START_REF] Kipf | Semi-Supervised Classification with Graph Convolutional Networks[END_REF], which used the following convolutional operation:

X = D-1 2 Â D 1 2 XW + b , (1)
where X ∈ R N ×F is the output of N nodes and F filters, X ∈ R N ×C is the input of C features, W ∈ R C×F is the weights, b is the bias, D ∈ R N ×N the degree matrix, and  ∈ R N ×N is the self-loop adjacency matrix (  = I N + A).

We considered the LV mid-wall mesh as an indirect graph G = (V, E) with N nodes v i ∈ V and edges (v i , v j ) ∈ E. We used the thickness value of each node v i as the input feature X ∈ R N ×1 . Since the input were uniformly remeshed, no edge feature was use. The adjacency matrix A was extracted from the atlas mesh edges and used for every inputs. The LV mesh could then be represented as a graph G = (X, A). Index Pooling. We employed the pooling method as proposed by [START_REF] Simonovsky | Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs[END_REF], where a coarse graph was generated to pre-define the corresponding pooling index and the new adjacency matrix during the model construction. In our case, the coarse graph was generated using the ACVD uniform meshing, with reduced number of points, and the corresponding pooling indexes were defined using kdimensional tree nearest neighbour search (KD-tree NN). In this project, we built the index pooling layer using max pooling method. The graph coarsening and pooling indexes searching are computationally expensive, which is unfit for online processing. This pooling method is more suitable with a point-to-point corespondent graph input, as the pooling indexes of the atlas mesh can be applied to all the input graphs. The index pooling steps are shown in Fig. 1.III.

Model Architecture. The model architecture is shown in Fig. 1.II. Starting with an input graph of N nodes, the model was built using two consecutive GCN layers, followed by an index pooling layer, reducing the aggregated graph to N dwn nodes. The pooling output was then passed through three more GCN layers, before feeding to the fully-connected network (FCN) classification block. We set the filter size to 64 for all the GCNs, except the last GCN, where the filter was set to 1. The classification block was built with 4 fully-connected layers with [128, 64, 32, 2] units, respectively. We applied linear rectifier activation the first 3 layers and the softmax activation for the output layer. The model was trained using the binary cross-entropy loss. The model was built using tools provided by Spektral1 (GCN layer) and Tensorflow2 .

Interpretability Study

We studied the interpretability of the graph neural network by adapting to our context two existing methods: Local Interpretable Model-agnostic Explanation (LIME, [START_REF] Ribeiro | Explaining the Predictions of Any Classifier[END_REF]), and integrated gradients [START_REF] Sundararajan | Axiomatic Attribution for Deep Networks[END_REF].

LIME. To summarize briefly, in the case of image data LIME computes a local surrogate linear model based on the absence or presence of superpixels. Our usecase is similar if we consider the input graph G = (X, A) as an image with pixel values defined as the thickness. Following [START_REF] Garreau | What does LIME really see in images?[END_REF], our method can be described as:

1. segment the mesh into d patches; 2. randomly turn on/off the patches to create new inputs G 1 = (X 1 , A),. . . , G n = (X n , A); 3. run the model prediction on all the new inputs y i f (G i ); 4. compute βn by fitting the y i s to a local weighted surrogate model.

We used two segmentation methods in step 1. The first is quick shift [START_REF] Vedaldi | Quick Shift and Kernel Methods for Mode Seeking[END_REF], as is default for the image version of LIME, which bases the segmentation on both the nodes 3D coordinates and the thickness value 3 . We scaled the magnitude of the node coordinates and thickness value using scikit-learn standard feature scaler 4 . The quickshift algorithm was then applied with the distance threshold of 0.2. The second is grid segmentation with KD-tree NN, which is based only on the nodes 3D coordinates. The mesh was first downsampled to 30 mm radius using voxel downsampling, before running the KD-Tree search, which generated a quasi uniform grid segmentation of the input mesh. Turning the patches i on meant replacing the original value of patch with the replacement value, and vice versa. To study the case of VA+ classification, the replacement value was set to 1 to represent the normalised healthy LVMYO, under the hypothesis that the completely healthy LV would be classified as VA-.

Integrated gradients. Integrated gradients is computed as the integral of backpropagated gradients of the straightline path from the baseline input x to the original input x. To adapt the method to the graph network, the integrated gradients along the dimension i th for a model f (G) with the input graph G = (X, A) and baseline graph G = (X , A) was calculated as:

IG i (G = (X, A)) := (X i -X i ) × 1 α=0 ∂f (X + α(X -X ), A) ∂X i dα , (2)
where α ∈ [0, 1] denotes the step coefficients between the baseline input (α = 0) to the input (α = 1). We set the number of step to 50. We set the baseline feature X the same way as the replacement input in LIME by changing the thickness feature value to 1.

Experimental Setup

We studied our method using a retrospective dataset of 600 patients, collected between 2010 and 2020. The dataset included the CT images captured at diastolic of patients with history myocardial infarction (MI) at least 1 month before the scan date and without any history of LV surgery. The dataset included 27.5% of patients labelled as VA+. The VA inclusion criteria were any episode of ventricular tachycardia (VT) or fibrillation (VF), and aborted cardiac arrest. The total population was randomly divided at 1 : 4 ratio, resulting in 451 and 149 patients for training and testing, respectively. Two-sample t-test was used on all the available clinical characteristics to ensure that there was no significant difference between the training and testing population. The available characteristics in the dataset were age, gender, hypertension, diabetes, dyslipidaemia, smoking, LVEF, scar size and scar age. The scar size was calculated as the area on the LV surface with < 5cm thickness, and the scar age was calculated as the delay between the MI and the scan date.

Baseline Models

DL Model. We studied the performance of the GCN-Pooling model against the baseline DL models using 10-fold cross-validation on the training dataset.

Using the 2D thickness bullseye prediction pipeline proposed by [START_REF] Ly | Scar-Related Ventricular Arrhythmia Prediction from Imaging Using Explainable Deep Learning[END_REF], we tested two models: the conditional variational autoencoder classification (CVAE-Class) model and the direct CNN classification model (using the same layers as the CVAE-Class without the decoder). To test the performance of the traditional CNNs, we also run the cross-validation test with the 3D LV wall mask as input, using the 3D variant of the VAE-Class (without the condition) and direct CNN model. We used the SAX oriented LV wall masks to ensured the rotation and the voxel spacing consistency between inputs.

For the graph input, we generated two sets of LV mid-wall meshes at 500 and 5000 nodes using the pipeline described in section 2.1. With the atlas-fitted inputs, we run cross-validation on the GCN-Pooling, GCN (without index pooling) and FCN model. The baseline GCN model was built with the same layers as the GCN-Pooling, and the FCN model was built the same layers as the classifier block (4-consecutive fully-connected layers). As ablation study, we also run cross-validation on the GCN and FCN model using the rigid registered remesh inputs without the atlas fitting.

Clinical Baseline. Finally, we compared the best DL model against the clinical characteristics. With training dataset, we trained the best DL model and run univariate analysis to find the significant variables associated with VA. Then, the optimal cut-off values were calculated with the receiver operator curve (ROC) analysis [START_REF] Unal | Defining an Optimal Cut-Point Value in ROC Analysis: An Alternative Approach[END_REF] using the following equation:

Cutoff Optimal = min(|AUC -Spe c | + |AUC -Sen c |) . ( 3
)
We then compared the generalisability of the DL model and the cutoff values on the testing dataset.

Results

The Tab. 1 shows the cross-validation results of the DL models. The GCN-Pooling model outperformed the baselines models with the cross-validate accuracy of 0.818 ± 0.06. It outperformed the 2D and 3D input models (both CVAE-Class and CNN-Class), thus proving that the LV wall thickness could be formulated as graph to accurately predict the presence/absence of VA. The 3D models also underperformed compared to the 2D model, which further demonstrated the limit of the 3D CNNs in the classification task of the 3D anatomy such as the LV wall.

For the FCN and GCN models, the point-to-point correspondence was crucial for the models optimisation, as proven by the plummet in the accuracy of the models trained with non atlas fitting inputs. Without the index pooling, the 500-node models (FCN and GCN) outperformed the 5000-node models, however their accuracy could only reach 0.78. The prediction accuracy was increased for the 500-node models with additional node coordinates as the input feature. By adding the index pooling layer, the GCN-Pooling was able to properly learn the more complex heterogeneity of the 5000-node inputs and achieved higher prediction accuracy.

The univariate analysis on the training population clinical characteristics resulted in 4 significant variables (p < 0.01): LVEF, gender, scar size and scar age. The optimal cutoff values calculated from the dataset were 43%, 65cm 2 and 132months for the LVEF, scar size and scar age, respectively.

The evaluation results on the testing dataset are shown in Tab. 2. The 5000node GCN-Pooling model achieved the highest prediction accuracy at 0.812, followed by the scar-based markers at 0.725 (scar size) and 0.689 (scar age). The LVEF had the lowest performance at 0.671 accuracy.

Model Interpretability

The Fig. 2 shows the output coefficients of LIME and integrated gradients on a true positive prediction from the testing population. We could note the consistency of the high coefficient (blue) regions between the two methods. The high coefficient regions were also faithful among LIME outputs when the different segmentation methods were used.

We observed that the regions with prominent coefficient correlated strongly with the thinning regions of the LVMYO. This validates the hypothesis that the post-infarction LV thinning is associated with the presence of VA. On top of that, a closer inspection of the top coefficient patches showed that the GCN-Pooling model did not base its VA+ prediction on the entire thinning regions. Rather, higher coefficients were focused on smaller distinctive regions within or adjacent to the scar regions, as indicates by the yellow ellipsoids in the Fig. 2.

Discussion

Although, the testing dataset were not used during the designing and tuning of the model, the cross-validation and evaluation results were still based on mono-centre dataset. The retrospective nature of dataset could also introduce additional biases relating to the center imaging guideline, which skewed toward a selected population. Therefore, the current study population might not be the realistic representation of the general public. The interpretablity analysis only provided a perspective into the relation between the model prediction and the input. The high coefficient regions could be read as highly arrhythmogenic, simply because they were the regions allowing the model to classify the input as VA+. While the choice of the segmentation method in LIME is not trivial, we focused the analysis only on two segmen- tation methods, to limit the scope of this study. The quick shift method was chosen as it incorporates both physical coordinates and the thickness values of the node and was parameterised to generate small segments (by setting smaller threshold). On contrast, the grid segmentation method does not consider the thickness value and was parameterised to generate larger segments (using larger neighbour searching radius). Therefore, the consistency of the two LIME methods, as well as the integrated gradients, further solidify the tolerance of our interpretability approaches toward superpixel segmentation bias. Nevertheless, limiting by the retrospective aspect of the available data, the current analysis of the interpretability outputs were restricted to hypothesising.

Normalised Coefficient A). Thickness Map D). Integrated Gradients C). LIME (Grid Segment.) B). LIME (Quick Shift)

A prospective and multi-centre dataset is necessary to confirm the generalisability of the prediction pipeline and the validity of the detected arrhythmogenic site.

Conclusion

We proposed a novel automatic pipeline for VA prediction using the cardiac CT images. Formulating the LV thickness map into a graph input allowed the model to perform an accurate prediction of VA based on the 3D anatomy of the LV and achieved a better score then the model trained on the 2D input. The evaluation on the testing dataset showed that the GCN-Pooling model outperformed the clinical markers, especially comparing to the current gold standard predictor (LVEF). The interpretabiliy studies proved that the model derived its prediction

Fig. 1 .

 1 Fig. 1. Image processing pipeline, GCN-Pooling architecture and Index Pooling layer. The thickness input mesh was the result after fitting the average mesh to the mid-wall mesh, ensuring the point-to-point correspondence of every input. Index Pooling: a). pooling patches (from KD-tree NN); b). original (smaller spheres) and pooling nodes (bigger spheres); c & d). coarse graph.

Fig. 2 .

 2 Fig. 2. Interpretability studies of the GCN-Pooling model on a true positive prediction case from testing population. The yellow ellipsoids highlight the regions with consistently high coefficient among different methods. First row: inferior LV view; second row: apex view.

Table 1 .

 1 10-fold cross-validation of the DL baseline models. The results were diplayed as mean (±std). (*) Non average fitted input, (**) Non average fitted input with position and thickness features. Bold row: best accuracy model.

	Model	Input Shape	Accuracy	Sensitivity	Specificity
	CNN-class	256 × 256	0.775 (±0.05)	0.616 (±0.10)	0.834 (±0.06)
		240 × 240 × 288 0.759 (±0.06)	0.508 (±0.19)	0.853 (±0.05)
	(C)VAE-Class	256 × 256	0.788 (±0.06)	0.691 (±0.18)	0.825 (±0.05)
		240 × 240 × 288 0.775 (±0.06)	0.457 (±0.18)	0.875 (±0.03)
	FCN	N = 500*	0.604 (±0.04)	0.525 (±0.15)	0.643 (±0.09)
		N = 500**	0.700 (±0.06)	0.266 (±0.17)	0.862 (±0.05)
		N = 500	0.770 (±0.06)	0.716 (±0.18)	0.790 (±0.07)
		N = 5000*	0.706 (±0.07)	0.250 (±0.11)	0.878 (±0.09)
		N = 5000**	0.743 (±0.03)	0.120 (±0.09)	0.975 (±0.03)
		N = 5000	0.761 (±0.12)	0.775 (±0.17)	0.756 (±0.17)
	GCN	N = 500*	0.701 (±0.05)	0.626 (±0.09)	0.742 (±0.11)
		N = 500**	0.718 (±0.07)	0.766 (±0.17)	0.700 (±0.09)
		N = 500	0.784 (±0.08)	0.716 (±0.17)	0.809 (±0.09)
		N = 5000*	0.679 (±0.12)	0.633 (±0.17)	0.696 (±0.21)
		N = 5000**	0.677 (±0.09)	0.566 (±0.20)	0.718 (±0.16)
		N = 5000	0.779 (±0.08)	0.716 (±0.19)	0.803 (±0.10)
	GCN-Pooling N = 500	0.784 (±0.05)	0.808 (±0.07)	0.775 (±0.06)
		N = 5000	0.818 (±0.06) 0.766 (±0.10) 0.837 (±0.07)

Table 2 .

 2 Evaluation results on the testing population of the GCN-Pooling model and the clinical baselines.

		Accuracy	Sensitivity	Specificity
	GCN-Pooling (N = 5000)	0.812	0.780	0.824
	Scar Size > 65.49cm 2	0.725	0.683	0.741
	Scar Age > 132months	0.698	0.839	0.640
	LVEF < 43%	0.671	0.707	0.657

https://github.com/danielegrattarola/spektral

https://www.tensorflow.org/

https://github.com/Nick-Ol/MedoidShift-and-QuickShift

https://scikit-learn.org/

from the very specific regions within the greater scar regions, an encouraging evidence for the future work on the personalised identification of arrhythmogenic site of the LV.