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2. Three artificial intelligence data challenges based on CT and MRI

Author

Lassau, N., Bousaid, I., Chouzenoux, E., Lamarque, J.P., Charmettant, B., Azoulay, M., Cotton, F., Khalil, A., Lucidarme, O., Pigneur, F., Benaceur, Y., Sadate, A., Lederlin, M., Laurent, F., Chassagnon, G., Ernst, O., Ferreti, G., Diascorn, Y., Brillet, P.Y., Creze, M., Cassagnes, L., Caramella, C., Loubet, A., Dallongeville, A., Abassebay, N., Ohana, M., Banaste, N., Cadi, M., Behr, J., Boussel, L., Fournier, L., Zins, M., Beregi, J.P., Luciani, A., Cotten, A., and Meder, J.F.

Published
2020
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5. Five simultaneous artificial intelligence data challenges on ultrasound, CT, and MRI

Author

Lassau, N., Estienne, T., de Vomecourt, P., Azoulay, M., Cagnol, J., Garcia, G., Majer, M., Jehanno, E., Renard-Penna, R., Balleyguier, C., Bidault, F., Caramella, C., Jacques, T., Dubrulle, F., Behr, J., Poussange, N., Bocquet, J., Montagne, S., Cornelis, F., Faruch, M., Bresson, B., Brunelle, S., Jalaguier-Coudray, A., Amoretti, N., Blum, A., Paisant, A., Herreros, V., Rouviere, O., Si-Mohamed, S., Di Marco, L., Hauger, O., Garetier, M., Pigneur, F., Bergère, A., Cyteval, C., Fournier, L., Malhaire, C., Drape, J.-L., Poncelet, E., Bordonne, C., Cauliez, H., Budzik, J.-F., Boisserie, M., Willaume, T., Molière, S., Peyron Faure, N., Caius Giurca, S., Juhan, V., Caramella, T., Perrey, A., Desmots, F., Faivre-Pierre, M., Abitbol, M., Lotte, R., Istrati, D., Guenoun, D., Luciani, A., Zins, M., Meder, J.-F., and Cotten, A.

Published
2019
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14. 544P Nivolumab plus ipilimumab in microsatellite instability high (MSI)/mismatch repair-deficient (dMMR) metastatic colorectal cancer (mCRC): Final survival analysis and prognostic evaluation of GDF-15 in the phase II GERCOR NIPICOL study

Author

Depotte, L., Nay, P., Borg, C., Meurisse, A., Henriques, J., Bennouna, J., Fouchardiere, C. de la, Tougeron, D., Mazard, T., Chibaudel, B., Tournigand, C., Vernerey, D., Pigneur, F., André, T., and Cohen, R.

Published
2024
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19. Predicting Difficult Laparoscopic Total Mesorectal Excision for Locally-advanced Mid-low Rectal Cancer: The EuMaRCS Score Validation

Author

de'ANGELIS N, Martínez-Pérez A, Vitali GC, Pigneur F, Luciani A, Brunetti F, Kraft M, Martí-Martínez E, Moroni P, Espin E, Ris F, Pucciarelli S, and EuMaRCS Study Group

Subjects
locally advanced rectal cancer, total mesorectal excision, laparoscopy, Predictive score
Abstract

Background/Aim: The European MRI and Rectal Cancer Surgery (EuMaRCS) score was proposed to identify preoperatively difficult laparoscopic total mesorectal excision (L-TME) for locally advanced rectal cancer (LARC). This study aimed to test EuMaRCS's validity. Patients and Methods: Data were retrieved from a European multicenter database, including patients with mid/low LARC, treated with neoadjuvant chemoradiation therapy and L-TME with primary anastomosis. The EuMaRCS score was calculated on: BMI>30 (3 points), interspinous distance= T3b (4 points), and male sex (1 point). Results: The sample was composed of 141 patients, of whom 23 (16.3%) had a difficult L-TME. The EuMaRCS score demonstrated high accuracy in predicting difficult surgery (AROC: 0.806, 95%CI=0.720.88), with a cut-off >3 being associated with the best balance in sensitivity (82.6%) and specificity (66.1%). Conclusion: The EuMaRCS score represents a validated tool to predict preoperatively difficult L-TME in LARC patients.

Published
2020

20. Assessing surgical difficulty in locally advanced mid-low rectal cancer: the accuracy of two MRI-based predictive scores

Author

De'Angelis, N., Pigneur, F., Martinez-Perez, A., Vitali, G. C., Landi, F., Gomez-Abril, S. A., Assalino, M., Espin, E., Ris, F., Luciani, A., Brunetti, F., Alani, R., Aupin, L., Bianchi, G., Memeo, R., Petrucciani, N., Marti-Martinez, E., Ripolles, T., Breguet, R., Puppa, G., Terraz, S., Armario, D., Rodrigues, V., and Vera, M.

Subjects
Male, medicine.medical_specialty, Databases, Factual, Colorectal cancer, mri, rectal cancer, score, surgical difficulty, Anastomosis, Sensitivity and Specificity, External validity, 03 medical and health sciences, 0302 clinical medicine, Predictive Value of Tests, medicine, Humans, Stage (cooking), Rectal cancer, Retrospective Studies, Proctectomy, Receiver operating characteristic, Rectal Neoplasms, business.industry, Patient Selection, Rectum, Gastroenterology, Retrospective cohort study, Middle Aged, medicine.disease, Magnetic Resonance Imaging, Total mesorectal excision, Treatment Outcome, ROC Curve, Area Under Curve, 030220 oncology & carcinogenesis, Female, Laparoscopy, 030211 gastroenterology & hepatology, Radiology, business, Body mass index, MRI
Abstract

Aim Predicting surgical difficulty is a critical factor in the management of locally advanced rectal cancer (LARC). This study evaluates the accuracy and external validity of a recently published morphometric score to predict surgical difficulty and additionally proposes a new score to identify preoperatively LARC patients with a high risk of having a difficult surgery. Methods This is a retrospective study based on the European MRI and Rectal Cancer Surgery (EuMaRCS) database, including patients with mid/low LARC who were treated with neoadjuvant chemoradiation therapy and laparoscopic total mesorectal excision (L-TME) with primary anastomosis. For all patients, pretreatment and restaging MRI were available. Surgical difficulty was graded as high and low based upon a composite outcome, including operative (e.g. duration of surgery) and postoperative variables (e.g. hospital stay). Score accuracy was assessed by estimating sensitivity, specificity and area under the receiver operating characteristic curve (AROC). Results In a total of 136 LARC patients, 17 (12.5%) were graded as high surgical difficulty. The previously published score (calculated on body mass index, intertuberous distance, mesorectal fat area, type of anastomosis) showed low predictive value (sensitivity 11.8%; specificity 92.4%; AROC 0.612). The new EuMaRCS score was developed using the following significant predictors of surgical difficulty: body mass index > 30, interspinous distance < 96.4 mm, ymrT stage >= T3b and male sex. It demonstrated high accuracy (AROC 0.802). Conclusion The EuMaRCS score was found to be more sensitive and specific than the previous score in predicting surgical difficulty in LARC patients who are candidates for L-TME. However, this score has yet to be externally validated.

Published
2019

28. Predictors of surgical outcomes and survival in rectal cancer patients undergoing laparoscopic total mesorectal excision after neoadjuvant chemoradiation therapy: the interest of pelvimetry and restaging magnetic resonance imaging studies

Author

de'Angelis N, Pigneur F, Martínez-Pérez A, Vitali GC, Landi F, Torres-Sánchez T, Rodrigues V, Memeo R, Bianchi G, Brunetti F, Espin E, Ris F, Luciani A, and EuMaRCS Study Group

Abstract

Background: Locally advanced rectal cancer (LARC) requires a multimodal therapy tailored to the patient and tumor characteristics. Pretreatment magnetic resonance imaging (MRI) is necessary to stage the primary tumor, while restaging MRI, which is not systematically performed, may be of interest to identify poor responders to neoadjuvant chemoradiation therapy (NCRT), and redefine therapeutic approach. The EuMaRCS study group aimed to investigate the role and accuracy of pretreatment (including pelvimetry) and restaging MRIs in predicting surgical difficulties and surgical outcomes in LARC therapy. Methods: Patients with mid or low LARC who were administered NCRT, who underwent laparoscopic total mesorectal excision, and for whom pretreatment and restaging MRIs were available, were included. Results: MRIs of 170 patients (median age: 61 years) were reanalyzed by the same radiologist. Pelvimetry differed significantly between males and females, but no gender difference was noted in the clinical and tumor characteristics. Tumor volume and tumor height assessed on the restaging MRI were associated, respectively, with operative time and estimated blood loss. Conversion was predicted by tumor volume, interischial distance and pubic tubercle height. The quality of the surgical resection was found to be a predictor of overall and disease-free survival. The sensitivity and specificity of tumor regression grade 1 to identify a pathologic complete response were 76.9% and 89.3%, respectively. Conclusions: In LARC management, pelvimetry and restaging MRI may be useful to predict surgical difficulties and surgical outcomes. However, the main independent predictor of patient survival appears to be the achievement of a successful surgical resection.

Published
2018

30. Hommage au Professeur Alain Rahmouni

Author

Kobeiter, H., primary, Luciani, A., additional, Deux, J.F., additional, Hodel, J., additional, Tacher, V., additional, Anglade, M.C., additional, Baranes, L., additional, Beaussart, P., additional, Bouanane, M., additional, Chiaradia, M., additional, Dao, T.H., additional, Devillers, A., additional, Djabbari, M., additional, Kulski, A., additional, Legou, F., additional, Meyblum, E., additional, Pigneur, F., additional, You, K., additional, Derbel, H., additional, Galletto, A., additional, Kharrat, R., additional, Lotfalizadeh, E., additional, Sifaoui, I., additional, Vitellius, M., additional, Boutekadjirt, A., additional, Herin, E., additional, and Mulé, S., additional

Published
2018
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35. Tangential Fields (TgFs) Breast Radiation Therapy (RT): Prospective Evaluation of the Dose Distribution in the Axilla and the Sentinel Lymph Node Area (SLNA) Determined Intraoperatively by Clip Placement

Author

Belkacemi, Y., primary, Bigorie, V., additional, Pan, Q., additional, Bosc, R., additional, Bouaita, R., additional, Pigneur, F., additional, Guet, S., additional, Badaoui, H., additional, Assaf, E., additional, Caillet, P., additional, Itti, E., additional, and Calitchi, E., additional

Published
2014
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36. Radiothérapie mammaire adjuvante : les faisceaux tangentiels standard ne permettent pas une irradiation optimale des niveaux I et II axillaires et de la région du ganglion sentinelle

Author

Allab Pan, Q., primary, Grellier, N., additional, Bigorie, V., additional, Khodari, W., additional, Pigneur, F., additional, Beaussart, P., additional, Totobenazara, J., additional, Mège, J., additional, Caillet, P., additional, Dao, T., additional, Salmon, R., additional, Calitchi, E., additional, Bosc, R., additional, and Belkacémi, Y., additional

Published
2013
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