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4 results on '"Isabelle Doutriaux-Dumoulin"'

1. Breast nodule classification with two-dimensional ultrasound using Mask-RCNN ensemble aggregation

Author

Pascal Kbaier, Alexandre Popoff, Nathalie Lassau, Isabelle Thomassin-Naggara, Caroline Raynaud, Héloise Dapvril, Sana Harguem-Zayani, Imad Bousaid, Isabelle Doutriaux-Dumoulin, Foucauld Chamming's, Mathilde Charlot, Luc Ceugnart, Ewan Evain, Thomas Caramella, Antoine Olivier, Joseph Orabona, Corinne Balleyguier, Tiphaine Fourquet, Cybèle Ciofolo-Veit, Michele Monroc, and Audrey Haquin

Subjects
medicine.medical_specialty, Radiological and Ultrasound Technology, Artificial neural network, business.industry, Deep learning, Ultrasound, Nodule (medicine), Two dimensional ultrasound, General Medicine, Convolutional neural network, Area Under Curve, Test set, medicine, Humans, Radiology, Nuclear Medicine and imaging, Segmentation, Neural Networks, Computer, Artificial intelligence, Radiology, medicine.symptom, business, Algorithms, Ultrasonography
Abstract

Purpose The purpose of this study was to create a deep learning algorithm to infer the benign or malignant nature of breast nodules using two-dimensional B-mode ultrasound data initially marked as BI-RADS 3 and 4. Materials and methods An ensemble of mask region-based convolutional neural networks (Mask-RCNN) combining nodule segmentation and classification were trained to explicitly localize the nodule and generate a probability of the nodule to be malignant on two-dimensional B-mode ultrasound. These probabilities were aggregated at test time to produce final results. Resulting inferences were assessed using area under the curve (AUC). Results A total of 460 ultrasound images of breast nodules classified as BI-RADS 3 or 4 were included. There were 295 benign and 165 malignant breast nodules used for training and validation, and another 137 breast nodules images used for testing. As a part of the challenge, the distribution of benign and malignant breast nodules in the test database remained unknown. The obtained AUC was 0.69 (95% CI: 0.57–0.82) on the training set and 0.67 on the test set. Conclusion The proposed deep learning solution helps classify benign and malignant breast nodules based solely on two-dimensional ultrasound images initially marked as BIRADS 3 and 4.

Published
2021
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2. Opérer ou non une lésion atypique du sein ? Prise en compte de l’anxiété dans l’aide à la décision partagée à partir d’une cohorte prospective de 300 patientes

Author

Stefan Michiels, M. Cortet, Carole Mathelin, C. Tunon, Frédéric Marchal, Monique Cohen, Cécile Charles, L. Boulanger, D. Boinon, Flore Salviat, A. Favier, A.-V. Salomon, C. Vaysse, Suzette Delaloge, Isabelle Doutriaux-Dumoulin, V. Fermeaux, Veronique Boussion, Charles Coutant, Catherine Uzan, M. Espie, Chafika Mazouni, B. De Korvin, Nathalie Chabbert-Buffet, Sonia Zilberman, Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
medicine.medical_specialty, Younger age, media_common.quotation_subject, Anxiety, 03 medical and health sciences, Atypical breast lesion, 0302 clinical medicine, Breast cancer, Lésions atypiques, medicine, Perception du risque de cancer, Breast screening, Chirurgie, Cancer du sein, 030304 developmental biology, media_common, Gynecology, 0303 health sciences, business.industry, Obstetrics and Gynecology, medicine.disease, 3. Good health, Risk perception, Reproductive Medicine, Multicenter study, 030220 oncology & carcinogenesis, Temperament, Surgery, Perceived risk of developing breast cancer, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Decision process, medicine.symptom, business, Anxiété
Abstract

INTRODUCTION: Organized and individual breast screening have been accompanied by an increase in the detection of "atypical breast lesions "(ABL). Recently, the NOMAT multicenter study proposed a predictive model of the risk of developing breast cancer after detection of an ABL in order to avoid surgical removal of "low-risk" lesions. It also aimed to provide information on psychological experience, in particularly anxiety, to assist in the shared medical decision process. METHODS: Three hundred women undergoing surgery for ABL were included between 2015 and 2018 at 18 French centers. Women completed questionnaires before and after surgery assessing their level of anxiety (STAI-State, STAI-Trait), their level of tolerance to uncertainty, their perceived risk of developing a breast cancer, and their satisfaction with the management care. RESULTS: One hundred nighty nine patients completed the STAI-Status before and after surgery. Overall, a decrease in anxiety level (35.4 vs 42.7, p

Published
2021
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3. Prospective Multicenter Study Validate a Prediction Model for Surgery Uptake Among Women with Atypical Breast Lesions

Author

Magali Lacroix Triki, Monique Cohen, Corinne Balleyguier, Stefan Michiels, Catherine Uzan, Joelle Mollard, M. Espie, Suzette Delaloge, Anne Vincent Salomon, Pierre de Saint Hilaire, Natacha Joyon, L. Boulanger, Veronique Boussion, Flore Salviat, Christine Tunon de Lara, Brigitte De Korvin, Isabelle Doutriaux-Dumoulin, Charles Coutant, Caroline Rossoni, Nathalie Chabbert, Frédéric Marchal, Carole Mathelin, Chafika Mazouni, Sonia Zilberman, Eva Jouve, Service de Chirurgie et Cancérologie Gynécologique et Mammaire [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service d'Oncologie médicale [CHU Pitié-Salpêtrière], Centre de Recherche Saint-Antoine (CR Saint-Antoine), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Saint-Antoine [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut Gustave Roussy (IGR), Centre Eugène Marquis (CRLCC), Institut Bergonié [Bordeaux], UNICANCER, Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC), CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université - Faculté de Médecine (SU FM), Sorbonne Université (SU), Centre Jean Perrin [Clermont-Ferrand] (UNICANCER/CJP), Génétique et Biologie du Développement, Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Hopital Saint-Louis [AP-HP] (AP-HP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre Régional de Lutte contre le cancer Georges-François Leclerc [Dijon] (UNICANCER/CRLCC-CGFL), Institut de Cancérologie de Lorraine - Alexis Vautrin [Nancy] (UNICANCER/ICL), Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Centre Régional de Lutte contre le Cancer Oscar Lambret [Lille] (UNICANCER/Lille), Université Lille Nord de France (COMUE)-UNICANCER, Institut de Cancérologie de l'Ouest [Angers/Nantes] (UNICANCER/ICO), Institut Claudius Regaud, Institut Universitaire du Cancer de Toulouse - Oncopole (IUCT Oncopole - UMR 1037), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM), Les Hôpitaux Universitaires de Strasbourg (HUS), Hôpital de la Croix-Rousse [CHU - HCL], Hospices Civils de Lyon (HCL), Service de chirurgie gynécologique et mammaire [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre de Recherche Saint-Antoine (CRSA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Université de Lille-UNICANCER, Université de Toulouse (UT)-Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM), Gestionnaire, Hal Sorbonne Université, and Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
medicine.medical_specialty, medicine.medical_treatment, [SDV]Life Sciences [q-bio], Biopsy, Unnecessary Surgery, Population, Breast Neoplasms, Atypical ductal hyperplasia, Unnecessary Procedures, 03 medical and health sciences, Atypical breast lesion, 0302 clinical medicine, Breast cancer, Surgical oncology, medicine, Humans, Breast, Prospective Studies, education, B3 lesion, education.field_of_study, Hyperplasia, medicine.diagnostic_test, business.industry, Lumpectomy, Carcinoma, Ductal, Breast, Ductal carcinoma in situ, Cancer, medicine.disease, 3. Good health, Surgery, [SDV] Life Sciences [q-bio], Carcinoma, Intraductal, Noninfiltrating, Oncology, Multicenter study, 030220 oncology & carcinogenesis, 030211 gastroenterology & hepatology, Female, business, Carcinoma in Situ, Model
Abstract

International audience; Background: Diagnosis of atypical breast lesions (ABLs) leads to unnecessary surgery in 75-90% of women. We have previously developed a model including age, complete radiological target excision after biopsy, and focus size that predicts the probability of cancer at surgery. The present study aimed to validate this model in a prospective multicenter setting.- methods: Women with a recently diagnosed ABL on image-guided biopsy were recruited in 18 centers, before wire-guided localized excisional lumpectomy. Primary outcome was the negative predictive value (NPV) of the model.Results: The NOMAT model could be used in 287 of the 300 patients included (195 with ADH). At surgery, 12 invasive (all grade 1), and 43 in situ carcinomas were identified (all ABL: 55/287, 19%; ADH only: 49/195, 25%). The area under the receiving operating characteristics curve of the model was 0.64 (95% CI 0.58-0.69) for all ABL, and 0.63 for ADH only (95% CI 0.56-0.70). For the pre-specified threshold of 20% predicted probability of cancer, NPV was 82% (77-87%) for all ABL, and 77% (95% CI 71-83%) for patients with ADH. At a 10% threshold, NPV was 89% (84-94%) for all ABL, and 85% (95% CI 78--92%) for the ADH. At this threshold, 58% of the whole ABL population (and 54% of ADH patients) could have avoided surgery with only 2 missed invasive cancers.Conclusion: The NOMAT model could be useful to avoid unnecessary surgery among women with ABL, including for patients with ADH.

Published
2020
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4. Report of a unique case of gemcitabine-induced radiation recall myelitis following spinal cord irradiation

Author

Stéphane Supiot, Isabelle Doutriaux-Dumoulin, F. Thillays, and Ingrid Masson

Subjects
Chemotherapy, medicine.medical_specialty, business.industry, medicine.medical_treatment, Myelitis, Case Report, Context (language use), General Medicine, Spinal cord, medicine.disease, Radiation recall, Gemcitabine, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Medicine, Irradiation, Radiology, business, Lung cancer, 030217 neurology & neurosurgery, medicine.drug
Abstract

Radiation recall is a rare phenomenon, defined as an acute inflammatory reaction in a previously irradiated area, after administration of anti-tumor agents, including chemotherapy. It is most commonly reported to trigger skin reactions but internal organ involvement is possible, particularly with gemcitabine. We report here a unique case of a gemcitabine-induced radiation recall myelitis following spinal irradiation. A 53-year-old patient received analgesic irradiation of the seventh thoracic vertebra (T7) in the context of metastatic non-small cell lung cancer, at conventional radiotherapy dose and fractionation. She was subsequently treated with gemcitabine and developed myelitis whose chronology is compatible with a radiation recall reaction. Spinal MRI confirmed a T6–T7 spinal cord enhancement, with an associated spinal cord oedema. Corticosteroids and supportive care did not improve myelitis symptoms. The patient died within a year of the radiation recall, due to a metastatic progression of lung cancer. This is, to our knowledge, the first reported case of gemcitabine-induced radiation recall myelitis and only the third case involving the spinal cord. Radiation recall is a rare and poorly understood phenomenon and all cases should be reported.

Published
2020
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