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

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.

[Identification of perforating vessels by augmented reality: Application for the deep inferior epigastric perforator flap]. / Repérage des vaisseaux perforants par réalité augmentée : application au lambeau perforant d'artère épigastrique inférieure profonde.

The augmented reality on smart glasses allows the surgeon to visualize three-dimensional virtual objects during surgery, superimposed in real time to the anatomy of the patient. This makes it possible to preserve the vision of the surgical field and to dispose of added computerized information without the need to use a physical surgical guide or a deported screen. TECHNIQUE: The three-dimensional objects that we used and visualized in augmented reality came from the reconstructions made from the CT-scans of the patients. These objects have been transferred through a dedicated application on stereoscopic smart glasses. The positioning and the stabilization of the virtual layers on the anatomy of the patients were obtained thanks to the recognition, by the glasses, of a tracker placed on the skin. We used this technology, in addition to the usual locating methods for preoperative planning and the selection of perforating vessels for 12 patients operated on a breast reconstruction, by perforating flap of deep lower epigastric artery. The "hands-free" smart glasses with two stereoscopic screens make it possible to provide the reconstructive surgeon with binocular visualization in the operative field of the vessels identified with the CT-scan.

The standard tangential fields used for breast irradiation do not allow optimal coverage and dose distribution in axillary levels I-II and the sentinel node area.

BACKGROUND: Recent data from ACOSOG Z0011 and NSABP B32 trials suggested no need for axillary lymph node dissection (ALND) in patients with micrometastatic involvement of the sentinel lymph node (SLN). The low rate of axillary recurrence was attributed to the axilla coverage by the tangential fields (TgFs) irradiation and systemic therapy. This study aimed to evaluate dose distribution and coverage of the axilla levels I-II and the SLN area. PATIENTS AND METHODS: One hundred and nine patients were analyzed according to three groups: group 1 (50 Gy; n = 18), group 2 (60 Gy; n = 34) and group 3 (66 Gy; n = 57). Patients were treated using the standard (STgF; n = 22) or high (HTgF; n = 87) TgF. RESULTS: The median doses delivered to level I using HTgF versus STgF were 33 and 20 Gy (P = 0.0001). The mean dose delivered to the SLN area was only 28 Gy. Additionally, the SLN area was totally included in the HTgF in 1 out of 12 patients who had intraoperative clip placement in the SNL area. CONCLUSIONS: TgFs provide a limited coverage of the axilla and the SNLB area. This information should be considered when only TgFs are planned to target the axilla in patients with a positive SLN without ALND. Standardization of locoregional radiotherapy in this situation is urgently needed.

[Preoperative angiographic CT-scan for perforator flap transfer. Clinical applications in an emergency unit of reconstructive surgery: four clinical cases]. / Intérêt de l'angio-TDM dans la chirurgie des lambeaux perforants. Applications dans une unité de chirurgie plastique et reconstructrice. A propos de quatre cas cliniques.

Our experience of the deep inferior epigastric artery perforator flap has led us to perform systematically an abdominal CT-scan for the pretherapeutic checking. This exam gives us a precise vascular mapping of musculocutaneous and septocutaneous perforators artery of the flap, may enable a better orientation in the dissection and reduce the surgery time. We have enlarged the indication of this exam to the members flaps who needs the dissection of a musculocutaneous or a septocutaneous perforators vessels: Nakajima's et al. classification [1]. The mapping of perforating vessels on 3D reconstruction pictures helps us to planify the vascular cutaneous autologous grafts.

Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment.

PURPOSE: The purpose of this study was to build and train a deep convolutional neural networks (CNN) algorithm to segment muscular body mass (MBM) to predict muscular surface from a two-dimensional axial computed tomography (CT) slice through L3 vertebra. MATERIALS AND METHODS: An ensemble of 15 deep learning models with a two-dimensional U-net architecture with a 4-level depth and 18 initial filters were trained to segment MBM. The muscular surface values were computed from the predicted masks and corrected with the algorithm's estimated bias. Resulting mask prediction and surface prediction were assessed using Dice similarity coefficient (DSC) and root mean squared error (RMSE) scores respectively using ground truth masks as standards of reference. RESULTS: A total of 1025 individual CT slices were used for training and validation and 500 additional axial CT slices were used for testing. The obtained mean DSC and RMSE on the test set were 0.97 and 3.7 cm2 respectively. CONCLUSION: Deep learning methods using convolutional neural networks algorithm enable a robust and automated extraction of CT derived MBM for sarcopenia assessment, which could be implemented in a clinical workflow.

Three artificial intelligence data challenges based on CT and MRI.

PURPOSE: The second edition of the artificial intelligence (AI) data challenge was organized by the French Society of Radiology with the aim to: (i), work on relevant public health issues; (ii), build large, multicentre, high quality databases; and (iii), include three-dimensional (3D) information and prognostic questions. MATERIALS AND METHODS: Relevant clinical questions were proposed by French subspecialty colleges of radiology. Their feasibility was assessed by experts in the field of AI. A dedicated platform was set up for inclusion centers to safely upload their anonymized examinations in compliance with general data protection regulation. The quality of the database was checked by experts weekly with annotations performed by radiologists. Multidisciplinary teams competed between September 11th and October 13th 2019. RESULTS: Three questions were selected using different imaging and evaluation modalities, including: pulmonary nodule detection and classification from 3D computed tomography (CT), prediction of expanded disability status scale in multiple sclerosis using 3D magnetic resonance imaging (MRI) and segmentation of muscular surface for sarcopenia estimation from two-dimensional CT. A total of 4347 examinations were gathered of which only 6% were excluded. Three independent databases from 24 individual centers were created. A total of 143 participants were split into 20 multidisciplinary teams. CONCLUSION: Three data challenges with over 1200 general data protection regulation compliant CT or MRI examinations each were organized. Future challenges should be made with more complex situations combining histopathological or genetic information to resemble real life situations faced by radiologists in routine practice.

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

PURPOSE: The goal of this data challenge was to create a structured dynamic with the following objectives: (1) teach radiologists the new rules of General Data Protection Regulation (GDPR), while building a large multicentric prospective database of ultrasound, computed tomography (CT) and MRI patient images; (2) build a network including radiologists, researchers, start-ups, large companies, and students from engineering schools, and; (3) provide all French stakeholders working together during 5 data challenges with a secured framework, offering a realistic picture of the benefits and concerns in October 2018. MATERIALS AND METHODS: Relevant clinical questions were chosen by the Société Francaise de Radiologie. The challenge was designed to respect all French ethical and data protection constraints. Multidisciplinary teams with at least one radiologist, one engineering student, and a company and/or research lab were gathered using different networks, and clinical databases were created accordingly. RESULTS: Five challenges were launched: detection of meniscal tears on MRI, segmentation of renal cortex on CT, detection and characterization of liver lesions on ultrasound, detection of breast lesions on MRI, and characterization of thyroid cartilage lesions on CT. A total of 5,170 images within 4 months were provided for the challenge by 46 radiology services. Twenty-six multidisciplinary teams with 181 contestants worked for one month on the challenges. Three challenges, meniscal tears, renal cortex, and liver lesions, resulted in an accuracy>90%. The fourth challenge (breast) reached 82% and the lastone (thyroid) 70%. CONCLUSION: Theses five challenges were able to gather a large community of radiologists, engineers, researchers, and companies in a very short period of time. The accurate results of three of the five modalities suggest that artificial intelligence is a promising tool in these radiology modalities.

Ipsilateral breast cancer recurrence after Deep Inferior Epigastric Perforator (DIEP) flap reconstruction: Incidence and radiological presentation.

PURPOSE: To assess the incidence and presentation of ipsilateral cancer recurrences (ICR) after deep inferior epigastric perforator (DIEP) flap reconstruction for breast cancer. PATIENTS AND METHODS: Data of 247 consecutive women with DIEP flap reconstruction after breast cancer in our institution between 1997 and 2009 were retrospectively reviewed. RESULTS: Mean follow-up time was 4.1years±3.2 (SD) (median: 3years; range: 1month - 14years). Thirty-one patients (12.5%, 95%CI: =8.7-17.3) presented 34 relapses, in average 4.1years±2.6 after mastectomy: 14 (41%) were ipsilateral, 6 (18%) contralateral and 14 (41%) metastatic. ICRs occurred earlier (3.9 vs. 5.8years; P<0.05) than non-ICRs. Most ICRs (10/14, 71%) involved the periphery of the flap and presented as palpable nodules. The remaining (4/14, 29%) involved the axilla and 3/4 (75%) were palpable. Imaging procedures detected infra-clinical ICRs in 3 of 10 imaged patients (30%). CONCLUSION: ICRs after DIEP flap reconstruction are more frequent than contralateral recurrences suggesting the need for imaging follow-up of the reconstructed breast.

Breast tomosynthesis: Dosimetry and image quality assessment on phantom.

PURPOSE: To evaluate using phantom study the average glandular dose (AGD) and image quality in breast tomosynthesis. MATERIALS AND METHODS: The study was performed with a full-field digital mammography system (Mammomat Inspiration(®), Siemens, Erlangen, Germany) combined with tomosynthesis equipment (3D). For AGD evaluation, polymethyl methacrylate (PMMA) plates and a dosimeter were used to directly measure the absorbed doses in 2D and in 3D. The doses were then compared to the doses displayed on the equipment using the Mann-Whitney test. Three phantoms, accredited for 2D digital mammography (MTM 100, ACR RMI 156, BR3D), were imaged three times in 2D then in 3D. For each acquisition, the AGD was recorded. For image quality assessment, scores, defined by the rate of visible inserts, obtained for each acquisition both in 2D and in 3D, and for each phantom, were compared (Kruskall-Wallis and post-hoc Dunn tests). RESULTS: There was no significant difference between the measured and displayed AGD, both in 2D and in 3D imaging (P>0.05). With identical acquisition parameters, AGD were significantly greater in 3D than in 2D P<0.01). For phantoms MTM 100 and ACR RMI 156, there was no significant difference between the rate of visible inserts in 2D and in 3D (P=0.06 and P=0.36, respectively). However for phantom BR3D, the rate was significantly higher in 3D than in 2D (P<0.0001). CONCLUSION: Doses are significantly greater in 3D than in 2D. With tomosynthesis, out of the three phantoms tested, only phantom BR3D showed a higher rate of visible inserts.

Imaging strategies before beginning treatment of colorectal liver metastases.

The management of colorectal intrahepatic metastases before resection is multidisciplinary and radiologists and nuclear medicine specialists play a major role. In accordance with the French National Guide for appropriate use of diagnostic imaging, the approach should be multimodal: a chest-abdomen and pelvic (CAP) CT scan and hepatic MRI are mandatory while PET-CT provides important additional information, in particular on intra-abdominal extrahepatic metastases. This multimodal approach emphasizes the importance of early and appropriate use of imaging in these patients, as well as the central role of multidisciplinary meetings in oncology.

Imaging benign hepatocellular tumors: atypical forms and diagnostic traps.

Management of patients with a benign hepatocellular tumor relies largely on imaging data; the diagnosis of focal nodular hyperplasia (FNH) must be made with certainty using MRI, because no other clinical or laboratory data can help diagnosis. It is also essential to identify adenomas to manage them appropriately. The radiological report in these situations is therefore of major importance. However, there are diagnostic traps. The aim of this paper is to present the keys to the diagnosis of benign lesions and to warn of the main diagnostic pitfalls.

[Evaluation of noninvasive diagnostic criteria for hepatocellular carcinoma on pretransplant MRI (2010): correlation between MR imaging features and histological features on liver specimen]. / Évaluation des critères diagnostiques non invasifs du carcinome hépatocellulaire sur IRM pré-greffe hépatique (2010) : corrélations IRM - anatomopathologiques sur explants hépatiques.

PURPOSE: To validate the 2010 diagnostic criteria from the American Association for the Study of Liver Diseases (AASLD) for hepatocellular carcinoma (HCC) on MRI using the surgical liver specimen as a gold standard. PATIENTS AND METHODS: A total of 21 liver transplant recipients were retrospectively included. Each underwent surgery because of HCC between January 2007 and January 2008. Pre-transplant MRI was performed on a 1.5 Tesla MR unit. The T1W and T2W signal and kinetic contrast enhancement were correlated for each lesion with the surgical specimen. Lesion diameters between MRI and specimen were compared (Spearman). A multivariate model was created (R statistics software package) to predict the presence and grade of tumor differentiation (WHO, Edmonson Steiner). RESULTS: A total of 71 nodules were detected at histology, including 54 HCC (mean size: 25.3mm) compared to 68 on MRI. There was moderate agreement (r=0.58, P<0.001) between the maximum lesion diameters measured on MRI and at histology. Wash-out on MRI provided an accuracy of 75 % for the detection of HCC (sensitivity=75 %, specificity=76 %). Adding T2W hyperintensity to the AASLD criteria increased the sensitivity of MRI from 70.3 % to 77.7 % for the diagnosis of HCC and from 67.6 % to 79 % for nodules less than 20mm in diameter, without affecting specificity. On multivariate analysis, wash out as a single variable was significantly associated with a diagnosis of HCC (P<0.01, odds ratio 12.0, CI 95 % [2.6-55.5]). T1W hyperintensity (P=0.04, odds ratio 5.4) and loss of signal on opposed-phase images (P=0.02, odds ratio 9.2) were predictive of good differentiation. CONCLUSION: On MRI, the AASLD criteria or presence of wash out within a liver nodule in patients with underlying chronic hepatocellular disease are suggestive of tumoral transformation. The addition of T2W hyperintensity to the AASLD criteria increases the detection of HCC, especially nodules smaller than 20mm.