The Liver Tumor Segmentation Benchmark (LiTS).

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://medicaldecathlon.com/. In addition, both data and online evaluation are accessible via https://competitions.codalab.org/competitions/17094.

Magnetic resonance enterography in Crohn's disease patients: current state of the art and future perspectives.

INTRODUCTION: Crohn's disease (CD) is a major concern due to relatively high incidence and major complications like stricture or fistulas, often requiring surgical treatment. In recent years, magnetic resonance enterography (MRE) became a popular method of diagnosis and disease surveillance. The purpose of this review is to summarize and discuss the major and most recent advances in various aspects of MRE usage in diagnosong Crohn's disease, and to discuss advances in technique, disease activity monitoring and response to treatment. METHODS: A literature search was performed and relevant publications were included, with emphasis on articles from the past decade. AREAS COVERED: In this review we have presented articles with major advances in the field of MRE of CD patients such as proper sequence selection, recent advances in scoring of disease activity, differentiation between inflammation and fibrosis, response to treatment and technological advances such as the use of AI. EXPERT OPINION: The main goal in improving MRE performance will be sequence selection aimed at differenting between inflammation and stricture while shortening the study length adjusted to patient compliance, and developing a standardized scoring system for MRE reporting assisted by artificial intelligence.

Automated Detection of Crohn's Disease Intestinal Strictures on Capsule Endoscopy Images Using Deep Neural Networks.

BACKGROUND AND AIMS: Passable intestinal strictures are frequently detected on capsule endoscopy [CE]. Such strictures are a major component of inflammatory scores. Deep neural network technology for CE is emerging. However, the ability of deep neural networks to identify intestinal strictures on CE images of Crohn's disease [CD] patients has not yet been evaluated. METHODS: We tested a state-of-the-art deep learning network for detecting CE images of strictures. Images of normal mucosa, mucosal ulcers, and strictures of Crohn's disease patients were retrieved from our previously described CE image bank. Ulcers were classified as per degree of severity. We performed 10 cross-validation experiments. A clear patient-level separation was maintained between training and testing sets. RESULTS: Overall, the entire dataset included 27 892 CE images: 1942 stricture images, 14 266 normal mucosa images, and 11 684 ulcer images [mild: 7075, moderate: 2386, severe: 2223]. For classifying strictures versus non-strictures, the network exhibited an average accuracy of 93.5% [±6.7%]. The network achieved excellent differentiation between strictures and normal mucosa (area under the curve [AUC] 0.989), strictures and all ulcers [AUC 0.942], and between strictures and different grades of ulcers [for mild, moderate, and severe ulcers-AUCs 0.992, 0.975, and 0.889, respectively]. CONCLUSIONS: Deep neural networks are highly accurate in the detection of strictures on CE images in Crohn's disease. The network can accurately separate strictures from ulcers across the severity range. The current accuracy for the detection of ulcers and strictures by deep neural networks may allow for automated detection and grading of Crohn's disease-related findings on CE.

CT Image-based Decision Support System for Categorization of Liver Metastases Into Primary Cancer Sites: Initial Results.

RATIONALE AND OBJECTIVES: This study aimed to provide decision support for the human expert, to categorize liver metastases into their primary cancer sites. Currently, once a liver metastasis is detected, the process of finding the primary site is challenging, time-consuming, and requires multiple examinations. The proposed system can support the human expert in localizing the search for the cancer source by prioritizing the examinations to probable cancer sites. MATERIALS AND METHODS: The suggested method is a learning-based approach, using computed tomography (CT) data as the input source. Each metastasis is circumscribed by a radiologist in portal phase and in non-contrast CT images. Visual features are computed from these images, combined into feature vectors, and classified using support vector machine classification. A variety of different features were explored and tested. A leave-one-out cross-validation technique was conducted for classification evaluation. The methods were developed on a set of 50 lesion cases taken from 29 patients. RESULTS: Experiments were conducted on a separate set of 142 lesion cases taken from 71 patients with four different primary sites. Multiclass categorization results (four classes) achieved low accuracy results. However, the proposed system was found to provide promising results of 83% and 99% for top-2 and top-3 classification tasks, respectively. Moreover, when compared to the experts' ability to distinguish the different metastases, the system shows improved results. CONCLUSIONS: Automated systems, such as the one proposed, show promising new results and demonstrate new capabilities that, in the future, will be able to provide decision and treatment support for radiologists and oncologists, toward more efficient detection and treatment of cancer.

Assessment of patency capsule retention using MR diffusion-weighted imaging.

OBJECTIVES: Evaluate the ability of MR diffusion-weighted imaging (DWI) to predict patency capsule retention in Crohn's disease (CD). METHODS: Clinical and imaging data were prospectively reviewed for 80 CD patients following patency capsule administration and MR-DWI under institutional review board (IRB) approval with informed consent. Two radiologists separately assessed the presence/absence of restricted diffusion in the distal ileum. Apparent diffusion coefficients (ADC) from three regions of interest on the ileal wall were averaged. The association between restricted diffusion and retention, and sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated. Ability of ADC to predict retention was assessed with receiver operating characteristic (ROC) curve analysis. RESULTS: Restricted diffusion in the distal ileum was associated with capsule retention (p = 0.001, p < 0.0001). Sensitivity, specificity, PPV and NPV of restricted diffusion for capsule retention were 100.0%, 46.2%, 30.0%, 100% and 100.0%, 56.9%, 34.9%, 100%, respectively, for two radiologists. Accuracy of ADC to predict retention was high (area under the curve = 0.851, p < 0.0001). An ADC of 1.47 mm2/s showed 90.0% sensitivity and 50.0% specificity for retention. CONCLUSIONS: Sensitivity and NPV of restricted diffusion for patency capsule retention were 100%, suggesting that DWI may predict gastrointestinal tract capability to pass video camera endoscopy. KEY POINTS: • Capsule endoscopy enables assessment of the gastrointestinal mucosa in Crohn's disease • Prior patency capsule administration is recommended to evaluate gastrointestinal tract patency • MR diffusion-weighted imaging may detect pathological constriction of the ileum • Restricted diffusion in the distal ileum was associated with capsule retention • MR-DWI may predict gastrointestinal tract capability to pass capsule endoscopy.

Intraluminal Uterine Hypodensity in CT Scans of Postmenopausal Women: Recommendations for Interpretation.

OBJECTIVE: This study aims to investigate the association between intraluminal uterine hypodensity and uterine malignancy and establish thresholds that would minimize routine gynecological evaluation. METHODS: Two groups were recruited retrospectively: cancer group, which comprised 32 sequential endometrial cancer patients, and postmenopausal group, which comprised 63 women, with no known gynecologic malignancy.Two radiologists independently measured hypodensity, transversely in the axial plane and anterioposteriorly in the sagittal plane.The association between cancer and hypodensity was evaluated. Receiver operating characteristic curves were evaluated diameters predictive of cancer. RESULTS: Hypodensity was associated with cancer (cancer group, 93.8% vs. postmenopausal group, 38.1%; P < 0.0001). Hypodensity diameters correlated highly with prediction of cancer (transverse area under the curve, 0.899; anteroposterior area under the curve, 0.892). Diameters of 19.5 mm transverse and 6.0 mm anteroposterior yielded a sensitivity of 87% and 83% and specificity of 91% and 83%, respectively. CONCLUSIONS: Intrauterine hypodensity is a common finding in computed tomography scans of postmenopausal women. A transverse diameter of 19.5 mm and an anteroposterior diameter of 6.0 mm are suggested as thresholds for further gynecological sonographic evaluation.

Jejunal Diverticulitis.

BACKGROUND: Jejunal diverticulitis is a rare clinical entity often overlooked by physicians as a cause for abdominal pain. Although diagnostic capabilities improved in recent years, there is little data about diverticular disease in the proximal small bowel. The aim of this study is to present the clinical course and management in a series of eight cases of jejunal diverticulitis and possible therapeutic interventions. METHODS: A cohort retrospective analysis of all patients admitted for acute jejunal diverticulitis between January 2010 and June 2015 was conducted. Patient demographics, clinical, and surgical outcome were recorded and analyzed. RESULTS: Eight patients were admitted for acute jejunal diverticulitis with a mean age of 72.1 (range 55-87) years. Clinical presentation included six patients (75%) with a sealed perforation and only one patient demonstrated distant pneumoperitoneum. All patients were treated initially without surgery and only one patient required surgery because of diverticular complications. Recurrent episodes occurred in two patients (25%). Colonoscopy was performed in all patients after hospitalization that revealed large bowel diverticulosis in all patients (100%). Median follow-up was 8.2 months (3-15 months). CONCLUSION: Jejunal diverticulitis can be initially treated conservatively but complicated disease should be considered for surgical management. Further study is required on the relationship between small and large bowel diverticulosis.

Prediction of patency capsule retention in known Crohn's disease patients by using magnetic resonance imaging.

BACKGROUND AND AIMS: Evaluation of small-bowel patency is recommended before swallowing video capsule endoscopy to prevent capsule retention. This study aimed to evaluate the ability of magnetic resonance enterography (MRE) to predict patency capsule (PC) retention in patients with Crohn's disease and to identify the most predictive imaging features for retention. METHODS: Fifty-seven patients prospectively underwent MRE and PC. Two radiologists predicted PC retention. Interrater reliability was determined by using Cohen's κ coefficient. The sensitivity, specificity, and positive and negative predictive values were calculated for the predictions. Evaluation of the imaging features was done using the t test and receiver-operating characteristics; t-tests were also performed on the clinical parameters. RESULTS: The κ value for interrater reliability was 0.58. The sensitivity, specificity, PPV, and NPV for the predictions by the 2 radiologists were 92.3%, 59%, 40%, 96.3%, and 100%, 52.3%, 38.2%, 100%, respectively. The maximal stricture length (9.7 ± 3.66 cm vs 7.0 ± 3.08 cm, P = .04) and the number of prestenotic dilations (1.9 ± 1.07 vs 1.0 ± 1.38, P = .03) were associated with PC retention. The area under the receiver-operating characteristic curves was 0.69 for the maximal stricture length and 0.751 for the number of prestenotic dilations. The phenotype of the disease was the only clinical parameter significantly correlated with PC retention. CONCLUSIONS: MRE has a high NPV and sensitivity for PC retention. When capsule retention is suggested by MRE, PC should be performed before the video capsule endoscopy examination. The maximal stricture length and the number of prestenotic dilations were found to be the most predictive imaging features for PC retention.

Automated method for detection and segmentation of liver metastatic lesions in follow-up CT examinations.

This paper presents a fully automated method for detection and segmentation of liver metastases in serial computed tomography (CT) examinations. Our method uses a given two-dimensional baseline segmentation mask for identifying the lesion location in the follow-up CT and locating surrounding tissues, using nonrigid image registration and template matching, in order to reduce the search area for segmentation. Adaptive region growing and mean-shift clustering are used to obtain the lesion segmentation. Our database contains 127 cases from the CT abdomen unit at Sheba Medical Center. Development of the methodology was conducted using 22 of the cases, and testing was conducted on the remaining 105 cases. Results show that 94 of the 105 lesions were detected, for an overall matching rate of 90% making the correct RECIST 1.1 assessment in 88% of the cases. The average Dice index was [Formula: see text], the average sensitivity was [Formula: see text], and the positive predictive value was [Formula: see text]. In 92% of the rated cases, the results were classified by the radiologists as acceptable or better. The segmentation performance, matching rate, and RECIST assessment results hence appear promising.

[Clinical pathological conference: abdominal masses and purulent ascites].

A 91 year old patient presented with constipation, abdominal distension, weakness and anorexia lasting for two days. Computed tomography revealed multiple peritoneal masses with significant growth within days and local invasiveness without regard to anatomical boundaries. No lymphadenopathy or hepatosplenomegaly were found. Abdominal paracentesis showed 60,000 cells/mm3 presumed to be neutrophils. During follow-up, there were no clinical or radiographic signs of peritonitis. Trans-abdominal true-cut biopsy from the peritoneal masses was consistent with diffuse large B cell lymphoma germinal center B cell type, clinically presenting as peritoneal lymphomatosis. FISH cytogenetic study identified single BLC-6 gene in the tumor infiltrating lymphocytes. We speculated that this aberration in the patient's immune system cells contributed to this rare, unusual and aggressive lymphoma presentation in an otherwise non-immune compromised patient.