Comparison of virtual computed tomography enteroscopy using carbon dioxide with small-bowel enteroclysis and capsule endoscopy in patients with small-bowel tuberculosis

Cascade-E-Yolov5s network for recognizing the ulcerative lesion subtypes in small intestinal

In endoscopy, accurately diagnosing small intestinal ulcers presents significant challenges due to the complex morphology, varying number, and extensive distribution of the lesions, which contribute to a reduced accuracy in immediate diagnosis. The definitive diagnosis typically relies on pathological analysis, laboratory investigations, and prolonged follow-up, often leading to diagnostic delays. This study introduces the Cascade-E-Yolov5s network, designed to improve the efficiency and accuracy of immediate ulcer diagnosis by intelligently identifying ulcer subtypes. The Cascade-E-Yolov5s network integrates EfficientNet for the classification of ulcer lesion images and SimAM-Yolov5s for detecting lesions on these classified images. In the SimAM-Yolov5s component, EfficientNet replaces the traditional backbone structure of Yolov5s, and enhancements such as the SIoU loss function and a simple, parameter-free attention module are incorporated to optimize model performance. The study utilized a dataset comprising 4909 ulcer images from 684 patients at Shanghai Changhai Hospital, encompassing four ulcer types: cryptogenic multifocal ulcerous stenosing enteritis, non-specific ulcer, small intestinal tuberculosis, and Crohn's disease. The experimental findings indicate that Cascade-E-Yolov5s surpasses conventional detection networks, achieving an average detection precision of 86.46% and a mean average precision at the IoU of 0.5 (mAP@0.5) of 82.20%. This model notably enhances the detection efficiency of small intestinal ulcer subtypes, thereby assisting clinicians in making more precise immediate diagnoses.

Oral CT Contrast Agents: What's New and Why, From the AJR Special Series on Contrast Media

Current CT oral contrast agents improve the conspicuity of and confidence in bowel and peritoneal findings in many clinical scenarios, particularly for outpatient and oncologic abdominopelvic imaging. Yet, existing positive and neutral oral contrast agents may diminish the detectability of certain radiologic findings, frequently in the same scans in which the oral contrast agent improves the detectability of other findings. With ongoing improvements in CT technology, particularly multienergy CT, opportunities are opening for new types of oral contrast agents to further improve anatomic delineation and disease detection using CT. The CT signal of new dark oral contrast agents and of new high-Z oral contrast agents promises to combine the strengths of both positive and neutral oral CT contrast agents by providing distinct CT appearances in comparison with bodily tissues, iodinated IV contrast agents, and other classes of new CT contrast agents. High-Z oral contrast agents will unlock previously inaccessible capabilities of multienergy CT, particularly photon-counting detector CT, for differentiating simultaneously administered IV and oral contrast agents; this technique will allow generation of rich 3D, intuitive, perfectly coregistered, high-resolution image sets with individual contrast agent "colors" that provide compelling clarity for intertwined intraabdominal anatomy and disease processes.

Differentiation of Crohn's disease, ulcerative colitis, and intestinal tuberculosis by dual-layer spectral detector CT enterography

AIM

To investigate the value of radiological features and energy spectrum quantitative parameters in the differential diagnosis of Crohn's disease (CD), ulcerative colitis (UC), and intestinal tuberculosis (ITB) by dual-layer spectral detector computed tomography (CT) enterography (CTE).

MATERIALS AND METHODS

Clinical and CTE data were collected from 182 patients with CD, 29 with UC, and 51 with ITB. CT images were obtained at the enteric phases and portal phases. The quantitative energy spectrum parameters were iodine density (ID), normalised ID (NID), virtual non-contrast (VNC) value, and effective atomic number (Z-eff). The area under curve (AUC) of the receiver operating characteristic curve (ROC) was calculated.

RESULTS

The vascular comb sign (p=0.009) and enlarged lymph nodes (p=0.001) were more common in patients with CD than UC or ITB. In the differentiation of moderate-severe active CD from UC, enteric phase NID (AUC, 0.938; p<0.001) and portal phase Z-eff (AUC, 0.925; p<0.001) had the highest accuracy, which were compared separately. In the differentiation of moderate-severe active CD from ITB, enteric phase NID (AUC, 0.906; p<0.001) and portal phase Z-eff (AUC, 0.947; p<0.001) had the highest accuracy; however, the AUC value was highest when the four parameters are combined (AUC, 0.989; p<0.001; AUC, 0.986; p<0.001; AUC, 0.936; p<0.001; and AUC, 0.986; p<0.001).

CONCLUSION

The present study shows that the combined strategies of four parameters have higher sensitivity and specificity in differentiating CD, UC, and ITB, and may play a key role in guiding treatment.

Imaging of infra-thoracic tuberculosis

Tuberculosis (TB) is a potentially curable disease that is a leading cause of death globally. While it typically affects the lungs, this disease may involve many extra-pulmonary sites, particularly in patients with risk factors. Extra-pulmonary TB often mimics a variety of different diseases, posing a diagnostic dilemma. Imaging aids in early diagnosis of TB, especially in patients with non-specific or atypical symptoms found at extra-pulmonary infra-thoracic locations. Imaging also helps guide appropriate laboratory investigation, monitor disease progress, and response to treatment. This review aims to highlight the imaging spectrum of TB affecting the infra-thoracic region, that is, gastrointestinal tract, abdominal lymph nodes, peritoneal cavity, intra-abdominal solid organs, and urogenital system.

Automated classification of ulcerative lesions in small intestine using densenet with channel attention and residual dilated blocks

Objective. Ulceration of the small intestine, which has a high incidence, includes Crohn's disease (CD), intestinal tuberculosis (ITB), primary small intestinal lymphoma (PSIL), cryptogenic multifocal ulcerous stenosing enteritis (CMUSE), and non-specific ulcer (NSU). However, the ulceration morphology can easily be misdiagnosed through enteroscopy.Approach. In this study, DRCA-DenseNet169, which is based on DenseNet169, with residual dilated blocks and a channel attention block, is proposed to identify CD, ITB, PSIL, CMUSE, and NSU intelligently. In addition, a novel loss function that incorporates dynamic weights is designed to enhance the precision of imbalanced datasets with limited samples. DRCA-Densenet169 was evaluated using 10883 enteroscopy images, including 5375 ulcer images and 5508 normal images, which were obtained from the Shanghai Changhai Hospital.Main results. DRCA-Densenet169 achieved an overall accuracy of 85.27% ± 0.32%, a weighted-precision of 83.99% ± 2.47%, a weighted-recall of 84.36% ± 0.88% and a weighted-F1-score of 84.07% ± 2.14%.Significance. The results demonstrate that DRCA-Densenet169 has high recognition accuracy and strong robustness in identifying different types of ulcers when obtaining immediate and preliminary diagnoses.

Perfusion Computed Tomography May Help in Discriminating Gastrointestinal Tuberculosis and Crohn's Disease

Gastrointestinal tuberculosis (GITB) and Crohn's disease (CD) are close mimics. This prospective study aimed to evaluate the diagnostic performance of perfusion computed tomography (CT) in differentiating GITB from CD. Consecutive patients with ileocaecal thickening underwent perfusion CT of the ileocaecal region between January 2019 and July 2020. Two radiologists (blinded to the final diagnosis) independently assessed blood flow (BF), blood volume (BV), mean transit time (MTT), and permeability at perfusion CT. These parameters were compared among the patients with GITB as well as active and inactive CD. Receiver operating characteristic curves were utilized for determining the diagnostic performance of perfusion CT. Interclass correlation coefficient and Bland-Altman analysis were performed to compare the observations of the two radiologists. During the study period, 34 patients underwent perfusion CT. Eight patients had diagnoses other than intestinal tuberculosis or CD. Thus, 26 patients (mean age 36 ± 14 years, 18 males) with GITB (n = 11), active CD (n = 6), and inactive CD (n = 9) were evaluated. BF, MTT, and permeability showed significant differences among the groups, while BV did not differ significantly among the groups. BF and permeability had 100% sensitivity and 100% specificity, while MTT had 61.5-100% sensitivity and 70-100% specificity for differentiating GITB from active CD and active from inactive CD. The interclass correlation coefficient for perfusion CT parameters was 0.88-1. Perfusion CT is a novel imaging technique that can improve the diagnostic performance of differentiating tuberculosis from CD.