ACR Appropriateness Criteria® Suspected Small-Bowel Obstruction

Imaging, Expert Panel on Gastrointestinal; Chang, Kevin J.; Marin, Daniele; Kim, David H.; Fowler, Kathryn J.; Camacho, Marc A.; Cash, Brooks D.; García, Encarnación Martínez; Hatten, Benjamin W.; Kambadakone, Avinash; Levy, Angela D.; Liu, Peter S.; Moreno, Courtney A.; Peterson, Christine; Pietryga, Jason A.; Siegel, Alan; Weinstein, Stefanie; Carucci, Laura R.

doi:10.1016/j.jacr.2020.01.025

Cited by 25 publications

(13 citation statements)

References 84 publications

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“…Several factors may explain why only two earlier studies have evaluated an artificial-intelligence approach to SBO diagnosis, despite the high frequency of mechanical SBO among nontraumatic surgical emergencies [ 9 , 10 ]. It should be noted that these studies focused on standard radiographs, which are no longer recommended for diagnosing SBO [ 4 ]. First, developing an artificial-intelligence model for TZ detection requires the establishment of a large database by highly experienced radiologists.…”

Section: Discussionmentioning

confidence: 99%

“…All guidelines recommend computed tomography (CT) as the first-line imaging study for patients with suspected mechanical SBO [ 3 , 4 ]. The goal is four-fold: (i) to confirm or refute the diagnosis of SBO and, when SBO is present, (ii) to locate the site of the obstruction, that is, the transition zone (TZ) (iii) to identify the cause, and (iv) to look for complications such as strangulation or perforation.…”

Section: Introductionmentioning

confidence: 99%

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Adhesion-related small bowel obstruction: deep learning for automatic transition-zone detection by CT

et al. 2022

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Background To train a machine-learning model to locate the transition zone (TZ) of adhesion-related small bowel obstruction (SBO) on CT scans. Materials and methods We used 562 CTs performed in 2005–2018 in 404 patients with adhesion-related SBO. Annotation of the TZs was performed by experienced radiologists and trained residents using bounding boxes. Preprocessing involved using a pretrained model to extract the abdominopelvic region. We modeled TZ localization as a binary classification problem by splitting the abdominopelvic region into 125 patches. We then trained a neural network model to classify each patch as containing or not containing a TZ. We coupled this with a trained probabilistic estimation of presence of a TZ in each patch. The models were first evaluated by computing the area under the receiver operating characteristics curve (AUROC). Then, to assess the clinical benefit, we measured the proportion of total abdominopelvic volume classified as containing a TZ for several different false-negative rates. Results The probability of containing a TZ was highest for the hypogastric region (56.9%). The coupled classification network and probability mapping produced an AUROC of 0.93. For a 15% proportion of volume classified as containing TZs, the probability of highlighted patches containing a TZ was 92%. Conclusion Modeling TZ localization by coupling convolutional neural network classification and probabilistic localization estimation shows the way to a possible automatic TZ detection, a complex radiological task with a major clinical impact.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adhesion-related small bowel obstruction: deep learning for automatic transition-zone detection by CT

et al. 2022

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“…In contrast, abdominal CT scan with oral and intravenous contrast, the standard imaging modality in diagnosis of SBO, 4 involves much more delay in care. Even the preferred imaging modality by the American College of Radiology Appropriateness Criteria of CT with intravenous contrast and no oral contrast is time-consuming when compared to ultrasound.…”

Section: Discussionmentioning

confidence: 99%

Point of Care Ultrasound as a Diagnostic Tool to Detect Small Bowel Obstruction in the Emergency Department: A Case Report

Nadelman¹,

Aurup²

2021

Journal of Education and Teaching in Emergency Medicine

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“…MBO is a clinical diagnosis that is confirmed with radiological imaging. Historically, abdominal x-rays were recommended to be the initial imaging modality, but their sensitivity to detect MBO is moderate and poses challenges in detecting the exact site, cause, or complications derived from MBO [9]. Contrast computed tomography (CT) is more valuable as it provides diagnostic precision [4].…”

Section: Diagnosismentioning

confidence: 99%

“…Contrast computed tomography (CT) is more valuable as it provides diagnostic precision [4]. The American College of Radiology recommends the use of CT of the abdomen and pelvis with intravenous (IV) contrast for patients with suspected acute small BO and either a CT abdomen and pelvis with IV contrast or a CT enterography for patients suspected to have intermittent or low-grade small BO [9].…”

Section: Diagnosismentioning

confidence: 99%

MASCC multidisciplinary evidence-based recommendations for the management of malignant bowel obstruction in advanced cancer

Madariaga

Lau²,

Ghoshal³

et al. 2022

Support Care Cancer

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Purpose To provide evidence-based recommendations on the management of malignant bowel obstruction (MBO) for patients with advanced cancer. Methods The Multinational Association for Supportive Care in Cancer (MASCC) MBO study group conducted a systematic review of databases (inception to March 2021) to identify studies about patients with advanced cancer and MBO that reported on the following outcomes: symptom management, bowel obstruction resolution, prognosis, overall survival, and quality of life. The review was restricted to studies published in English, but no restrictions were placed on publication year, country, and study type. As per the MASCC Guidelines Policy, the findings were synthesized to determine the levels of evidence to support each MBO intervention and, ultimately, the graded recommendations and suggestions. Results The systematic review identified 17,656 published studies and 397 selected for the guidelines. The MASCC study group developed a total of 25 evidence-based suggestions and recommendations about the management of MBO-related nausea and vomiting, bowel movements, pain, inflammation, bowel decompression, and nutrition. Expert consensus-based guidance about advanced care planning and psychosocial support is also provided. Conclusion This MASCC Guideline provides comprehensive, evidence-based recommendations about MBO management for patients with advanced cancer.

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ACR Appropriateness Criteria® Suspected Small-Bowel Obstruction

Cited by 25 publications

References 84 publications

Adhesion-related small bowel obstruction: deep learning for automatic transition-zone detection by CT

Adhesion-related small bowel obstruction: deep learning for automatic transition-zone detection by CT

Point of Care Ultrasound as a Diagnostic Tool to Detect Small Bowel Obstruction in the Emergency Department: A Case Report

MASCC multidisciplinary evidence-based recommendations for the management of malignant bowel obstruction in advanced cancer

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