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Short bowel syndrome is the most common cause of intestinal failure, with morbidity and mortality linked to remanent small intestine length. There is no current standard for noninvasive bowel length measurement. The literature was systematically searched for articles describing measurements of small intestine length from radiographic studies. Inclusion required reporting intestinal length as an outcome and use of diagnostic imaging for length assessment compared to a ground truth. Two reviewers independently screened studies for inclusion, extracted data, and assessed study quality. Eleven studies met the inclusion criteria and reported small intestinal length measurement using four imaging modalities: barium follow-through, ultrasound, computed tomography, and magnetic resonance. Five barium follow-through studies reported variable correlations with intraoperative measurements (r = 0.43-0.93); most (3/5) reported underestimation of length. US studies (n = 2) did not correlate with ground truths. Two computed tomography studies reported moderate-to-strong correlations with pathologic (r = 0.76) and intraoperative measurements (r = 0.99). Five studies of magnetic resonance showed moderate-to-strong correlations with intraoperative or postmortem measurements (r = 0.70-0.90). Vascular imaging software was used in two studies, and a segmentation algorithm was used for measurements in one. Noninvasive measurement of small intestine length is challenging. Three-dimensional imaging modalities reduce the risk of length underestimation, which is common with two-dimensional techniques. However, they also require longer times to perform length measurements. Automated segmentation has been trialed for magnetic resonance enterography, but this method does not translate directly to standard diagnostic imaging. While three-dimensional images are most accurate for length measurement, they are limited in their ability to measure intestinal dysmotility, which is an important functional measure in patients with intestinal failure. Future work should validate automated segmentation and measurement software using standard diagnostic imaging protocols. [ABSTRACT FROM AUTHOR]