Acute colonic flexures: the basis for developing an artificial intelligence-based tool for predicting the course of colonoscopy

Wozniak S, Pawlus A, Grzelak J, Chobotow S, Paulsen F, Olchowy C, Zaleska-Dorobisz U (2022)

Publication Type: Journal article

Publication year: 2022

Journal

Anatomical Science International Wiley-Blackwell: No OnlineOpen / Springer Verlag (Germany)

DOI: 10.1007/s12565-022-00681-8

Abstract

Tortuosity of the colon is an important parameter for predicting the course of colonoscopy. Computed tomography scans of the abdominal cavity were performed in 224 (94 female, 130 male) adult subjects. The number of acute (angle not exceeding 90°) bends between adjacent colonic segments was noted and analyzed. Data were analyzed for correlation with gender, age, height and weight. An artificial intelligence algorithm was proposed to predict the course of colonoscopy. We determined the number of acute flexions in females to be 9.74 ± 2.5 (min–max: 4–15) and in males to be 8.7 ± 2.75 (min–max: 4–20). In addition, more acute flexions were found in women than in men and in older women (after 60 years) and men (after 80 years) than in younger ones. We found the greatest variability in the number of acute flexures in the sigmoid colon (0–9), but no correlation was found between the number of acute flexures and age, gender, height or BMI. In the transverse colon, older and female subjects had more flexures than younger and male subjects, respectively. Older subjects had more acute flexures in the descending colon than younger subjects. There are opportunities to use the number of acute flexures (4–7, 8–12, more than 12 flexures) to classify patients into appropriate risk categories for future incomplete colonoscopy. On this basis, we predicted troublesome colonoscopies in 14.9% female and in 6.1% male subjects.

Authors with CRIS profile

Friedrich Paulsen Lehrstuhl für Funktionelle und Klinische Anatomie

Involved external institutions

Wrocław Medical University / Uniwersytet Medyczny we Wrocławiu PL Poland (PL) Provincial Specialist Hospital Legnica / Wojewódzki Szpital Specjalistyczny w Legnicy PL Poland (PL)

How to cite

APA:

Wozniak, S., Pawlus, A., Grzelak, J., Chobotow, S., Paulsen, F., Olchowy, C., & Zaleska-Dorobisz, U. (2022). Acute colonic flexures: the basis for developing an artificial intelligence-based tool for predicting the course of colonoscopy. Anatomical Science International. https://doi.org/10.1007/s12565-022-00681-8

MLA:

Wozniak, Slawomir, et al. "Acute colonic flexures: the basis for developing an artificial intelligence-based tool for predicting the course of colonoscopy." Anatomical Science International (2022).

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