BACKGROUND: We developed a deep learning algorithm to evaluate defecatory patterns to identify dyssynergic defecation using 3-dimensional high definition anal manometry (3D-HDAM). AIMS: We developed a 3D-HDAM deep learning algorithm to evaluate for dyssynergia. METHODS: Spatial-temporal data were extracted from consecutive 3D-HDAM studies performed between 2018 and 2020 at Dartmouth-Hitchcock Health. The technical procedure and gold standard definition of dyssynergia were based on the London consensus, adapted to the needs of 3D-HDAM technology. Three machine learning models were generated: (1) traditional machine learning informed by conventional anorectal function metrics, (2) deep learning, and (3) a hybrid approach. Diagnostic accuracy was evaluated using bootstrap sampling to calculate area-under-the-curve (AUC). To evaluate overfitting, models were validated by adding 502 simulated defecation maneuvers with diagnostic ambiguity. RESULTS: 302 3D-HDAM studies representing 1208 simulated defecation maneuvers were included (average age 55.2 years; 80.5% women). The deep learning model had comparable diagnostic accuracy [AUC 0.91 (95% confidence interval 0.89-0.93)] to traditional [AUC 0.93(0.92-0.95)] and hybrid [AUC 0.96(0.94-0.97)] predictive models in training cohorts. However, the deep learning model handled ambiguous tests more cautiously than other models; the deep learning model was more likely to designate an ambiguous test as inconclusive [odds ratio 4.21(2.78-6.38)] versus traditional/hybrid approaches. CONCLUSIONS: Deep learning is capable of considering complex spatial-temporal information on 3D-HDAM technology. Future studies are needed to evaluate the clinical context of these preliminary findings.
Deep Learning , Defecation , Humans , Female , Middle Aged , Male , Manometry/methods , Anal Canal , Ataxia , Constipation/diagnosis
Acrodermatitis/diagnosis , Hand Dermatoses/diagnosis , Nails, Malformed/diagnosis , Acrodermatitis/drug therapy , Acrodermatitis/pathology , Administration, Cutaneous , Aged , Anti-Inflammatory Agents/administration & dosage , Calcitriol/administration & dosage , Calcitriol/analogs & derivatives , Clobetasol/administration & dosage , Diagnosis, Differential , Fingers , Hand Dermatoses/drug therapy , Hand Dermatoses/pathology , Humans , Male , Nails, Malformed/drug therapy , Nails, Malformed/pathology