Background and Study Aims: Small polyps are occasionally missed during colonoscopy. This study was conducted to validate the diagnostic performance of a polyp-detection algorithm to alert endoscopists to unrecognized lesions. Methods: A computer-aided detection (CADe) algorithm was developed based on convolutional neural networks using training data from 1991 still colonoscopy images from 283 subjects with adenomatous polyps. The CADe algorithm was evaluated on a validation dataset including 50 short videos with 1-2 polyps (3.5 AE 1.5 mm, range 2-8 mm) and 50 videos without polyps. Two expert colonoscopists and two physicians in training separately read the same videos, blinded to the presence of polyps. The CADe algorithm was also evaluated using eight full videos with polyps and seven full videos without a polyp. Results: The per-video sensitivity of CADe for polyp detection was 88% and the per-frame false-positive rate was 2.8%, with a confidence level of ≥30%. The per-video sensitivity of both experts was 88%, and the sensitivities of the two physicians in training were 84% and 76%. For each reader, the frames with missed polyps appearing on short videos were significantly less than the frames with detected polyps, but no trends were observed regarding polyp size, morphology or color. For full video readings, per-polyp sensitivity was 100% with a per-frame false-positive rate of 1.7%, and per-frame specificity of 98.3%. Conclusions: The sensitivity of CADe to detect small polyps was almost equivalent to experts and superior to physicians in training. A clinical trial using CADe is warranted.

In the heart, TRPM4 is most abundantly distributed in the conduction system. Previously, a single mutation, ‘E7K’, was identified in its distal N-terminus to cause conduction disorder because of enhanced cell-surface expression. It remains, however, unclear how this expression increase leads to conduction failure rather than abnormally enhanced cardiac excitability. To address this issue theoretically, we mathematically formulated the gating kinetics of the E7K-mutant TRPM4 channel by a combined use of voltage jump analysis and ionomycin-perforated cell-attached recording technique and incorporated the resultant rate constants of opening and closing into a human Purkinje fiber single-cell action potential (AP) model (Trovato model) to perform 1D-cable simulations. The results from TRPM4 expressing HEK293 cells showed that as compared with the wild-type, the open state is much preferred in the E7K mutant with increased voltage-and Ca2+-sensitivities. These theoretical predictions were confirmed by power spectrum and single channel analyses of expressed wild-type and E7K-mutant TRPM4 channels. In our modified Trovato model, the facilitated opening of the E7K mutant channel markedly prolonged AP duration with concomitant depolarizing shifts of the resting membrane potential in a manner dependent on the channel density (or maximal activity). This was, however, little evident in the wild-type TRPM4 channel. Moreover, 1D-cable simulations with the modified Trovato model revealed that increasing the density of E7K (but not of wild-type) TRPM4 channels progressively reduced AP conduction velocity eventually culminating in complete conduction block. These results clearly suggest the brady-arrhythmogenicity of the E7K mutant channel which likely results from its pathologically enhanced activity.