Software for automated classification of probe-based confocal laser endomicroscopy videos of colorectal polyps

Table 1 Study population characteristics

Study population	Summary (n = 71)
Age (yr), median (min, 25th, 75th, max)	75 (46, 68, 79, 93)
Gender, %
Male	49
Female	51
History of colon cancer, %	9
Family history of colon cancer, %	10

Table 2 Colorectal lesion characteristics

Colorectal lesions	Summary (n = 135)
Polyp size (mm), median (min, 25th, 75th, max)	8 (1, 5, 20, 60)
Polyp location, %
Cecum	24
Rectum	20
Ascending	18
Sigmoid	14.5
Transverse	15
Descending	5.5
Splenic flex	3
Histopathology diagnosis, %
Hyperplastic	31
Tubular adenoma	52
Tubulovillous adenoma	11.5
Hyperplastic and adenomatous features	2.5
Adenocarcinoma	3
Neoplastic lesion, simplified histopathology, %	69
Paris classification, %
1p	1
1s	57
2a	32
2b	5
2c	1
2a/c	4

Table 3 Performance comparison between automated probe-based confocal laser endomicroscopy classification and off-line expert diagnosis of probe-based confocal laser endomicroscopy, for the differentiation between neoplastic and non-neoplastic colonic polyps

	Automated pCLE classification	Off-line expert diagnosis of pCLE
Accuracy
%	89.6	89.6
Fraction	121/135	121/135
Sensitivity
%	92.5	91.4
Fraction	86/93	85/93
Specificity
%	83.3	85.7
Fraction	35/42	36/42
Statistical significance between (1) and (2)
McNemar’s test, alpha = 0.05
Accuracy: (P, power)	(Not significant, 2.5%)
Sensitivity: (P, power)	(Not significant, 6.5%)
Specificity: (P, power)	(Not significant, 5.2%)
Statistical equivalence between (1) and (2)
Two-sided Z test
95% CI for accuracy	-0.073-0.073
95% CI for sensitivity	-0.068-0.089
95% CI for specificity	-0.18-0.13

pCLE: Probe-based confocal laser endomicroscopy.