Real-time, computer-aided, detection-assisted colonoscopy eliminates differences in adenoma detection rate between trainee and experienced endoscopists

Background and study aims  Adenoma detection rate (ADR) is a well-accepted quality indicator of screening colonoscopy. In recent years, the added value of artificial intelligence (AI) has been demonstrated in terms of ADR and adenoma miss rate (AMR). To date, there are no studies evaluating the impact of AI on the performance of trainee endoscopists (TEs). This study aimed to assess whether AI might eliminate any difference in ADR or AMR between TEs and experienced endoscopists (EEs). Patients and methods  We performed a prospective observational study in 45 subjects referred for screening colonoscopy. A same-day tandem examination was carried out for each patient by a TE with the AI assistance and subsequently by an EE unaware of the lesions detected by the TE. Besides ADR and AMR, we also calculated for each subgroup of endoscopists the adenoma per colonoscopy (APC), polyp detection rate (PDR), polyp per colonoscopy (PPC) and polyp miss rate (PMR). Subgroup analyses according to size, morphology, and site were also performed. Results  ADR, APC, PDR, and PPC of AI-supported TEs were 38 %, 0.93, 62 %, 1.93, respectively. The corresponding parameters for EEs were 40 %, 1.07, 58 %, 2.22. No significant difference was found for each analysis between the two groups ( P  > 0.05). AMR and PMR for AI-assisted TEs were 12.5 % and 13 %, respectively. Sub-analyses did not show any significant difference ( P  > 0.05) between the two categories of operators. Conclusions  In this single-center prospective study, the possible impact of AI on endoscopist quality training was demonstrated. In the future, this could result in better efficacy of screening colonoscopy by reducing the incidence of interval or missed cancers.

Accuracy and inter-observer agreement of the nice and kudo classifications of superficial colonic lesions: a comparative study

PURPOSE

For superficial colonic lesions, the NICE and Kudo classifications are used in the in vivo prediction of histology and as guide to therapy. The NICE system derives information from unmagnified NBI endoscopic images. The Kudo one necessitates a magnification, but, as this tool is not commonly available, it is applied also to characterize unmagnified pictures to compare their diagnostic performances.

METHODS

We conducted a prospective comparison of the NICE versus the Kudo classification for the differential diagnosis of colonic polyps taking histology as the gold standard. The inter-observer agreement for both classifications among 11 colonoscopists was also evaluated. Short unmagnified NBI videoclips of 64 colonic polyps were sent twice to the participants. In the first round, they classified the lesions according to the NICE classification; 4 months later, the same videos were assessed with the Kudo system. The diagnosis provided by the participants was grouped in non-neoplastic, non-invasive neoplasia, invasive neoplasia.

RESULTS

Overall, the diagnostic accuracy was 82% (95%CI: 79-85) with the NICE system and 81% (95%CI: 78-84) with the Kudo one (ρ = 0.78). The accuracy of the NICE classification for non-neoplastic lesions was greater compared with the Kudo's (ρ = 0.03). Sensitivity sub-analyses revealed a higher ability of the NICE in distinguishing between neoplastic vs. non-neoplastic lesions (ρ = 0.01). The overall inter-rater agreement did not differ when the classifications were compared.

CONCLUSION

The NICE and the Kudo classifications might be considered comparable. Our data could allow the use of the NBI Kudo classification even in those centers where magnification is not available.

Interobserver agreement of the Paris and simplified classifications of superficial colonic lesions: a Western study

Background and study aims  The Paris classification of superficial colonic lesions has been widely adopted, but a simplified description that subgroups the shape into pedunculated, sessile/flat and depressed lesions has been proposed recently. The aim of this study was to evaluate the accuracy and inter-rater agreement among 13 Western endoscopists for the two classification systems. Methods  Seventy video clips of superficial colonic lesions were classified according to the two classifications, and their size estimated. The interobserver agreement for each classification was assessed using both Cohen k and AC1 statistics. Accuracy was taken as the concordance between the standard morphology definition and that made by participants. Sensitivity analyses investigated agreement between trainees (T) and staff members (SM), simple or mixed lesions, distinct lesion phenotypes, and for laterally spreading tumors (LSTs). Results  Overall, the interobserver agreement for the Paris classification was substantial (κ = 0.61; AC1 = 0.66), with 79.3 % accuracy. Between SM and T, the values were superimposable. For size estimation, the agreement was 0.48 by the κ-value, and 0.50 by AC1. For single or mixed lesions, κ-values were 0.60 and 0.43, respectively; corresponding AC1 values were 0.68 and 0.57. Evaluating the several different polyp subtypes separately, agreement differed significantly when analyzed by the k-statistics (0.08-0.12) or the AC1 statistics (0.59-0.71). Analyses of LSTs provided a κ-value of 0.50 and an AC1 score of 0.62, with 77.6 % accuracy. The simplified classification outperformed the Paris classification: κ = 0.68, AC1 = 0.82, accuracy = 91.6 %. Conclusions  Agreement is often measured with Cohen's κ, but we documented higher levels of agreement when analyzed with the AC1 statistic. The level of agreement was substantial for the Paris classification, and almost perfect for the simplified system.

Helicobacter pylori Primary and Secondary Genotypic Resistance to Clarithromycin and Levofloxacin Detection in Stools: A 4-Year Scenario in Southern Italy

Antibiotic resistance has become an emerging problem for treating Helicobacter pylori (H. pylori) infection. Clarithromycin and levofloxacin are two key antibiotics used for its eradication. Therefore, we reviewed our experience with genotypic resistance analysis in stools to both clarithromycin and levofloxacin in the last four years to evaluate time trends, both in naive and failure patients. Patients collected a fecal sample using the THD fecal test device. Real-time polymerase chain reaction was performed to detect point mutations conferring resistance to clarithromycin (A2142C, A2142G, and A2143G in 23S rRNA) and levofloxacin (substitutions at amino acid position 87 and 91 of gyrA). One hundred and thirty-five naive patients were recruited between 2017-2020. Clarithromycin resistance was detected in 37 (27.4%). The time trend did not show any significant variation from 2017 to 2020 (p = 0.33). Primary levofloxacin resistance was found in 26 subjects (19.2%), and we observed a dramatic increase in rates from 2017 (10%) to 2018 (3.3%), 2019 (20%), and 2020 (37.8%). Ninety-one patients with at least one eradication failure were recruited. Secondary resistance to clarithromycin and levofloxacin was found in 59 (64.8%) and 45 patients (59.3%), respectively. In conclusion, our geographic area has a high risk of resistance to clarithromycin. There is also a progressive spreading of levofloxacin-resistant strains.

Subcellular localization of high- and low-molecular weight acid phosphatases from chicken liver

The subcellular localization of high and low molecular weight acid phosphatases in chicken liver was studied. The high molecular weight acid phosphatase is mainly associated with the particulate fraction, particularly with the mitochondrial-lysosomal fraction, whereas the low molecular weight form seems to be a soluble cytoplasmic enzyme. Biochemical properties including optimal pH, molecular weight determination and the effect of some modifier substances indicate that mitochondria-lysosomes and microsomes contain the same high molecular weight acid phosphatase form.