Artificial intelligence for detecting and delineating the extent of superficial esophageal squamous cell carcinoma and precancerous lesions under narrow-band imaging (with video).

BACKGROUND AND AIMS: Although narrow-band imaging (NBI) is a useful modality for detecting and delineating esophageal squamous cell carcinoma (ESCC), there is a risk of incorrectly determining the margins of some lesions even with NBI. This study aimed to develop an artificial intelligence (AI) system for detecting superficial ESCC and precancerous lesions and delineating the extent of lesions under NBI. METHODS: Nonmagnified NBI images from 4 hospitals were collected and annotated. Internal and external image test datasets were used to evaluate the detection and delineation performance of the system. The delineation performance of the system was compared with that of endoscopists. Furthermore, the system was directly integrated into the endoscopy equipment, and its real-time diagnostic capability was prospectively estimated. RESULTS: The system was trained and tested using 10,047 still images and 140 videos from 1112 patients and 1183 lesions. In the image testing, the accuracy of the system in detecting lesions in internal and external tests was 92.4% and 89.9%, respectively. The accuracy of the system in delineating extents in internal and external tests was 88.9% and 87.0%, respectively. The delineation performance of the system was superior to that of junior endoscopists and similar to that of senior endoscopists. In the prospective clinical evaluation, the system exhibited satisfactory performance, with an accuracy of 91.4% in detecting lesions and an accuracy of 85.9% in delineating extents. CONCLUSIONS: The proposed AI system could accurately detect superficial ESCC and precancerous lesions and delineate the extent of lesions under NBI.

Artificial intelligence for diagnosing microvessels of precancerous lesions and superficial esophageal squamous cell carcinomas: a multicenter study.

BACKGROUND: Intrapapillary capillary loop (IPCL) is an important factor for predicting invasion depth of esophageal squamous cell carcinoma (ESCC). The invasion depth is closely related to the selection of treatment strategy. However, diagnosis of IPCLs is complicated and subject to interobserver variability. This study aimed to develop an artificial intelligence (AI) system to predict IPCLs subtypes of precancerous lesions and superficial ESCC. METHODS: Images of magnifying endoscopy with narrow band imaging from three hospitals were collected retrospectively. IPCLs subtypes were annotated on images by expert endoscopists according to Japanese Endoscopic Society classification. The performance of the AI system was evaluated using internal and external validation datasets (IVD and EVD) and compared with that of the 11 endoscopists. RESULTS: A total of 7094 images from 685 patients were used to train and validate the AI system. The combined accuracy of the AI system for diagnosing IPCLs subtypes in IVD and EVD was 91.3% and 89.8%, respectively. The AI system achieved better performance than endoscopists in predicting IPCLs subtypes and invasion depth. The ability of junior endoscopists to diagnose IPCLs subtypes (combined accuracy: 84.7% vs 78.2%, P < 0.0001) and invasion depth (combined accuracy: 74.4% vs 67.9%, P < 0.0001) were significantly improved with AI system assistance. Although there was no significant differences, the performance of senior endoscopists was slightly elevated. CONCLUSIONS: The proposed AI system could improve the diagnostic ability of endoscopists to predict IPCLs classification of precancerous lesions and superficial ESCC.

Effect of an artificial intelligence-assisted system on endoscopic diagnosis of superficial oesophageal squamous cell carcinoma and precancerous lesions: a multicentre, tandem, double-blind, randomised controlled trial.

BACKGROUND: Despite the usefulness of white light endoscopy (WLE) and non-magnified narrow-band imaging (NBI) for screening for superficial oesophageal squamous cell carcinoma and precancerous lesions, these lesions might be missed due to their subtle features and interpretation variations among endoscopists. Our team has developed an artificial intelligence (AI) system to detect superficial oesophageal squamous cell carcinoma and precancerous lesions using WLE and non-magnified NBI. We aimed to evaluate the auxiliary diagnostic performance of the AI system in a real clinical setting. METHODS: We did a multicentre, tandem, double-blind, randomised controlled trial at 12 hospitals in China. Eligible patients were aged 18 years or older and underwent sedated upper gastrointestinal endoscopy for screening, investigation of gastrointestinal symptoms, or surveillance. Patients were randomly assigned (1:1) to either the AI-first group or the routine-first group using a computerised random number generator. Patients, pathologists, and statistical analysts were masked to group assignment, whereas endoscopists and research assistants were not. The same endoscopist at each centre did tandem upper gastrointestinal endoscopy for each eligible patient on the same day. In the AI-first group, the endoscopist did the first examination with the assistance of the AI system and the second examination without it. In the routine-first group, the order of examinations was reversed. The primary outcome was the miss rate of superficial oesophageal squamous cell carcinoma and precancerous lesions, calculated on a per-lesion and per-patient basis. All analyses were done on a per-protocol basis. This trial is registered with the Chinese Clinical Trial Registry (ChiCTR2100052116) and is completed. FINDINGS: Between Oct 19, 2021, and June 8, 2022, 5934 patients were randomly assigned to the AI-first group and 5912 to the routine-first group, of whom 5865 and 5850 were eligible for analysis. Per-lesion miss rates were 1·7% (2/118; 95% CI 0·0-4·0) in the AI-first group versus 6·7% (6/90; 1·5-11·8) in the routine-first group (risk ratio 0·25, 95% CI 0·06-1·08; p=0·079). Per-patient miss rates were 1·9% (2/106; 0·0-4·5) in AI-first group versus 5·1% (4/79; 0·2-9·9) in the routine-first group (0·37, 0·08-1·71; p=0·40). Bleeding after biopsy of oesophageal lesions was observed in 13 (0·2%) patients in the AI-first group and 11 (0·2%) patients in the routine-first group. No serious adverse events were reported by patients in either group. INTERPRETATION: The observed effect of AI-assisted endoscopy on the per-lesion and per-patient miss rates of superficial oesophageal squamous cell carcinoma and precancerous lesions under WLE and non-magnified NBI was consistent with substantial benefit through to a neutral or small negative effect. The effectiveness and cost-benefit of this AI system in real-world clinical settings remain to be further assessed. FUNDING: National Natural Science Foundation of China, 1·3·5 project for disciplines of excellence, West China Hospital, Sichuan University, and Chengdu Science and Technology Project. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

[The effects of eucommia ulmoides oliv on catching action of diabetic rats and myelinated nerve fibers in penile tissues].

OBJECTIVE: To explore the pharmacodynamic and pathological mechanism of eucommia ulmoides oliv in improving erectile function. METHODS: Thirty male diabetic rats were randomly divided into three groups: group A (n = 10, escipient group), group B (n = 10, sildenafil group), group C (n = 10, eucommia ulmoides oliv group) and group D (n = 10, the normal control group). After gavage for four weeks, the catching behaviors of all rats were observed, and ultrastructure of myelinated nerve fibers in penile tissue was examined by transmission electron microscope. The expression of neuronal nitric oxide synthase (nNOS) in penile tissues was examined by two steps immunohistochemistry method. RESULTS: Compared with group A, catching frequency of the rats in group C was notably increased (P < 0.05) and the expression of nNOS in penile tissue was significantly (P < 0.001). The examination by transmission electron microscope showed that in the rats' penile tissue of group A, myelinated nerve fibers were irregularly arranged and partially degenerated, and myelin sheaths lamella were splited and exhibited vacuoles or network forms. In group C, there were regular arrangements of myelinated nerve fibers, in which the formation of lamella was clear. CONCLUSION: By remitting the impairement of myelinated nerve fibers and enhancing the expression of nNOS in penile tissue, eucommia ulmoides oliv can improve erectile function of diabetic rats.

[Effect of eucommia ulmoides oliv on SOD activity and alpha-actin expression in the penile tissues of diabetic rats].

OBJECTIVE: To study the effect of aqueous abstract from eucommia ulmoides oliv on the activity of superoxide dismutase (SOD) and alpha-actin expression in the penile tissues of rats with diabetes mellitus (DM) in vitro. METHODS: A diabetes model was established by administration of alloxun twice to Sprague Dawley (SD) rats. Ten diabetic and 10 normal rats were randomly selected and the penile strips of each rat were divided into four equal shares and cultured in two groups, a eucommia ulmoides oliv coculture group (Group A, further dicided into 1 microg/ml, 10 microg/ml and 100 microg/ml subgroups) and a control group (Group B). Seven days later, the activity of SOD in the culture medium was detected by spectrophotometry, and the levels of micro-actin expression in the penile tissues were examined with the immunohistochemical method. RESULTS: Compared with Group B, the activity of SOD in the culture medium in athe 10 and 100 microg/ml subgroups was notably elevated (P < 0.01), and the numbers of immunoreactive positive cells of alpha-actin in the penile tissues remarkably increased (P < 0.01). CONCLUSION: The activity of SOD and alpha-actin expression in the penile tissues of diabetic rats in vitro can be increased by eucommia ulmioides oliv.