A visual deep learning model to predict abnormal versus normal parathyroid glands using intraoperative autofluorescence signals.

BACKGROUND: Previous work demonstrated that abnormal versus normal parathyroid glands (PGs) exhibit different patterns of autofluorescence, with former appearing darker and more heterogenous. Our objective was to develop a visual artificial intelligence model using intraoperative autofluorescence signals to predict whether a PG is abnormal (hypersecreting and/or hypercellular) or normal before excision during surgical exploration for primary hyperparathyroidism. METHODS: A total of 906 intraoperative parathyroid autofluorescence images of 303 patients undergoing parathyroidectomy/thyroidectomy were used to develop model. Autofluorescence image of each PG was uploaded into the visual artificial intelligence platform as abnormal or normal. For deep learning, randomly chosen 80% of data was used for training, 10% for testing, 10% for validation. The area under the receiver operating characteristic (AUROC), area under the precision-recall curve (AUPRC), recall (sensitivity), and precision (positive predictive value) of the model were calculated. RESULTS: AUROC and AUPRC of the model to predict normal and abnormal PGs were 0.90 and 0.93, respectively. Recall and precision of the model were 89% each. CONCLUSION: Visual artificial intelligence platforms may be used to compare the autofluorescence signal of a given parathyroid gland against a large database. This may be a new adjunctive tool for intraoperative assessment of parathyroid glands during surgical exploration for primary hyperparathyroidism.

The efficacy of laparoscopic transversus abdominis plane block on reducing postoperative narcotic usage in patients undergoing minimally invasive adrenalectomy.

BACKGROUND: Post-operative pain relief after abdominal operations is critical for patient satisfaction and rapid recovery. Narcotics have been a traditional part of postoperative analgesia, with transversus abdominis plane (TAP) block introduced recently. The aim of this study is to assess the efficacy of laparoscopic TAP block on postoperative pain control in patients undergoing minimally invasive adrenalectomy. METHODS: This was an institutional review board-approved retrospective study. Parameters related to postoperative pain control were compared between patients who underwent robotic transabdominal lateral adrenalectomy with (after December 2018) or without laparoscopic TAP block (control group) (before December 2018) by one surgeon. Statistics were performed using Mann Whitney U and Chi-square tests. RESULTS: There were 86 patients in the TAP and 83 patients in the control group. Groups were similar regarding demographic and clinical parameters. Despite the availability of intravenous acetaminophen to a higher percentage of patients in the control (31.3%) versus the TAP group (8.1%), 0-24 h lowest postoperative pain scores were significantly lower in the TAP group (P < 0.0001). In TAP versus control group, percentage of patients requiring narcotics and amount of narcotics used was lower (P = 0.04 vs P = 0.0004, respectively). Mainly due to less pain-related over-stay, percentage of patients requiring more than a day of hospital stay was less in the TAP (12%) versus control group (18%) (P = 0.01). CONCLUSION: To our knowledge, the utility of TAP block in patients undergoing minimally invasive adrenalectomy has not been reported in the past. This study shows that there may be benefits of laparoscopic TAP block in reducing post-operative narcotic usage while improving pain control in these patients.