Publications by authors named "Manabu Kujiraoka"
Article Synopsis
- - The study focuses on developing a deep learning model to automatically identify bleeding areas during laparoscopic hepatectomy, which can help improve safety in surgeries by enhancing hemostasis.
- - Researchers used a dataset of 2203 annotated images from 44 laparoscopic videos, dividing them into training, validation, and test subsets, and employed a convolutional neural network for semantic segmentation.
- - The evaluation metrics showed the model achieved precision of 0.76, recall of 0.79, and Dice coefficient of 0.77, indicating its potential for real-time alerts and training assessments in surgical practice.
Laparoscopic deroofing (LD) for giant liver cysts using indocyanine green (ICG) fluorescence imaging was performed in two patients: a 53-year-old man with a 26-cm, symptomatic cyst and a 50-year-old woman with a 13-cm, symptomatic cyst. ICG fluorescence imaging can be used to easily identify the boundary between the liver parenchyma and the liver cyst. No postoperative bile leakage was observed in both patients.
View Article and Find Full Text PDFValidation of a surgical difficulty grading system in laparoscopic cholecystectomy for acute cholecystitis.
J Hepatobiliary Pancreat Sci
February 2024
Background: The surgical difficulty of laparoscopic cholecystectomy (LC) for acute cholecystitis varies from case to case, and appropriate intraoperative evaluation would help prevent bile duct injury (BDI).
Methods: We analyzed 178 patients who underwent LC for acute cholecystitis. Expert surgeons and trainees individually evaluated the surgical difficulty.
Purpose: Acute abdominal infections can be fatal if the causative organism (s) are misidentified. The spread of antimicrobial-resistant bacteria has become a serious problem worldwide, making antibiotic selection extremely difficult. Using quantitative metagenomic analysis, we evaluated a commercial multiplex polymerase chain reaction (PCR) system (FilmArray™, bioMérieux, Marcy-l'Étoile, France) for the rapid identification of causative bacteria.
View Article and Find Full Text PDFPurposes: Acute cholangitis and cholecystitis can become severe conditions as a result of inappropriate therapeutic administration and thereafter become increasingly resistant to antimicrobial treatment. The simultaneous detection of the bacterial nucleic acid and antimicrobial resistance gene is covered by the national health insurance program in Japan for sepsis. In this study, we evaluate the use of a multichannel gene autoanalyzer (Verigene system) for the quick detection of causative bacteria in cases of acute cholangitis and cholecystitis.
View Article and Find Full Text PDFAcute cholecystitis (AC), which is strongly associated with retrograde bacterial infection, is an inflammatory disease that can be fatal if inappropriately treated. Currently, bacterial culture testing, which is basically recommended to detect the etiological agent, is a time-consuming (4-6 days), non-comprehensive approach. To rapidly detect a potential pathogen and predict its antimicrobial susceptibility, we undertook a metagenomic approach to characterize the bacterial infection associated with AC.
View Article and Find Full Text PDFIntroduction: This study evaluates the therapeutic outcomes for laparoscopic cholecystectomy for acute cholecystitis based on the time from symptom onset to surgery.
Methods: This study enrolled 224 patients. Patients' characteristics and operative outcomes were compared between patient groups based on the timing of laparoscopic cholecystectomy from symptom onset: ≤72 h versus >72 h, and ≤7 days versus ≥8 days.