TTTakayuki Takahashi
Papers(2)
Successful treatment …Development of a prog…
Collaborators(10)
Yoichiro YamamotoYusuke KobayashiDaisuke AokiGen TamiyaHikaru MatsuokaJun AkatsukaJun TakayamaKouji BannoMasaru NakamuraMayuka Anko
Institutions(6)
Federation Of Nationa…Riken Center For Adva…University of TsukubaKeio UniversityKeio UniversityAvalon University Sch…

Papers

Successful treatment of chylous leakage with delayed presentation after endometrial cancer surgery using dietary therapy, octreotide, and computed tomography‐guided lymphangiography: A case report and literature review

Abstract Objective Chylous ascites (CA) is a rare yet clinically significant complication following gynecologic cancer surgery, with incidence rates of 0.17 % to 9%. We aimed to describe a case of CA with a delayed clinical presentation nearly 100 days postoperatively in a patient with advanced endometrial cancer and to review the management strategies. Methods We retrospectively evaluated a 75‐year‐old patient who underwent radical hysterectomy, bilateral salpingo‐oophorectomy, extended lymphadenectomy (pelvic and para‐aortic), and partial omentectomy for stage IIIB endometrial cancer. Data collected included onset timing, ascitic fluid analysis, imaging findings, and treatment responses. Additionally, a narrative review identified 13 relevant studies discussing the onset, risk factors, diagnosis, and therapies for post‐operative CA in gynecologic oncology. Results Although CA typically appears within 4 to 21 days, our patient developed CA at approximately post‐operative day 99. Diagnostic paracentesis confirmed triglyceride‐rich ascitic fluid, establishing the diagnosis of CA. Dietary modification (fasting followed by medium‐chain triglyceride diet), octreotide therapy, and computed tomography (CT)‐guided lymphangiography effectively controlled the chylous leakage without requiring surgery. Conservative measures—low‐fat or medium‐chain triglyceride diets, total parenteral nutrition, and somatostatin analogs—are considered first‐line, while lymphangiography/embolization and eventual surgical ligation may be needed for refractory cases. Conclusions This case illustrates that CA with a delayed clinical presentation can be successfully treated with a stepwise conservative approach comprising dietary therapy, octreotide, and CT‐guided lymphangiography, even when presenting more than 3 months postoperatively. Moreover, our patient remained free of disease recurrence at 1 year and 8 months postoperatively, underscoring that timely management of CA can avoid delays in adjuvant therapy.

Development of a prognostic prediction support system for cervical intraepithelial neoplasia using artificial intelligence-based diagnosis

Human papillomavirus subtypes are predictive indicators of cervical intraepithelial neoplasia (CIN) progression. While colposcopy is also an essential part of cervical cancer prevention, its accuracy and reproducibility are limited because of subjective evaluation. This study aimed to develop an artificial intelligence (AI) algorithm that can accurately detect the optimal lesion associated with prognosis using colposcopic images of CIN2 patients by utilizing objective AI diagnosis. We identified colposcopic findings associated with the prognosis of patients with CIN2. We developed a convolutional neural network that can automatically detect the rate of high-grade lesions in the uterovaginal area in 12 segments. We finally evaluated the detection accuracy of our AI algorithm compared with the scores by multiple gynecologic oncologists. High-grade lesion occupancy in the uterovaginal area detected by senior colposcopists was significantly correlated with the prognosis of patients with CIN2. The detection rate for high-grade lesions in 12 segments of the uterovaginal area by the AI system was 62.1% for recall, and the overall correct response rate was 89.7%. Moreover, the percentage of high-grade lesions detected by the AI system was significantly correlated with the rate detected by multiple gynecologic senior oncologists (r=0.61). Our novel AI algorithm can accurately determine high-grade lesions associated with prognosis on colposcopic images, and these results provide an insight into the additional utility of colposcopy for the management of patients with CIN2.

6Works
2Papers
13Collaborators