Investigator

Takuya Yokoe

Kansai Medical University

TYTakuya Yokoe
Papers(6)
Transgastric drainage…Treatment for SMARCA4…Monogram and Heat Map…<scp>R0</scp> …Pneumovaginoscopy-ass…Acute abdomen caused …
Collaborators(4)
Hidetaka OkadaMasato KitaYoji HisamatsuYusuke Butsuhara
Institutions(1)
Kansai Medical Univer…

Papers

Monogram and Heat Map on Magnetic Resonance Imaging to Evaluate the Recommendation for Myomectomy in Patients with Infertility: A Pilot Study

Uterine myomas can cause infertility. Studies are attempting to determine the indications for myomectomy. However, the multiplicity and localization of myomas complicate this issue. We aimed to develop a visualization tool to aid patients with infertility in their decision-making for myomectomy. We included 191 women with uterine myoma attending an outpatient infertility clinic, of whom 124 patients underwent myomectomy. Of these, 65 (52.4%) patients became pregnant within 17.6 months after surgery, and 54 (83.1%) of them had a live birth. A logistic regression model predicting the pregnancy rate (area under the curve, 0.82; 95% confidence interval, 0.74-0.89; validation value, 74.6%) was generated using the leave-one-out cross-validation method. This model incorporated five factors: age, maximum level of infertility intervention following myomectomy, presence of submucosal myoma, maximum diameter of the myoma, and type of myomas (multiple or single). We successfully visualized the degree of involvement of each factor in the pregnancy rate by developing a nomogram based on this model. We expanded the data from the preoperative magnetic resonance images and applied machine learning using a convolutional neural network. The classification accuracy was 71.4% for sensitivity and 77.7% for specificity. Heatmap images, generated using gradient-weighted class activation mapping to show the classification results of this model, could distinguish between myomas that required enucleation and those that did not. Although a larger sample size is needed to further validate our findings, this innovative pilot study demonstrates the potential of machine learning to refine assessment criteria and improve patient decision-making.

Pneumovaginoscopy-assisted radical hysterectomy for early-stage cervical cancer: a novel bidirectional approach for tumor spillage prevention and R0 resection

This study evaluated the feasibility and outcomes of pneumovaginoscopy-assisted radical hysterectomy (PVRH) for cervical cancer up to stage IIA using a bidirectional fascia-oriented and nerve-sparing surgical approach. This retrospective observational cohort study examined the operative outcomes and prognoses of patients who underwent PVRH (n=59) for up to stage IIA cervical cancer. The basic procedure was Kyoto B2 (Viper Type II nerve-sparing) radical hysterectomy and pelvic lymphadenectomy through simultaneous vaginal and abdominal (open or laparoscopic) approaches. In all cases, pneumovaginoscopy (PV) was used to create a vaginal cuff and dissect the paracolpium and paracervical endopelvic fascia to minimize nerve damage. Thirty-eight (64.4%) patients had stage IB1 cancer. Seven (11.9%) had vaginal invasion (stage IIA1, n=4; IIA2, n=3). The abdominal approach was open in 38 cases and laparoscopic in 21. Adjuvant therapy was administered to 24 patients (41%); one patient received concurrent chemoradiotherapy for gastric-type adenocarcinoma. There were three (6.1%) intraoperative complications (CO PVRH is a new fascia-oriented and nerve-sparing surgery for early-stage cervical cancer. Further, it has favorable operative outcomes and good prognoses, similar to those of adjacent pelvic surgery such as trans-anal total mesorectal excision and radical prostatectomy.

8Works
6Papers
4Collaborators
Uterine Cervical NeoplasmsAdenocarcinomaUterine NeoplasmsGenital Neoplasms, MaleOvarian NeoplasmsNeoplasm StagingGenital Neoplasms, Female