Publications by authors named "Yuki Nozawa"

6 Publications

  • Page 1 of 1

Phase II study of stereotactic body radiotherapy with hydrogel spacer for prostate cancer: acute toxicity and propensity score-matched comparison.

Radiat Oncol 2021 Jun 12;16(1):107. Epub 2021 Jun 12.

Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyoku, Tokyo, 113-8655, Japan.

Background: The efficacy of a hydrogel spacer in stereotactic body radiotherapy (SBRT) has not been clarified. We evaluated the safety and efficacy of SBRT in combination with a hydrogel spacer for prostate cancer.

Methods: This is a prospective single-center, single-arm phase II study. Prostate cancer patients without lymph node or distant metastasis were eligible. All patients received a hydrogel spacer insertion, followed by SBRT of 36.25 Gy in 5 fractions with volumetric modulated arc therapy. The primary endpoint was physician-assessed acute gastrointestinal (GI) toxicity within 3 months. The secondary endpoints were physician-assessed acute genitourinary (GU) toxicity, patient-reported outcomes evaluated by the EPIC and FACT-P questionnaires, and dosimetric comparison. We used propensity score-matched analyses to compare patients with the hydrogel spacer with those without the spacer. The historical data of the control without a hydrogel spacer was obtained from our hospital's electronic records.

Results: Forty patients were enrolled between February 2017 and July 2018. A hydrogel spacer significantly reduced the dose to the rectum. Grade 2 acute GI and GU toxicity occurred in seven (18%) and 17 (44%) patients. The EPIC bowel and urinary summary score declined from the baseline to the first month (P < 0.01, < 0.01), yet it was still significantly lower in the third month (P < 0.01, P = 0.04). For propensity score-matched analyses, no significant differences in acute GI and GU toxicity were observed between the two groups. The EPIC bowel summary score was significantly better in the spacer group at 1 month (82.2 in the spacer group and 68.5 in the control group).

Conclusions: SBRT with a hydrogel spacer had the dosimetric benefits of reducing the rectal doses. The use of the hydrogel spacer did not reduce physician-assessed acute toxicity, but it improved patient-reported acute bowel toxicity.

Trial Registration: Trial registration: UMIN-CTR, UMIN000026213. Registered 19 February 2017, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000029385 .
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13014-021-01834-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8199395PMC
June 2021

Fast Statistical Iterative Reconstruction for Mega-voltage Computed Tomography.

J Med Invest 2020 ;67(1.2):30-39

Department of Radiology, The University of Tokyo Hospital, Japan.

Statistical iterative reconstruction is expected to improve the image quality of computed tomography (CT). However, one of the challenges of iterative reconstruction is its large computational cost. The purpose of this review is to summarize a fast iterative reconstruction algorithm by optimizing reconstruction parameters. Megavolt projection data was acquired from a TomoTherapy system and reconstructed using in-house statistical iterative reconstruction algorithm. Total variation was used as the regularization term and the weight of the regularization term was determined by evaluating signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and visual assessment of spatial resolution using Gammex and Cheese phantoms. Gradient decent with an adaptive convergence parameter, ordered subset expectation maximization (OSEM), and CPU/GPU parallelization were applied in order to accelerate the present reconstruction algorithm. The SNR and CNR of the iterative reconstruction were several times better than that of filtered back projection (FBP). The GPU parallelization code combined with the OSEM algorithm reconstructed an image several hundred times faster than a CPU calculation. With 500 iterations, which provided good convergence, our method produced a 512 × 512 pixel image within a few seconds. The image quality of the present algorithm was much better than that of FBP for patient data. J. Med. Invest. 67 : 30-39, February, 2020.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2152/jmi.67.30DOI Listing
June 2021

Salvage stereotactic body radiotherapy for post-operative oligo-recurrence of non-small cell lung cancer: A single-institution analysis of 59 patients.

Oncol Lett 2020 Apr 17;19(4):2695-2704. Epub 2020 Feb 17.

Department of Radiology, University of Tokyo Hospital, Tokyo 113-8655, Japan.

A standard treatment for patients with early-stage non-small cell lung cancer (NSCLC) who undergo surgery, and subsequently develop local failure or intrathoracic oligo-recurrence, has not yet been established. The present study aimed to assess the feasibility of stereotactic body radiotherapy (SBRT) for this subgroup of patients. Consequently, a retrospective analysis was conducted of patients with NSCLC recurrence who were treated with SBRT, and previously underwent curative surgical resection between October 2011 and October 2016. Post-SBRT survival [overall survival (OS); progression-free survival (PFS); and local control (LC)] and toxicity were analyzed. Prognostic factors for OS were identified using univariate and multivariate analysis. A total of 52 patients and 59 tumors were analyzed. The median follow-up time was 25 months (35 months for surviving patients), and median OS following salvage SBRT was 32 months. The 1- and 3-year OS rates were 84.4 and 67.8%, respectively. 1- and 3-year PFS rates were 80.8 and 58.7%, respectively. Only 4 patients (7.7%) developed local failure. Median LC was 71 months and 1- and 3-year LC rate were 97.9 and 94.9%, respectively. A total of 4 patients experienced grade 3 or higher adverse events (AEs) and two experienced grade 5 AEs (pneumonitis and hemoptysis). Central tumor location and the possibility of re-operation were independent prognostic factors for OS. The present study indicated that post-operative salvage SBRT is a promising therapeutic option for patients with NSCLC with locoregional or intrathoracic oligo-recurrence. We regard toxicity was also acceptable. However, further research is required on the appropriate selection of subjects, and stratification of the analysis by certain risk factors would increase the accuracy of the conclusions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3892/ol.2020.11407DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7068670PMC
April 2020

Publisher Correction: Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis.

Sci Rep 2020 Feb 17;10(1):3073. Epub 2020 Feb 17.

Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-020-60086-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026034PMC
February 2020

Prediction of malignant glioma grades using contrast-enhanced T1-weighted and T2-weighted magnetic resonance images based on a radiomic analysis.

Sci Rep 2019 12 19;9(1):19411. Epub 2019 Dec 19.

Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.

We conducted a feasibility study to predict malignant glioma grades via radiomic analysis using contrast-enhanced T1-weighted magnetic resonance images (CE-T1WIs) and T2-weighted magnetic resonance images (T2WIs). We proposed a framework and applied it to CE-T1WIs and T2WIs (with tumor region data) acquired preoperatively from 157 patients with malignant glioma (grade III: 55, grade IV: 102) as the primary dataset and 67 patients with malignant glioma (grade III: 22, grade IV: 45) as the validation dataset. Radiomic features such as size/shape, intensity, histogram, and texture features were extracted from the tumor regions on the CE-T1WIs and T2WIs. The Wilcoxon-Mann-Whitney (WMW) test and least absolute shrinkage and selection operator logistic regression (LASSO-LR) were employed to select the radiomic features. Various machine learning (ML) algorithms were used to construct prediction models for the malignant glioma grades using the selected radiomic features. Leave-one-out cross-validation (LOOCV) was implemented to evaluate the performance of the prediction models in the primary dataset. The selected radiomic features for all folds in the LOOCV of the primary dataset were used to perform an independent validation. As evaluation indices, accuracies, sensitivities, specificities, and values for the area under receiver operating characteristic curve (or simply the area under the curve (AUC)) for all prediction models were calculated. The mean AUC value for all prediction models constructed by the ML algorithms in the LOOCV of the primary dataset was 0.902 ± 0.024 (95% CI (confidence interval), 0.873-0.932). In the independent validation, the mean AUC value for all prediction models was 0.747 ± 0.034 (95% CI, 0.705-0.790). The results of this study suggest that the malignant glioma grades could be sufficiently and easily predicted by preparing the CE-T1WIs, T2WIs, and tumor delineations for each patient. Our proposed framework may be an effective tool for preoperatively grading malignant gliomas.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-019-55922-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6923390PMC
December 2019

Visual enhancement of Cone-beam CT by use of CycleGAN.

Med Phys 2020 Mar 3;47(3):998-1010. Epub 2020 Jan 3.

Department of Radiology, University of Tokyo Hospital, Tokyo, 113-8655, Japan.

Purpose: Cone-beam computed tomography (CBCT) offers advantages over conventional fan-beam CT in that it requires a shorter time and less exposure to obtain images. However, CBCT images suffer from low soft-tissue contrast, noise, and artifacts compared to conventional fan-beam CT images. Therefore, it is essential to improve the image quality of CBCT.

Methods: In this paper, we propose a synthetic approach to translate CBCT images with deep neural networks. Our method requires only unpaired and unaligned CBCT images and planning fan-beam CT (PlanCT) images for training. The CBCT images and PlanCT images may be obtained from other patients as long as they are acquired with the same scanner settings. Once trained, three-dimensionally reconstructed CBCT images can be directly translated into high-quality PlanCT-like images.

Results: We demonstrate the effectiveness of our method with images obtained from 20 prostate patients, and provide a statistical and visual comparison. The image quality of the translated images shows substantial improvement in voxel values, spatial uniformity, and artifact suppression compared to those of the original CBCT. The anatomical structures of the original CBCT images were also well preserved in the translated images.

Conclusions: Our method produces visually PlanCT-like images from CBCT images while preserving anatomical structures.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/mp.13963DOI Listing
March 2020
-->