Publications by authors named "Kanabu Nawa"

20 Publications

  • Page 1 of 1

Helical Skin Radiation Therapy Including Total Skin Radiation Therapy Using Tomotherapy for Primary Cutaneous Lymphoma With Bone Marrow Suppression as a Related Adverse Event.

Pract Radiat Oncol 2021 May-Jun;11(3):e308-e321. Epub 2021 Jan 10.

Department of Radiology, University of Tokyo Hospital, Hongo, Bunkyo-ku, Tokyo, Japan.

Purpose: Total skin electron beam therapy (TSEBT) is useful for primary cutaneous lymphoma. However, helical skin radiation therapy (HSRT) using tomotherapy may avoid the complexity and uncertainty of TSEBT.

Methods And Materials: All patients with primary cutaneous lymphoma who underwent HSRT at our hospital between June 2015 and July 2019 were investigated, including 7 patients registered in a clinical trial approved by an institutional review board (ID UMIN000022142). HSRT was performed in 3 partitioned skin areas: head and neck, trunk and arms, and legs.

Results: A total of 24 patients with 53 skin areas (including 8 patients with 24 skin areas who had undergone sequential total skin irradiation), with a median follow-up time of 13 months (range, 2-50), were investigated. Twenty patients (83.3%) had mycosis fungoides (MF). For 41 of 53 (77.4%) cases, a dose of 20 Gy in 10 fractions was used. The overall response rate in the treated fields of each HSRT in patients with MF was 100%, including 38 (80.9%) complete response, 4 (8.5%) good partial response, and 5 (10.6%) partial response. Eight patients with MF who underwent sequential total skin irradiation showed a 100% complete response. For patients with MF, the median survival time after a first round of HSRT was 22 months (95% confidence interval [CI], 13.6-30.4 months), the median response duration of each HSRT was 5 months (95% CI, 3.67-6.32 months), and the median time to in-field reirradiation for each HSRT was 15 months (95% CI, 9.76-20.24 months). Bone marrow suppression (grade ≥3) often occurred (94.1%) with HSRT on trunk and arm skin. An early patient died of HSRT-caused grade 5 leukopenia.

Conclusions: HSRT targeting trunk and arm skin induced severe bone marrow suppression that led to a temporary palliative effect. TSEBT should still be considered standard treatment for primary cutaneous lymphoma covering the total body surface area.
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http://dx.doi.org/10.1016/j.prro.2020.11.007DOI Listing
January 2021

[Improvement in Image Quality of CBCT during Treatment by Cycle Generative Adversarial Network].

Nihon Hoshasen Gijutsu Gakkai Zasshi 2020 ;76(11):1173-1184

Department of Radiology, University of Tokyo Hospital.

Purpose: Volumetric modulated arc therapy (VMAT) can acquire projection images during rotational irradiation, and cone-beam computed tomography (CBCT) images during VMAT delivery can be reconstructed. The poor quality of CBCT images prevents accurate recognition of organ position during the treatment. The purpose of this study was to improve the image quality of CBCT during the treatment by cycle generative adversarial network (CycleGAN).

Method: Twenty patients with clinically localized prostate cancer were treated with VMAT, and projection images for intra-treatment CBCT (iCBCT) were acquired. Synthesis of PCT (SynPCT) with improved image quality by CycleGAN requires only unpaired and unaligned iCBCT and planning CT (PCT) images for training. We performed visual and quantitative evaluation to compare iCBCT, SynPCT and PCT deformable image registration (DIR) to confirm the clinical usefulness.

Result: We demonstrated suitable CycleGAN networks and hyperparameters for SynPCT. The image quality of SynPCT improved visually and quantitatively while preserving anatomical structures of the original iCBCT. The undesirable deformation of PCT was reduced when SynPCT was used as its reference instead of iCBCT.

Conclusion: We have performed image synthesis with preservation of organ position by CycleGAN for iCBCT and confirmed the clinical usefulness.
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http://dx.doi.org/10.6009/jjrt.2020_JSRT_76.11.1173DOI Listing
November 2020

Surface and build-up dose comparison between Elekta 6 MV flattening filter and flattening-filter-free beams using an advanced Markus ionization chamber and a solid water-equivalent phantom.

J Appl Clin Med Phys 2020 Dec 12;21(12):334-339. Epub 2020 Nov 12.

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

Using a plane-parallel advanced Markus ionization chamber and a stack of water-equivalent solid phantom blocks, percentage surface and build-up doses of Elekta 6 MV flattening filter (FF) and flattening-filter-free (FFF) beams were measured as a function of the phantom depth for field sizes ranging from 2 × 2 to 10 × 10 cm . It was found that the dose difference between the FF and the FFF beams was relatively small. The maximum dose difference between the FF and the FFF beams was 4.4% at a depth of 1 mm for a field size of 2 × 2 cm . The dose difference was gradually decreased while the field size was increased up to 10 × 10 cm . The measured data were also compared to published Varian FF and FFF data, suggesting that the percentage surface and build-up doses as well as the percentage dose difference between FF and FFF beams by our Elekta linac were smaller than those by the Varian linac.
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http://dx.doi.org/10.1002/acm2.13094DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7769389PMC
December 2020

Retrospective dose reconstruction of prostate stereotactic body radiotherapy using cone-beam CT and a log file during VMAT delivery with flattening-filter-free mode.

Radiol Phys Technol 2020 Sep 12;13(3):238-248. Epub 2020 Jul 12.

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

This study aimed to reconstruct the dose distribution of single fraction of stereotactic body radiotherapy for patients with prostate cancer using cone-beam computed tomography (CBCT) and a log file during volumetric-modulated arc therapy (VMAT) delivery with flattening-filter-free (FFF) mode. Twenty patients with clinically localized prostate cancer were treated with FFF-VMAT, and projection images for in-treatment CBCT (iCBCT) imaging were concomitantly acquired with a log file. A D dose of 36.25 Gy in five fractions was prescribed to each planning target volume (PTV) on each treatment planning CT (pCT). Deformed pCT (dCT) was obtained from the iCBCT using a hybrid deformable image registration algorithm. Dose distributions on the dCT were calculated using Pinnacle v9.10 by converting the log file data to Pinnacle data format using an in-house software. Dose warping was performed by referring to deformation vector fields calculated from pCT and dCT. Reconstructed dose distribution was compared with that of the original plan. Dose differences between the original and reconstructed dose distributions were within 3% at the isocenter and observed in PTV and organ-at-risk (OAR) regions. Differences in OAR regions were relatively larger than those in the PTV, presumably because OARs were more deformed than the PTV. Therefore, our method can be used successfully to reconstruct the dose distributions of one fraction using iCBCT and a log file during FFF-VMAT delivery.
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http://dx.doi.org/10.1007/s12194-020-00574-3DOI Listing
September 2020

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

Acceptable fetal dose using flattening filter-free volumetric arc therapy (FFF VMAT) in postoperative chemoradiotherapy of tongue cancer during pregnancy.

Clin Transl Radiat Oncol 2020 Jan 14;20:9-12. Epub 2019 Oct 14.

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

Optimizing irradiation protocols for pregnant women is challenging, because there are few cases and a dearth of fetal dosimetry data. We cared for a 36-year-old pregnant woman with tongue cancer. Prior to treatment, we compared three intensity-modulated radiation therapy (IMRT) techniques, including helical tomotherapy, volumetric arc therapy (VMAT), and flattening-filter free VMAT (FFF-VMAT) using treatment planning software. FFF-VMAT achieved the minimum fetal exposure and was selected as the optimal modality. We prescribed 66 Gy to the involved nodes, 60 Gy to the tumor bed and ipsilateral neck, and 54 Gy to the contralateral neck over 33 fractions. To confirm the out-of-field exposure per fraction, surface doses and the rectal dose were measured during FFF-VMAT delivery. Postoperative chemoradiotherapy was delivered using IMRT and a cisplatin regimen. Without any shielding, the total fetal dose was 0.03 Gy, within the limits established by the ICRP. A healthy girl was born vaginally at 37 weeks' gestation.
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http://dx.doi.org/10.1016/j.ctro.2019.10.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6833340PMC
January 2020

Optimization of treatment strategy by using a machine learning model to predict survival time of patients with malignant glioma after radiotherapy.

J Radiat Res 2019 Nov;60(6):818-824

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

The purpose of this study was to predict the survival time of patients with malignant glioma after radiotherapy with high accuracy by considering additional clinical factors and optimize the prescription dose and treatment duration for individual patient by using a machine learning model. A total of 35 patients with malignant glioma were included in this study. The candidate features included 12 clinical features and 192 dose-volume histogram (DVH) features. The appropriate input features and parameters of the support vector machine (SVM) were selected using the genetic algorithm based on Akaike's information criterion, i.e. clinical, DVH, and both clinical and DVH features. The prediction accuracy of the SVM models was evaluated through a leave-one-out cross-validation test with residual error, which was defined as the absolute difference between the actual and predicted survival times after radiotherapy. Moreover, the influences of various values of prescription dose and treatment duration on the predicted survival time were evaluated. The prediction accuracy was significantly improved with the combined use of clinical and DVH features compared with the separate use of both features (P < 0.01, Wilcoxon signed rank test). Mean ± standard deviation of the leave-one-out cross-validation using the combined clinical and DVH features, only clinical features and only DVH features were 104.7 ± 96.5, 144.2 ± 126.1 and 204.5 ± 186.0 days, respectively. The prediction accuracy could be improved with the combination of clinical and DVH features, and our results show the potential to optimize the treatment strategy for individual patients based on a machine learning model.
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http://dx.doi.org/10.1093/jrr/rrz066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7357235PMC
November 2019

Improvement of the robustness to set up error by a virtual bolus in total scalp irradiation with Helical TomoTherapy.

Radiol Phys Technol 2019 Dec 23;12(4):433-437. Epub 2019 Oct 23.

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

Intensity-modulated radiation therapy has recently been used for total scalp irradiation. In inverse planning, the treatment planning system increases the fluence of tangential beam near the skin surface to counter the build-up region. Consequently, the dose to the skin surface increases even with small setup errors. Replacing the electron density of the surrounding air of some thickness with a virtual bolus during optimization could suppress the extremely high fluence near the skin. We confirmed the usefulness of a virtual bolus in total scalp irradiation. For each patient, two beams were planned, one with and the other without a virtual bolus. The dose distribution was calculated using computed tomography images that were shifted to simulate setup errors. The hot spot dose was suppressed in the plans using a virtual bolus. In conclusion, using a virtual bolus improved the robustness to setup errors.
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http://dx.doi.org/10.1007/s12194-019-00539-1DOI Listing
December 2019

Standardization of imaging features for radiomics analysis.

J Med Invest 2019 ;66(1.2):35-37

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

Radiomics has the potential to provide tumor characteristics with noninvasive and repeatable way. The purpose of this paper is to evaluate the standardization effect of imaging features for radiomics analysis. For this purpose, we prepared two CT databases ; one includes 40 non-small cell lung cancer (NSCLC) patients for whom tumor biopsies was performed before stereotactic body radiation therapy in The University of Tokyo Hospital, and the other includes 29 early-stage NSCLC datasets from the Cancer Imaging Archive. The former was used as the training data, whereas the later was used as the test data in the evaluation of the prediction model. In total, 476 imaging features were extracted from each data. Then, both training and test data were standardized as the min-max normalization, the z-score normalization, and the whitening from the principle component analysis. All of standardization strategies improved the accuracy for the histology prediction. The area under the receiver observed characteristics curve was 0.725, 0.789, and 0.785 in above standardizations, respectively. Radiomics analysis has shown that robust features have a high prognostic power in predicting early-stage NSCLC histology subtypes. The performance was able to be improved by standardizing the data in the feature space. J. Med. Invest. 66 : 35-37, February, 2019.
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http://dx.doi.org/10.2152/jmi.66.35DOI Listing
December 2019

Stereotactic body radiotherapy for centrally-located lung tumors with 56 Gy in seven fractions: A retrospective study.

Oncol Lett 2018 Oct 23;16(4):4498-4506. Epub 2018 Jul 23.

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

Stereotactic body radiotherapy (SBRT) for centrally-located lung tumors remains a challenge because of the increased risk of treatment-related adverse events (AEs), and uncertainty around prescribing the optimal dose. The present study reported the results of central tumor SBRT with 56 Gy in 7 fractions (fr) at the University of Tokyo Hospital. A total of 35 cases that underwent SBRT with or without volumetric-modulated arc therapy consisting of 56 Gy/7 fr for central lung lesions between 2010 and 2016 at the University of Tokyo Hospital were reveiwed. A central lesion was defined as a tumor within 2 cm of the proximal bronchial tree (RTOG 0236 definition) or within 2 cm in all directions of any critical mediastinal structure. Local control (LC), overall survival (OS), and AEs were investigated. The Kaplan-Meier method was used to estimate LC and OS. AEs were scored per the Common Terminology Criteria for Adverse Events Version 4.0. Thirty-five patients with 36 central lung lesions were included. Fifteen lesions were primary non-small cell lung cancer (NSCLC), 13 were recurrences of NSCLC, and 8 had oligo-recurrences from other primaries. Median tumor diameter was 29 mm. Eighteen patients had had prior surgery. At a median follow-up of 13.1 months for all patients and 18.3 months in surviving patients, 22 patients had died, ten due to primary disease (4 NSCLC), while three were treatment-related. The 1- and 2-year OS were 57.3 and 40.4%, respectively, and median OS was 15.7 months. Local recurrence occurred in only two lesions. 1- and 2-year LC rates were both 96%. Nine patients experienced grade ≥3 toxicity, representing 26% of the cohort. Two of these were grade 5, one pneumonitis and one hemoptysis. Considering the background of the subject, tumor control of our central SBRT is promising, especially in primary NSCLC. However, the safety of SBRT to central lung cancer remains controversial.
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http://dx.doi.org/10.3892/ol.2018.9188DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6126178PMC
October 2018

Cone Beam Computed Tomography Image Quality Improvement Using a Deep Convolutional Neural Network.

Cureus 2018 Apr 29;10(4):e2548. Epub 2018 Apr 29.

Radiology, The University of Tokyo Hospital.

Introduction Cone beam computed tomography (CBCT) plays an important role in image-guided radiation therapy (IGRT), while having disadvantages of severe shading artifact caused by the reconstruction using scatter contaminated and truncated projections. The purpose of this study is to develop a deep convolutional neural network (DCNN) method for improving CBCT image quality. Methods CBCT and planning computed tomography (pCT) image pairs from 20 prostate cancer patients were selected. Subsequently, each pCT volume was pre-aligned to the corresponding CBCT volume by image registration, thereby leading to registered pCT data (pCT). Next, a 39-layer DCNN model was trained to learn a direct mapping from the CBCT to the corresponding pCTimages. The trained model was applied to a new CBCT data set to obtain improved CBCT (i-CBCT) images. The resulting i-CBCT images were compared to pCT using the spatial non-uniformity (SNU), the peak-signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM). Results The image quality of the i-CBCT has shown a substantial improvement on spatial uniformity compared to that of the original CBCT, and a significant improvement on the PSNR and the SSIM compared to that of the original CBCT and the enhanced CBCT by the existing pCT-based correction method. Conclusion We have developed a DCNN method for improving CBCT image quality. The proposed method may be directly applicable to CBCT images acquired by any commercial CBCT scanner.
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http://dx.doi.org/10.7759/cureus.2548DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6021187PMC
April 2018

Flattening filter-free technique in volumetric modulated arc therapy for lung stereotactic body radiotherapy: A clinical comparison with the flattening filter technique.

Oncol Lett 2018 Mar 16;15(3):3928-3936. Epub 2018 Jan 16.

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

The present study sought to evaluate the impact of the flattening filter-free (FFF) technique in volumetric modulated arc therapy for lung stereotactic body radiotherapy. Its clinical safety and availability were compared with the flattening filter (FF) method. The cases of 65 patients who underwent lung volumetric modulated arc therapy-stereotactic body radiotherapy (VMAT-SBRT) using FF or FFF techniques were reviewed. A total of 55 Gy/4 fractions (fr) was prescribed for peripheral lesions or 56 Gy/7 fr for central lesions. The total monitor units (MU), treatment time, dose to tumors, dose to organs at risk, tumor control (local control rate, overall survival, progression-free survival) and adverse events between cases treated with FF and cases treated with the FFF technique were compared. A total of 35 patients were treated with conventional FF techniques prior to November 2014 and 30 patients were treated with FFF techniques after this date. It was revealed that the beam-on time was significantly shortened by the FFF technique (P<0.01). Other factors were similar for FFF and FF plans in respect to conformity (P=0.95), homogeneity (P=0.20) and other dosimetric values, including total MU and planning target volume/internal target volume coverage. The median follow-up period was 18 months (range, 2-35). One-year local control rates were 97.1 and 90.0% in the FF group and FFF groups, respectively (P=0.33). Grade 3 pneumonitis was observed in 5.8% of FF patients and 3.4% of FFF patients (P=1.00). No other adverse events ≥grade 3 were observed. The results of the study suggest that VMAT-SBRT using the FFF technique shortens the treatment time for lung SBRT while maintaining a high local control rate with low toxicity.
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http://dx.doi.org/10.3892/ol.2018.7809DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5854932PMC
March 2018

Classification of early stage non-small cell lung cancers on computed tomographic images into histological types using radiomic features: interobserver delineation variability analysis.

Radiol Phys Technol 2018 Mar 5;11(1):27-35. Epub 2017 Dec 5.

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

Radiomics, which involves the extraction of large numbers of quantitative features from medical images, has attracted attention in cancer research. In radiomics analysis, tumor segmentation is a crucial step. In this study, we evaluated the potential application of radiomics for predicting the histology of early stage non-small cell lung cancer (NSCLC) by analyzing interobserver variability in tumor delineation. Forty patient datasets were included in this study, 21 involving adenocarcinomas and 19 involving squamous cell carcinomas. All patients underwent stereotactic body radiotherapy treatment. In total, 476 features were extracted from each dataset, representing treatment planning, computed tomography images, and gross tumor volume (GTV). The definition of GTV can significantly affect the histology prediction. Therefore, in the present study, the effect of interobserver tumor delineation variability on radiomic features was evaluated by preparing 4 volumes of interest (VOIs) for each patient, as follows: the original GTV (which was delineated at treatment planning); two GTVs delineated retrospectively by radiation oncologists; and a semi-automatic GTV contoured by a medical physicist. Radiomic features extracted from each VOI were then analyzed using a naïve Bayesian model. Area-under-the-curve (AUC) analysis showed that interobserver variability in delineation is a significant factor in radiomics performance. Nevertheless, with 8 selected features, AUC values averaged over the VOIs were high (0.725 ± 0.070). The present study indicated that radiomics has potential for predicting early stage NSCLC histology despite variability in delineation. The high prediction accuracy implies that noninvasive histology evaluation by radiomics is a promising clinical application.
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http://dx.doi.org/10.1007/s12194-017-0433-2DOI Listing
March 2018

Evaluation of a commercial automatic treatment planning system for prostate cancers.

Med Dosim 2017 Autumn;42(3):203-209. Epub 2017 May 23.

Department of Radiology, University of Tokyo Hospital, Bunkyo-ku, Tokyo, Japan.

Recent developments in Radiation Oncology treatment planning have led to the development of software packages that facilitate automated intensity-modulated radiation therapy (IMRT) and volumetric-modulated arc therapy (VMAT) planning. Such solutions include site-specific modules, plan library methods, and algorithm-based methods. In this study, the plan quality for prostate cancer generated by the Auto-Planning module of the Pinnacle radiation therapy treatment planning system (v9.10, Fitchburg, WI) is retrospectively evaluated. The Auto-Planning module of Pinnacle uses a progressive optimization algorithm. Twenty-three prostate cancer cases, which had previously been planned and treated without lymph node irradiation, were replanned using the Auto-Planning module. Dose distributions were statistically compared with those of manual planning by the paired t-test at 5% significance level. Auto-Planning was performed without any manual intervention. Planning target volume (PTV) dose and dose to rectum were comparable between Auto-Planning and manual planning. The former, however, significantly reduced the dose to the bladder and femurs. Regression analysis was performed to examine the correlation between volume overlap between bladder and PTV divided by the total bladder volume and resultant V70. The findings showed that manual planning typically exhibits a logistic way for dose constraint, whereas Auto-Planning shows a more linear tendency. By calculating the Akaike information criterion (AIC) to validate the statistical model, a reduction of interoperator variation in Auto-Planning was shown. We showed that, for prostate cancer, the Auto-Planning module provided plans that are better than or comparable with those of manual planning. By comparing our results with those previously reported for head and neck cancer treatment, we recommend the homogeneous plan quality generated by the Auto-Planning module, which exhibits less dependence on anatomic complexity.
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http://dx.doi.org/10.1016/j.meddos.2017.03.004DOI Listing
May 2018

A report that Fukushima residents are concerned about radiation from Land, Food and Radon.

J Radiat Res 2016 Jul 16;57(4):418-21. Epub 2016 Mar 16.

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

The Great East Japan Earthquake and subsequent TEPCO Fukushima Daiichi nuclear disaster occurred on 11 March 2011, which caused the leakage of radioactive materials into the environment. In this study, we report public concerns about radiation in Fukushima and Tokyo almost one year after the nuclear disaster. We examined the public concerns by analyzing the data from 1022 participants, 555 in Fukushima and 467 in Tokyo. They were asked whether they were concerned about radiation from some of six different types of sources, which could be answered in a binary way, 'yes' or 'no'. We found not only similarities, but also significant differences in the degrees of concerns between Fukushima residents and Tokyo ones. Fukushima residents more concerned about radiation from land, food and radon in larger rate than that of Tokyo ones, while Tokyo residents were concerned about radiation from medical care. Residents in neither location were concerned about radiation from space. Our results suggested that careful risk communication should be undertaken, adaptively organized depending on location and other factors, e.g. comprehension about radiation, presence of the experience of evacuation, and also age and gender of the people.
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http://dx.doi.org/10.1093/jrr/rrw017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4973642PMC
July 2016

External effective radiation dose to workers in the restricted area of the Fukushima Daiichi Nuclear Power Plant during the third year after the Great East Japan Earthquake.

J Radiat Res 2016 Mar 9;57(2):178-81. Epub 2015 Dec 9.

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

Since the Great East Japan Earthquake on 11 March 2011, Iitate Village has continued to be classified as a deliberate evacuation area, in which residents are estimated to receive an annual additional effective radiation dose of >20 mSv. Some companies still operate in Iitate Village, with a special permit from the Cabinet Office Team in Charge of Assisting the Lives of Disaster Victims. In this study, we measured the annual effective radiation dose to workers in Iitate Village from 15 January to 13 December 2013. The workers stayed in Iitate for 10 h and left the village for the remaining 14 h each working day. They worked for 5 days each week in Iitate Village, but stayed outside of the village for the remaining 2 days each week. We found that the effective radiation dose of 70% of the workers was <2 mSv, including natural radiation; the maximum dose was 3.6 mSv. We estimated the potential annual additional effective radiation dose if people returned full-time to Iitate. Our analysis supports the plan for people to return to their home village at the end of 2017.
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http://dx.doi.org/10.1093/jrr/rrv073DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4795945PMC
March 2016
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