{"title":"脑弥散加权成像的深度学习重建:在体外和体内研究中对图像质量改善、表观弥散系数评估和体素内非相干运动评估的功效","authors":"Satomu Hanamatsu, Kazuhiro Murayama, Yoshiharu Ohno, Kaori Yamamoto, Masao Yui, Hiroshi Toyama","doi":"10.4274/dir.2023.232149","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Deep learning reconstruction (DLR) to improve imaging quality has already been introduced, but no studies have evaluated the effect of DLR on diffusion-weighted imaging (DWI) or intravoxel incoherent motion (IVIM) in <i>in vitro</i> or <i>in vivo</i> studies. The purpose of this study was to determine the effect of DLR for magnetic resonance imaging (MRI) in terms of image quality improvement, apparent diffusion coefficient (ADC) assessment, and IVIM index evaluation on DWI through <i>in vitro</i> and <i>in vivo</i> studies.</p><p><strong>Methods: </strong>For the <i>in vitro</i> study, a phantom recommended by the Quantitative Imaging Biomarkers Alliance was scanned and reconstructed with and without DLR, and 15 patients with brain tumors with normal-appearing gray and white matter examined using IVIM and reconstructed with and without DLR were included in the <i>in vivo</i> study. The ADCs of all phantoms for DWI with and without DLR, as well as the coefficient of variation percentage (CV%), and ADCs and IVIM indexes for each participant, were evaluated based on DWI with and without DLR by means of region-of-interest measurements. For the <i>in vitro</i> study, using the mean ADCs for all phantoms, a t-test was adopted to compare DWI with and without DLR. For the <i>in vivo</i> study, a Wilcoxon signed-rank test was used to compare the CV% between the two types of DWI. In addition, the Wilcoxon signed-rank test was used to compare the ADC, true diffusion coefficient (<i>D</i>), pseudodiffusion coefficient (<i>D*</i>), and percentage of water molecules in micro perfusion within 1 voxel (<i>f</i>) with and without DLR; the limits of agreement of each parameter were determined through a Bland-Altman analysis.</p><p><strong>Results: </strong>The <i>in vitro</i> study identified no significant differences between the ADC values for DWI with and without DLR (<i>P</i> > 0.05), and the CV% was significantly different for DWI with and without DLR (<i>P</i> < 0.05) when <i>b</i> values ≥250 s/mm<sup>2</sup> were used. The <i>in vivo</i> study revealed that <i>D*</i> and <i>f</i> with and without DLR were significantly different (<i>P</i> < 0.001). The limits of agreement of the ADC, <i>D</i>, and <i>D*</i> values for DWI with and without DLR were determined as 0.00 ± 0.51 × 10<sup>-3</sup>, 0.00 ± 0.06 × 10<sup>-3</sup>, and 1.13 ± 4.04 × 10-3 mm<sup>2</sup>/s, respectively. The limits of agreement of the f values for DWI with and without DLR were determined as -0.01 ± 0.07.</p><p><strong>Conclusion: </strong>Deep learning reconstruction for MRI has the potential to significantly improve DWI quality at higher <i>b</i> values. It has some effect on <i>D*</i> and f values in the IVIM index evaluation, but ADC and <i>D</i> values are less affected by DLR.</p>","PeriodicalId":11341,"journal":{"name":"Diagnostic and interventional radiology","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10679550/pdf/","citationCount":"0","resultStr":"{\"title\":\"Deep learning reconstruction for brain diffusion-weighted imaging: efficacy for image quality improvement, apparent diffusion coefficient assessment, and intravoxel incoherent motion evaluation in <i>in vitro</i> and <i>in vivo</i> studies\",\"authors\":\"Satomu Hanamatsu, Kazuhiro Murayama, Yoshiharu Ohno, Kaori Yamamoto, Masao Yui, Hiroshi Toyama\",\"doi\":\"10.4274/dir.2023.232149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>Deep learning reconstruction (DLR) to improve imaging quality has already been introduced, but no studies have evaluated the effect of DLR on diffusion-weighted imaging (DWI) or intravoxel incoherent motion (IVIM) in <i>in vitro</i> or <i>in vivo</i> studies. The purpose of this study was to determine the effect of DLR for magnetic resonance imaging (MRI) in terms of image quality improvement, apparent diffusion coefficient (ADC) assessment, and IVIM index evaluation on DWI through <i>in vitro</i> and <i>in vivo</i> studies.</p><p><strong>Methods: </strong>For the <i>in vitro</i> study, a phantom recommended by the Quantitative Imaging Biomarkers Alliance was scanned and reconstructed with and without DLR, and 15 patients with brain tumors with normal-appearing gray and white matter examined using IVIM and reconstructed with and without DLR were included in the <i>in vivo</i> study. The ADCs of all phantoms for DWI with and without DLR, as well as the coefficient of variation percentage (CV%), and ADCs and IVIM indexes for each participant, were evaluated based on DWI with and without DLR by means of region-of-interest measurements. For the <i>in vitro</i> study, using the mean ADCs for all phantoms, a t-test was adopted to compare DWI with and without DLR. For the <i>in vivo</i> study, a Wilcoxon signed-rank test was used to compare the CV% between the two types of DWI. In addition, the Wilcoxon signed-rank test was used to compare the ADC, true diffusion coefficient (<i>D</i>), pseudodiffusion coefficient (<i>D*</i>), and percentage of water molecules in micro perfusion within 1 voxel (<i>f</i>) with and without DLR; the limits of agreement of each parameter were determined through a Bland-Altman analysis.</p><p><strong>Results: </strong>The <i>in vitro</i> study identified no significant differences between the ADC values for DWI with and without DLR (<i>P</i> > 0.05), and the CV% was significantly different for DWI with and without DLR (<i>P</i> < 0.05) when <i>b</i> values ≥250 s/mm<sup>2</sup> were used. The <i>in vivo</i> study revealed that <i>D*</i> and <i>f</i> with and without DLR were significantly different (<i>P</i> < 0.001). The limits of agreement of the ADC, <i>D</i>, and <i>D*</i> values for DWI with and without DLR were determined as 0.00 ± 0.51 × 10<sup>-3</sup>, 0.00 ± 0.06 × 10<sup>-3</sup>, and 1.13 ± 4.04 × 10-3 mm<sup>2</sup>/s, respectively. The limits of agreement of the f values for DWI with and without DLR were determined as -0.01 ± 0.07.</p><p><strong>Conclusion: </strong>Deep learning reconstruction for MRI has the potential to significantly improve DWI quality at higher <i>b</i> values. It has some effect on <i>D*</i> and f values in the IVIM index evaluation, but ADC and <i>D</i> values are less affected by DLR.</p>\",\"PeriodicalId\":11341,\"journal\":{\"name\":\"Diagnostic and interventional radiology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2023-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10679550/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Diagnostic and interventional radiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.4274/dir.2023.232149\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/8/9 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diagnostic and interventional radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4274/dir.2023.232149","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/8/9 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
Deep learning reconstruction for brain diffusion-weighted imaging: efficacy for image quality improvement, apparent diffusion coefficient assessment, and intravoxel incoherent motion evaluation in in vitro and in vivo studies
Purpose: Deep learning reconstruction (DLR) to improve imaging quality has already been introduced, but no studies have evaluated the effect of DLR on diffusion-weighted imaging (DWI) or intravoxel incoherent motion (IVIM) in in vitro or in vivo studies. The purpose of this study was to determine the effect of DLR for magnetic resonance imaging (MRI) in terms of image quality improvement, apparent diffusion coefficient (ADC) assessment, and IVIM index evaluation on DWI through in vitro and in vivo studies.
Methods: For the in vitro study, a phantom recommended by the Quantitative Imaging Biomarkers Alliance was scanned and reconstructed with and without DLR, and 15 patients with brain tumors with normal-appearing gray and white matter examined using IVIM and reconstructed with and without DLR were included in the in vivo study. The ADCs of all phantoms for DWI with and without DLR, as well as the coefficient of variation percentage (CV%), and ADCs and IVIM indexes for each participant, were evaluated based on DWI with and without DLR by means of region-of-interest measurements. For the in vitro study, using the mean ADCs for all phantoms, a t-test was adopted to compare DWI with and without DLR. For the in vivo study, a Wilcoxon signed-rank test was used to compare the CV% between the two types of DWI. In addition, the Wilcoxon signed-rank test was used to compare the ADC, true diffusion coefficient (D), pseudodiffusion coefficient (D*), and percentage of water molecules in micro perfusion within 1 voxel (f) with and without DLR; the limits of agreement of each parameter were determined through a Bland-Altman analysis.
Results: The in vitro study identified no significant differences between the ADC values for DWI with and without DLR (P > 0.05), and the CV% was significantly different for DWI with and without DLR (P < 0.05) when b values ≥250 s/mm2 were used. The in vivo study revealed that D* and f with and without DLR were significantly different (P < 0.001). The limits of agreement of the ADC, D, and D* values for DWI with and without DLR were determined as 0.00 ± 0.51 × 10-3, 0.00 ± 0.06 × 10-3, and 1.13 ± 4.04 × 10-3 mm2/s, respectively. The limits of agreement of the f values for DWI with and without DLR were determined as -0.01 ± 0.07.
Conclusion: Deep learning reconstruction for MRI has the potential to significantly improve DWI quality at higher b values. It has some effect on D* and f values in the IVIM index evaluation, but ADC and D values are less affected by DLR.
期刊介绍:
Diagnostic and Interventional Radiology (Diagn Interv Radiol) is the open access, online-only official publication of Turkish Society of Radiology. It is published bimonthly and the journal’s publication language is English.
The journal is a medium for original articles, reviews, pictorial essays, technical notes related to all fields of diagnostic and interventional radiology.