Comparison of reduced field-of-view DWI and full field-of view DWI for the differentiation between non-muscle invasive bladder cancer and muscle invasive bladder cancer using VI-RADS

Juri, Hiroshi; Higashiyama, Akira; Yamamoto, Kazuhisa; Narumi, Yasuo; Azuma, Haruhito; Yamamoto, Kazuhide; Osuga, Keigo

doi:10.1371/journal.pone.0271470

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Compared to SS DWI, our findings have established the superior subjective image quality of rFOV STA DWI, which was consistent with previous studies [ 13 , 25 ]. In addition, our study further compared the SNR and CNR.…”

Section: Discussionsupporting

confidence: 93%

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Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion

Zhang,

Xu,

Wang

et al. 2024

Insights Imaging

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Objectives To investigate whether reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with deep learning reconstruction (DLR) can improve the accuracy of evaluating muscle invasion using VI-RADS. Methods Eighty-six bladder cancer participants who were evaluated by conventional full field-of-view (fFOV) DWI, standard rFOV (rFOVSTA) DWI, and fast rFOV with DLR (rFOVDLR) DWI were included in this prospective study. Tumors were categorized according to the vesical imaging reporting and data system (VI-RADS). Qualitative image quality scoring, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC value were evaluated. Friedman test with post hoc test revealed the difference across the three DWIs. Receiver operating characteristic analysis was performed to calculate the areas under the curve (AUCs). Results The AUC of the rFOVSTA DWI and rFOVDLR DWI were higher than that of fFOV DWI. rFOVDLR DWI reduced the acquisition time from 5:02 min to 3:25 min, and showed higher scores in overall image quality with higher CNR and SNR, compared to rFOVSTA DWI (p < 0.05). The mean ADC of all cases of rFOVSTA DWI and rFOVDLR DWI was significantly lower than that of fFOV DWI (all p < 0.05). There was no difference in mean ADC value and the AUC for evaluating muscle invasion between rFOVSTA DWI and rFOVDLR DWI (p > 0.05). Conclusions rFOV DWI with DLR can improve the diagnostic accuracy of fFOV DWI for evaluating muscle invasion. Applying DLR to rFOV DWI reduced the acquisition time and improved overall image quality while maintaining ADC value and diagnostic accuracy. Critical relevance statement The diagnostic performance and image quality of full field-of-view DWI, reduced field-of-view (rFOV) DWI with and without DLR were compared. DLR would benefit the wide clinical application of rFOV DWI by reducing the acquisition time and improving the image quality. Key Points Deep learning reconstruction (DLR) can reduce scan time and improve image quality. Reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with DLR showed better diagnostic performances than full field-of-view DWI. There was no difference of diagnostic accuracy between rFOV DWI with DLR and standard rFOV DWI. Graphical Abstract

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Section: Discussionsupporting

confidence: 93%

“…However, compared with full FOV DWI, rFOV DWI had lower signal-to-noise ratio (SNR) because of smaller field of view. Moreover, it is worth noting that the use of rFOV DWI may result in longer scan time compared to conventional DWI [ 10 , 13 , 15 ], which poses a challenge to its routine clinical application.…”

Section: Introductionmentioning

confidence: 99%

Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion

Zhang,

Xu,

Wang

et al. 2024

Insights Imaging

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Comparative analysis of image quality and diagnostic performance among SS-EPI, MS-EPI, and rFOV DWI in bladder cancer

Takeuchi,

Higaki,

Kojima

et al. 2024

Jpn J Radiol

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Purpose To compare image quality and diagnostic performance among SS-EPI diffusion weighted imaging (DWI), multi-shot (MS) EPI DWI, and reduced field-of-view (rFOV) DWI for muscle-invasive bladder cancer (MIBC). Materials and methods This retrospective study included 73 patients with bladder cancer who underwent multiparametric MRI in our referral center between August 2020 and February 2023. Qualitative image assessment was performed in 73; and quantitative assessment was performed in 66 patients with maximum lesion diameter > 10 mm. The diagnostic performance of the imaging finding of muscle invasion was evaluated in 47 patients with pathological confirmation of MIBC. T2-weighted imaging, SS-EPI DWI, MS-EPI DWI, rFOV DWI, and dynamic contrast-enhanced imaging were acquired with 3 T-MRI. Qualitative image assessment was performed by three readers who rated anatomical distortion, clarity of bladder wall, and lesion conspicuity using a four-point scale. Quantitative assessment included calculation of SNR and CNR, and grading of the presence of muscle layer invasion according to the VI-RADS diagnostic criteria. Wilcoxon matched pairs signed rank test was used to compare qualitative and quantitative image quality. McNemar test and receiver-operating characteristic analysis were used to compare diagnostic performance. Results Anatomical distortion was less in MS-EPI DWI, rFOV DWI, and SS-EPI DWI, in that order with significant difference. Clarity of bladder wall was greater for MS-EPI DWI, SS-EPI DWI, and rFOV DWI, in that order. There were significant differences between any two combinations of the three DWI types, except between SS-EPI DWI and MS-EPI in Reader 1. Lesion conspicuity, diagnostic performance, SNR and CNR were not significantly different among the three DWI types. Conclusions Among the three DWI sequences evaluated, MS-EPI DWI showed the least anatomical distortion and superior bladder wall delineation but no improvement in diagnostic performance for MIBC. MS-EPI DWI may be considered for additional imaging if SS-EPI DWI is of poor quality.

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Current Status of Magnetic Resonance Imaging Use in Bladder Cancer

Ahn

2024

Invest Radiol

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Bladder cancer (BC) is a significant global health concern, with over 500,000 new cases and 200,000 deaths annually, emphasizing the need for accurate staging and effective management. Traditional diagnostic techniques, such as cystoscopy and transurethral resection, are fundamental but have limitations in accurately assessing the depth of invasion. These limitations include the possibility of understaging and procedural variability, which can significantly impact treatment decisions. This review focuses on the role of multiparametric magnetic resonance imaging (mpMRI) in the diagnosis and staging of BC, particularly emphasizing the Vesical Imaging-Reporting and Data System (VI-RADS) framework. By enhancing interpretive consistency and diagnostic accuracy, mpMRI and VI-RADS offer detailed visualization of tumor characteristics and depth of invasion, while reducing the need for more invasive traditional methods. These advancements not only improve staging accuracy but also enhance treatment planning, underscoring the importance of advanced imaging in evolving BC management and positively influencing patient outcomes.

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Comparison of reduced field-of-view DWI and full field-of view DWI for the differentiation between non-muscle invasive bladder cancer and muscle invasive bladder cancer using VI-RADS

Cited by 3 publications

References 18 publications

Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion

Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion

Comparative analysis of image quality and diagnostic performance among SS-EPI, MS-EPI, and rFOV DWI in bladder cancer

Current Status of Magnetic Resonance Imaging Use in Bladder Cancer

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