Compressed Sensing 3D T2WI Radiomics Model: Improving Diagnostic Performance in Muscle Invasion of Bladder Cancer

Overview

Journal BMC Med Imaging

Publisher Biomed Central

Specialty Radiology

Date 2024 Jun 17

PMID 38886638

Authors

Shuo Li

Zhichang Fan

Junting Guo

Ding Li

Zeke Chen

Xiaoyue Zhang

Yongfang Wang

Yan Li

Guoqiang Yang

Xiaochun Wang

Affiliations

Soon will be listed here.

Abstract

Background: Preoperative discrimination between non-muscle-invasive bladder cancer (NMIBC) and the muscle invasive bladder cancer (MIBC) is a determinant of management. The purpose of this research is to employ radiomics to evaluate the diagnostic value in determining muscle invasiveness of compressed sensing (CS) accelerated 3D T2-weighted-SPACE sequence with high resolution and short acquisition time.

Methods: This prospective study involved 108 participants who underwent preoperative 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted sequences. The cohort was divided into training and validation cohorts in a 7:3 ratio. In the training cohort, a Rad-score was constructed based on radiomic features selected by intraclass correlation coefficients, pearson correlation coefficient and least absolute shrinkage and selection operator . Multivariate logistic regression was used to develop a nomogram combined radiomics and clinical indices. In the validation cohort, the performances of the models were evaluated by ROC, calibration, and decision curves.

Results: In the validation cohort, the area under ROC curve of 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted models were 0.87(95% confidence interval (CI):0.73-1.00), 0.79(95%CI:0.63-0.96) and 0.77(95%CI:0.60-0.93), respectively. The differences in signal-to-noise ratio and contrast-to-noise ratio between 3D-CS-T2-weighted-SPACE and 3D-T2-weighted-SPACE sequences were not statistically significant(p > 0.05). While the clinical model composed of three clinical indices was 0.74(95%CI:0.55-0.94) and the radiomics-clinical nomogram model was 0.88(95%CI:0.75-1.00). The calibration curves confirmed high goodness of fit, and the decision curve also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model.

Conclusion: The radiomics model based on compressed sensing 3D T2WI sequence, which was acquired within a shorter acquisition time, showed superior diagnostic efficacy in muscle invasion of bladder cancer. Additionally, the nomogram model could enhance the diagnostic performance.

References

Almansour H, Weiland E, Kuehn B, Kannengiesser S, Gassenmaier S, Herrmann J . Accelerated Three-dimensional T2-Weighted Turbo-Spin-Echo Sequences with Inner-Volume Excitation and Iterative Denoising in the Setting of Pelvis MRI at 1.5T: Impact on Image Quality and Lesion Detection. Acad Radiol. 2022; 29(11):e248-e259. DOI: 10.1016/j.acra.2022.01.003. View

Xu X, Liu Y, Zhang X, Tian Q, Wu Y, Zhang G . Preoperative prediction of muscular invasiveness of bladder cancer with radiomic features on conventional MRI and its high-order derivative maps. Abdom Radiol (NY). 2017; 42(7):1896-1905. DOI: 10.1007/s00261-017-1079-6. View

Wu S, Zheng J, Li Y, Yu H, Shi S, Xie W . A Radiomics Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Bladder Cancer. Clin Cancer Res. 2017; 23(22):6904-6911. DOI: 10.1158/1078-0432.CCR-17-1510. View

Ueno Y, Takeuchi M, Tamada T, Sofue K, Takahashi S, Kamishima Y . Diagnostic Accuracy and Interobserver Agreement for the Vesical Imaging-Reporting and Data System for Muscle-invasive Bladder Cancer: A Multireader Validation Study. Eur Urol. 2019; 76(1):54-56. DOI: 10.1016/j.eururo.2019.03.012. View

Sakata A, Fushimi Y, Okada T, Nakajima S, Hinoda T, Speier P . Evaluation of cerebral arteriovenous shunts: a comparison of parallel imaging time-of-flight magnetic resonance angiography (TOF-MRA) and compressed sensing TOF-MRA to digital subtraction angiography. Neuroradiology. 2020; 63(6):879-887. DOI: 10.1007/s00234-020-02581-y. View

Flaig T, Spiess P, Abern M, Agarwal N, Bangs R, Boorjian S . NCCN Guidelines® Insights: Bladder Cancer, Version 2.2022. J Natl Compr Canc Netw. 2022; 20(8):866-878. DOI: 10.6004/jnccn.2022.0041. View

Shin J, Seo N, Baek S, Son N, Lim J, Kim N . MRI Radiomics Model Predicts Pathologic Complete Response of Rectal Cancer Following Chemoradiotherapy. Radiology. 2022; 303(2):351-358. DOI: 10.1148/radiol.211986. View

Zhang X, Xu X, Tian Q, Li B, Wu Y, Yang Z . Radiomics assessment of bladder cancer grade using texture features from diffusion-weighted imaging. J Magn Reson Imaging. 2017; 46(5):1281-1288. PMC: 5557707. DOI: 10.1002/jmri.25669. View

Chen Y, Zhang L, Zhou Z, Lin B, Jiang Z, Tang C . Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma. World J Gastroenterol. 2022; 28(31):4399-4416. PMC: 9453772. DOI: 10.3748/wjg.v28.i31.4399. View

10.

Li G, Li L, Li Y, Qian Z, Wu F, He Y . An MRI radiomics approach to predict survival and tumour-infiltrating macrophages in gliomas. Brain. 2022; 145(3):1151-1161. PMC: 9050568. DOI: 10.1093/brain/awab340. View

11.

Zheng J, Kong J, Wu S, Li Y, Cai J, Yu H . Development of a noninvasive tool to preoperatively evaluate the muscular invasiveness of bladder cancer using a radiomics approach. Cancer. 2019; 125(24):4388-4398. DOI: 10.1002/cncr.32490. View

12.

Chen Z, Sun B, Xue Y, Duan Q, Zheng E, He Y . Comparing compressed sensing breath-hold 3D MR cholangiopancreatography with two parallel imaging MRCP strategies in main pancreatic duct and common bile duct. Eur J Radiol. 2021; 142:109833. DOI: 10.1016/j.ejrad.2021.109833. View

13.

Panebianco V, Narumi Y, Altun E, Bochner B, Efstathiou J, Hafeez S . Multiparametric Magnetic Resonance Imaging for Bladder Cancer: Development of VI-RADS (Vesical Imaging-Reporting And Data System). Eur Urol. 2018; 74(3):294-306. PMC: 6690492. DOI: 10.1016/j.eururo.2018.04.029. View

14.

Xu S, Yao Q, Liu G, Jin D, Chen H, Xu J . Combining DWI radiomics features with transurethral resection promotes the differentiation between muscle-invasive bladder cancer and non-muscle-invasive bladder cancer. Eur Radiol. 2019; 30(3):1804-1812. DOI: 10.1007/s00330-019-06484-2. View

15.

Choi M, Lee Y, Jung S, Han D . High-resolution 3D T2-weighted SPACE sequence with compressed sensing for the prostate gland: diagnostic performance in comparison with conventional T2-weighted images. Abdom Radiol (NY). 2022; 48(3):1090-1099. DOI: 10.1007/s00261-022-03777-x. View

16.

Bathala T, Venkatesan A, Ma J, Bhosale P, Wei W, Kudchadker R . Quality comparison between three-dimensional T2-weighted SPACE and two-dimensional T2-weighted turbo spin echo magnetic resonance images for the brachytherapy planning evaluation of prostate and periprostatic anatomy. Brachytherapy. 2020; 19(4):484-490. PMC: 7368804. DOI: 10.1016/j.brachy.2020.04.001. View

17.

Antoni S, Ferlay J, Soerjomataram I, Znaor A, Jemal A, Bray F . Bladder Cancer Incidence and Mortality: A Global Overview and Recent Trends. Eur Urol. 2016; 71(1):96-108. DOI: 10.1016/j.eururo.2016.06.010. View

18.

Zhang W, Zhang W, Li X, Cao X, Yang G, Zhang H . Predicting Tumor Perineural Invasion Status in High-Grade Prostate Cancer Based on a Clinical-Radiomics Model Incorporating T2-Weighted and Diffusion-Weighted Magnetic Resonance Images. Cancers (Basel). 2023; 15(1). PMC: 9817925. DOI: 10.3390/cancers15010086. View

19.

Patel V, Oh W, Galsky M . Treatment of muscle-invasive and advanced bladder cancer in 2020. CA Cancer J Clin. 2020; 70(5):404-423. DOI: 10.3322/caac.21631. View

20.

Hecht E, Yitta S, Lim R, Fitzgerald E, Storey P, Babb J . Preliminary clinical experience at 3 T with a 3D T2-weighted sequence compared with multiplanar 2D for evaluation of the female pelvis. AJR Am J Roentgenol. 2011; 197(2):W346-52. DOI: 10.2214/AJR.10.5914. View