Objective: The aim of this study was to demonstrate the feasibility of the recently introduced Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumours (VERDICT) framework for imaging prostate cancer with diffusion-weighted magnetic resonance imaging (DW-MRI) within a clinical setting.
Materials And Methods: The VERDICT framework is a noninvasive microstructure imaging technique that combines an in-depth diffusion MRI acquisition with a mathematical model to estimate and map microstructural tissue parameters such as cell size and density and vascular perfusion. In total, 8 patients underwent 3-T MRI using 9 different b values (100-3000 s/mm). All patients were imaged before undergoing biopsy. Experiments with VERDICT analyzed DW-MRI data from patients with histologically confirmed prostate cancer in areas of cancerous and benign peripheral zone tissue. For comparison, we also fitted commonly used diffusion models such as the apparent diffusion coefficient (ADC), the intravoxel incoherent motion (IVIM), and the kurtosis model. We also investigated correlations of ADC and kurtosis with VERDICT parameters to gain some biophysical insight into the various parameter values.
Results: Eight patients had prostate cancer in the peripheral zone, with Gleason score 3 + 3 (n = 1), 3 + 4 (n = 6), and 4 + 3 (n = 1). The VERDICT model identified a significant increase in the intracellular and vascular volume fraction estimates in cancerous compared with benign peripheral zone, as well as a significant decrease in the volume of the extracellular-extravascular space (EES) (P = 0.05). This is in agreement with manual segmentation of the biopsies for prostate tissue component analysis, which found proliferation of epithelium, loss of surrounding stroma, and an increase in vasculature. The standard ADC and kurtosis parameters were also significantly different (P = 0.05) between tissue types. There was no significant difference in any of the IVIM parameters (P = 0.11 to 0.29). The VERDICT parametric maps from voxel-by-voxel fitting clearly differentiated cancer from benign regions. Kurtosis and ADC parameters correlated most strongly with VERDICT's intracellular volume fraction but also moderately with the EES and vascular fractions.
Conclusions: The VERDICT model distinguished tumor from benign areas, while revealing differences in microstructure descriptors such as cellular, vascular, and EES fractions. The parameters of ADC and kurtosis models also discriminated between cancer and benign regions. However, VERDICT provides more specific information that disentangles the various microstructural features underlying the changes in ADC and kurtosis. These results highlight the clinical potential of the VERDICT framework and motivate the construction of a shorter, clinically viable imaging protocol to enable larger trials leading to widespread translation of the method.
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http://dx.doi.org/10.1097/RLI.0000000000000115 | DOI Listing |
Brain Behav
January 2025
Department of Radiology, Liuzhou Worker's Hospital, Guangxi, China.
Background: Adult glioblastomas (GBMs) are associated with high recurrence and mortality. Personalized treatment based on molecular markers may help improve the prognosis. We aimed to evaluate whether apparent diffusion coefficient (ADC) histogram analysis can better predict MGMT and TERT molecular characteristics and to determine the prognostic relevance of genetic profile in patients with GBM.
View Article and Find Full Text PDFBMC Med Imaging
December 2024
Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Background: Diffusion-weighted imaging (DWI) can be used for quantitative tumor assessment. DWI with different models may show different aspects of tissue characteristics.
Objective: To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, stretched exponential magnetic resonance diffusion weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in differentiating benign from malignant solitary pulmonary lesions (SPLs).
Insights Imaging
December 2024
Department of MR, The First Affiliated Hospital, Xinxiang Medical University, Weihui, China.
Background: To investigate the efficacy of three-compartment restriction spectrum imaging (RSI), diffusion kurtosis imaging (DKI), and diffusion-weighted imaging (DWI) in the assessment of lymph node metastases (LNM) in rectal cancer.
Methods: A total of 77 patients with rectal cancer who underwent pelvic MRI were enrolled. RSI-derived parameters (f, f, and f), DKI-derived parameters (D and K), and the DWI-derived parameter (ADC) were calculated and compared using a Mann-Whitney U test or independent samples t-test.
Cancer Cell Int
December 2024
Department of Radiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital/Center, No. 519 Kunzhou Road, Xishan District, Kunming, Yunnan, 650118, P.R. China.
Objective: This study aimed to compare the performance of amide proton transfer-weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in differentiating benign from malignant breast lesions, evaluate molecular subtypes of breast cancer, and determine the diagnostic efficacy of the quantitative magnetic resonance imaging (qMRI) parameters in differentiating benign from malignant breast diseases.
Methods: The study included 168 women who underwent breast APTWI and DKI at Yunnan Cancer Hospital between December 2022 and July 2023. The APT signal intensity (SI), apparent kurtosis coefficient (Kapp), non-Gaussian diffusion coefficient (Dapp), and apparent diffusion coefficient (ADC) values were measured before surgery.
Int Urol Nephrol
December 2024
Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, No. 24 Fukang Road, Nankai District, Tianjin, 300192, China.
Objective: To investigate the value of multiparametric magnetic resonance imaging (MRI) as a non-invasive method to predict the aggressiveness of renal cell carcinoma (RCC) by developing a convolutional neural network (CNN) model and fusing it with clinical characteristics.
Methods: Multiparametric abdominal MRI was performed on 47 pathologically confirmed RCC patients between 2019 and 2023. Preoperative MRI was performed on all patients to assess their clinical characteristics.
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