What’s new in Genitourinary Imaging – July 2020

Prostate Microstructure in Prostate Cancer Using 3-T MRI With Diffusion-Relaxation Correlation Spectrum Imaging: Validation With Whole-Mount Digital Histopathology

Zhang Z, Wu HH, Priester A, et al. Prostate Microstructure in Prostate Cancer Using 3-T MRI with Diffusion-Relaxation Correlation Spectrum Imaging: Validation with Whole-Mount Digital Histopathology. Radiology. 2020;192330.

https://doi.org/10.1148/radiol.2020192330

In this prospective study by Zhang Z. et al., the authors sought to validate the use of novel diffusion-relaxation correlation spectroscopic imaging (DR-CSI) in the characterization of prostatic tissue compartments in patients with prostate cancer. DR-CSI has been recently proposed for the identification of spatially overlapping tissue compartments that have been previously inaccessible to traditional MR methods. The authors evaluated 13 patients with prostate cancer who underwent robotic-assisted radical prostatectomy over a 7-month period. The prostate specimens were imaged using 3T MR imaging with DR-CSI then sliced to create whole-mount digital histopathology slides. Three DR-CSI spectral signal components (f_A, f_B, f_C) were compared with tissue fractions quantified in prostate cancer and benign tissue regions (f_epithelium, f_stroma, f_lumen) using Spearman correlation coefficients and two-sided ttests. The three DR-CSI spectral peaks (f_A, f_B, f_C) were consistently identified and strongly correlated with the three tissue fractions (f_epithelium, f_stroma, f_lumen) with correlation coefficients of 0.74 (95% CI: 0.62, 0.83), 0.80 (95% CI: 0.66, 0.89), and 0.67 (95% CI: 0.51, 0.81), respectively. Using two-sided t tests, prostate cancer, when compared to benign tissue regions, was found to have increased f_A, decreased f_C, increased f_epithelium, and decreased f_lumen. The results from this study validates ex-vivo DR-CSI in the characterization of microstructural tissue compartments in prostate cancer.

Differential diagnosis of <3 cm renal tumors by ultrasonography: a rapid, quantitative, elastography self-corrected contrast-enhanced ultrasound imaging mode beyond screening

Sun D, Lu Q, Wei C, Li Y, Zheng Y, Hu B. Differential diagnosis of <3 cm renal tumors by ultrasonography: a rapid, quantitative, elastography self-corrected contrast-enhanced ultrasound imaging mode beyond screening. Br J Radiol. 2020;20190974.

https://doi.org/10.1259/bjr.20190974

In this IRB-approved retrospective study by Sun D. et al., the authors proposed the combined use of contrast-enhanced US (CEUS) and ultrasound elastography using the  acoustic radiation force impulse (ARFI) elastography technique for the early diagnosis of small renal tumors less than 3 cm. ARFI has been increasingly utilized in the evaluation of the mechanical property (relative hardness and elasticity) of focal lesions in the kidney, breast, prostate, thyroid gland and liver. 35 patients with 37 renal tumors less than 3 cm were studied over a 14-month period using both CEUS and ARFI in the same setting. CEUS was scored based on peak intensity,  time-to-peak and time-to-wash-in compared to the renal cortex, homogeneity and the presence versus absence of a pseudo-capsule. CEUS and ARFI examinations were reviewed by different radiologists who were blinded to the results of the other examination. The diagnostic accuracy using CEUS was 86.5% and 5/37 cases (13.5%) were misdiagnosed. With the combination of CEUS and ARFI, the diagnostic accuracy improved to 94.6% by correcting the diagnosis in 3 cases. The authors acknowledged that the results of this study will require validation in a larger study population with evaluation of the inter-observer and intra-observer variability of CEUS and ultrasound elastography.

Update on Renal Neoplasms: Clinicopathologic-Radiologic Correlation With Case-Based Examples

Valencia-Guerrero A, O’Shea A, Cornejo KM, Wu CL. Update on Renal Neoplasms: Clinicopathologic-Radiologic Correlation With Case-Based Examples. AJR Am J Roentgenol. 2020;214(6):1220-1228.

https://doi.org/10.2214/AJR.20.22816

This review article provides a brief overview of the clinicopathologic and radiologic correlation of 12 renal neoplasms, encompassing the conventional subtypes of renal cell carcinoma and a few of the newly recognized subtypes from the 2016 World Health Organization classification of renal tumors. In addition, the authors briefly discuss infrequent neoplasms that may enter the differential diagnosis of a renal mass, with corresponding radiologic and gross images and histologic findings of case-based examples.

Accuracy of ADC Ratio in Discriminating True and False Positives in Multiparametric Prostatic MRI

Falaschi Z, Valenti M, Lanzo G, et al. Accuracy of ADC ratio in discriminating true and false positives in multiparametric prostatic MRI. Eur J Radiol. 2020;128:109024.

https://doi.org/10.1016/j.ejrad.2020.109024

Multiparametric MRI (mpMRI) is the gold standard imaging technique for the evaluation of malignant lesions in the prostate gland. However, given its relatively low PPV and specificity, it can lead to higher rate of FP results and unwarranted prostatic biopsies. For the acquisition, interpretation, and reporting of prostatic mpMRI, most centers currently use the Prostate Imaging Reporting and Data System (PI-RADS V2). The authors of this study propose the use of ADC ratio (ratio between the ADC value of a possibly malignant prostatic nodule and that of the corresponding, apparently, benign gland parenchyma) with PI-RADS V2 to improve the detection of prostate cancer on mpMRI.

In this retrospective study, 73 male patients with histologically confirmed prostate cancer using 12-core biopsy with 98 prostatic lesions with PI-RADS category of 3 or more on mpMRI were included. The ADC ratios were calculated for the previously reported malignant lesions and the apparently benign parenchyma. A threshold of 0.6 was used for the ADC ratio, where lesions with an ADC ratio > 0.6 were considered benign and lesions with an ADC ratio < 0.6 were considered malignant.

With conventional interpretation using PI-RADS, the PPV was 38.7% with a sensitivity of 84% with increased to 51.6% and 96%, respectively, with the addition of the ADC ratio.

Comparison of Likert and PI-RADS version 2 MRI scoring systems for the detection of clinically significant prostate cancer

Zawaideh JP, Sala E, Pantelidou M, et al. Comparison of Likert and PI-RADS version 2 MRI scoring systems for the detection of clinically significant prostate cancer [published online ahead of print, 2020 Jun 11]. Br J Radiol. 2020;20200298.

https://doi.org/10.1259/bjr.20200298

In this retrospective study by Zawaideh J.P. et al., the authors sought to compare the diagnostic performance of the two widely used scoring systems for prostatic mpMRI interpretation and reporting, the Prostate Imaging Reporting and Data System (PI-RADS V2) and the Likert-based scoring system. 199 male patients who underwent prostatic mpMRI with a threshold score of ≥3 were included. Overall, the Likert system had a moderate but non-significant higher specificity than PI-RADS (0.77 vs 0.66; p = 0.078) but with unchanged sensitivity (0.94) leading to a significantly higher AUC (0.92 vs 0.87, p = 0.002) and higher PPV (0.66 vs 0.58). The results reported in this study are consistent with those previously reported using both PI-RADS V1 and V2 showing similar detection rates for clinically significant prostate cancer, but with an improvement in diagnostic accuracy for the Likert-based system.

Staging of bladder cancer with multiparametric MRI

Juri H, Narumi Y, Panebianco V, Osuga K. Staging of bladder cancer with multiparametric MRI. Br J Radiol. 2020;20200116.

https://doi.org/10.1259/bjr.20200116

CT and MRI are the modalities of choice for staging of bladder cancer. Although CT is the first choice for N and M staging, the accuracy of T staging for the distinction of non-muscle invasive bladder cancer and muscle invasive bladder cancer. Multiparametric MRI has recently become one of the most important modalities of choice for the T staging of bladder cancer given its inherent tissue characterization capabilities. In this review, the authors describe the method, interpretation and clinical timing of mpMRI examinations, the staging method of mpMRI using VI-RADS, and clinical validation studies of mpMRI based on VI-RADS. The 5-point scoring system of the probability of bladder cancer invasion based on VI-RADS categories is discussed, where muscle invasion ranges from highly unlikely for VI-RADS category 1, equivocal for VI-RADS category 3 to very likely for VI-RADS category 5.

Ultra-High-b-Value Kurtosis Imaging for Noninvasive Tissue Characterization of Ovarian Lesions

Mokry T, Mlynarska-Bujny A, Kuder TA, et al. Ultra-High-b-Value Kurtosis Imaging for Noninvasive Tissue Characterization of Ovarian Lesions. Radiology. 2020;191700.

https://doi.org/10.1148/radiol.2020191700

In this prospective cohort study by Mokry T. et al., the authors propose the utilization of quantitative texture analysis using diffusion-weighted MRI protocols for the discrimination of benign versus malignant ovarian lesions. 58 women with 79 sonographically indeterminate ovarian lesions over a duration of 2 years were included. The ovarian lesions were manually segmented on a single transverse slice on DWI. ADC calculation and kurtosis (a measure of distribution) fitting were performed. Area under the ROC for ADC, kurtosis-derived ADC (D_app), and apparent kurtosis coefficient (K_app) between malignant and benign lesions were assessed by using a logistic model.

ADC and D_app were lower and K_app was higher in malignant lesions: median ADC, D_app, and K_app were 0.74 µm2/msec , 0.98 µm2/msec, and 1.01 for malignant lesions, and 1.13 µm2/msec, 1.45 µm2/msec, and 0.65 for benign lesions (P values of .01, .02, < .001, respectively). AUC for K_app of 0.85 (95% CI: 0.77, 0.94) was higher than was AUC from ADC of 0.78 (95% CI: 0.67, 0.89; P = .047).

The authors concluded that DWI using quantitative kurtosis variables is superior to ADC values in the differentiation between benign and malignant ovarian lesions.

Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome: Spectrum of imaging findings

Paschall AK, Nikpanah M, Farhadi F, et al. Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome: Spectrum of imaging findings. Clin Imaging. 2020;68:14-19.

https://doi.org/10.1016/j.clinimag.2020.06.010

Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) syndrome is caused by an autosomal dominant germline mutation in the fumarate hydratase (FH) gene (1q42.2) causing an increased risk of developing benign renal cysts and early-onset papillary type II renal cell carcinoma (RCC). Benign cutaneous and uterine leiomyomas are frequent manifestations in patients with HLRCC.

In this retrospective study by Paschall A.K. et al., the authors describe the MRI and CT imaging characteristics of 39 pathologically confirmed lesions in 20 patients with HLRCC syndrome. The examined lesions had a mean diameter of 5.06 ± 3.80 cm and an estimated annual growth rate of 1.06 cm per year. 50% of lesions demonstrated nodularity, 65% were mostly T2-hyperintense, 83% demonstrated restricted diffusion in solid portions of the lesions, and 65% had well-defined margins. 76% of patients demonstrated extra-renal manifestations, 53% lymphadenopathy, and 43% distant metastasis.