Comparison of the Pharmacokinetics of Gadolinium-Based and Iron Oxide-Based Contrast Agents inside the Lymphatic Structure using Magnetic Resonance Lymphangiography.

PURPOSE: Gadolinium (Gd)-based contrast agents are primarily used for contrast-enhanced magnetic resonance lymphangiography (MRL). However, overcoming venous contamination issues remains challenging. This study aims to assess the MRL efficacy of the newly developed iron-based contrast agent (INV-001) that is specially designed to mitigate venous contamination issues. The study further explores the optimal dosage, including both injection volume and concentration, required to achieve successful visualization of the popliteal lymph nodes and surrounding lymphatic vessels. PROCEDURES: All animals utilized in this study were male Sprague-Dawley (SD) rats weighing between 250 and 300 g. The contrast agents prepared were injected intradermally in the fourth phalanx of both hind limbs using a 30-gauge syringe in SD rats. MRL was performed every 16 min on a coronal 3D time-of-flight sequence with saturation bands using a 9.4-T animal machine. RESULTS: Contrary to Gd-DOTA, which exhibited venous contamination in most animals irrespective of injection dosages and conditions, INV-001 showed no venous contamination. For Gd-DOTA, the popliteal lymph nodes and lymphatic vessels reached peak enhancement 16 min after injection from the injection site and then rapidly washed out. However, with INV-001, they reached peak enhancement between 16 and 32 min after injection, with prolonged visualization of the popliteal lymph node and lymphatic vessels. INV-001 at 0.45 µmol (15 mM, 30 µL) and 0.75 µmol (15 mM, 50 µL) achieved high scores for qualitative image analysis, providing good visualization of the popliteal lymph nodes and lymphatic vessels without issues of venous contamination, interstitial space enhancement, or lymph node enlargement. CONCLUSION: In MRL, INV-001, a novel T1 contrast agent based on iron, enables prolonged enhancement of popliteal lymph nodes and lymphatic vessels without venous contamination.

Focal nodular enhancement on DCE MRI of the prostatectomy bed: radiologic-pathologic correlations and prognostic value.

OBJECTIVES: To determine the concordance of dynamic contrast-enhanced (DCE) imaging findings with clinico-pathologic characteristics and their prognostic impact for predicting biochemical recurrence (BCR) in patients who underwent radical prostatectomy (RP) for prostate cancer. METHODS: This retrospective study included patients who underwent MRI within 1 year after RP between November 2019 and October 2020. DCE findings and their concordance with the presence and location of positive surgical margin (PSM) were assessed using RP specimens. Kaplan-Meier and logistic regression analyses were used to evaluate the prognostic impact of DCE findings for BCR. RESULTS: Among the 272 men (mean age ± standard deviation, 66.6 ± 7.4 years), focal nodular enhancement was more frequently observed in those with PSM compared to those with negative margin (85.4% versus 14.6%; p < 0.001). The sites of focal nodular enhancement were 72.9% (35/48) concordant with the PSM locations. Focal nodular enhancement was associated with a higher Gleason score, higher preoperative PSA (≥ 10 ng/mL), higher Gleason grade at the surgical margin, and non-limited margin involvement (p = 0.002, 0.006, 0.032, and 0.001, respectively). In patients without BCR at the time of MRI, focal nodular enhancement was associated with a shorter time to BCR (p < 0.001) and a significant factor predicting 1-year BCR in both univariate (odds ratio = 8.4 [95% CI: 2.5-28.3]; p = 0.001) and multivariate (odds ratio = 5.49 [1.56-19.3]; p = 0.008) analyses. CONCLUSIONS: Focal nodular enhancement on post-prostatectomy MRI was associated with adverse clinico-pathologic characteristics of high risk for recurrence and can be a predictor for 1-year BCR in patients undergoing RP. KEY POINTS: • Focal nodular enhancement (PI-RR DCE score ≥ 4) was 72.9% (35/48) concordant with the site of positive resection margin by radiologic-histologic correlation. • Focal nodular enhancement (PI-RR DCE score ≥ 4) was associated with higher Gleason score ( ≥ 8), preoperative PSA ( > 10 ng/mL), and Gleason grade 4 or 5 at the surgical margin and non-limited margin involvement (p ≤ 0.032). • In patients without BCR at the time of MRI, focal nodular enhancement was a significant factor predicting 1-year BCR (odds ratio = 5.49; 95% CI: 1.56-19.3; p = 0.008).

Preclinical Long-term Magnetic Resonance Imaging Study of Silymarin Liver-protective Effects.

Background and Aims: Efficacy evaluations with preclinical magnetic resonance imaging (MRI) are uncommon, but MRI in the preclinical phase of drug development provides information that is useful for longitudinal monitoring. The study aim was to monitor the protective effectiveness of silymarin with multiparameter MRI and biomarkers in a thioacetamide (TAA)-induced model of liver injury in rats. Correlation analysis was conducted to assess compare the monitoring of liver function by MRI and biomarkers. Methods: TAA was injected three times a week for 8 weeks to generate a disease model (TAA group). In the TAA and silymarin-treated (TAA-SY) groups, silymarin was administered three times weekly from week 4. MR images were acquired at 0, 2, 4, 6, and 8 weeks in the control, TAA, and TAA-SY groups. Results: The area under the curve to maximum time (AUCtmax) and T2* values of the TAA group decreased over the study period, but the serological markers of liver abnormality increased significantly more than those in the control group. In the TAA-SY group, MRI and serological biomarkers indicated attenuation of liver function as in the TAA group. However, pattern changes were observed from week 6 to comparable levels in the control group with silymarin treatment. Negative correlations between either AUCtmax or T2* values and the serological biomarkers were observed. Conclusions: Silymarin had hepatoprotective effects on TAA-induced liver injury and demonstrated the usefulness of multiparametric MRI to evaluate efficacy in preclinical studies of liver drug development.

Hyperoxia-Induced ΔR1: MRI Biomarker of Histological Infarction in Acute Cerebral Stroke.

OBJECTIVE: To evaluate whether hyperoxia-induced ΔR1 (hyperO2ΔR1) can accurately identify histological infarction in an acute cerebral stroke model. MATERIALS AND METHODS: In 18 rats, MRI parameters, including hyperO2ΔR1, apparent diffusion coefficient (ADC), cerebral blood flow and volume, and 18F-fluorodeoxyglucose uptake on PET were measured 2.5, 4.5, and 6.5 hours after a 60-minutes occlusion of the right middle cerebral artery. Histological examination of the brain was performed immediately following the imaging studies. MRI and PET images were co-registered with digitized histological images. The ipsilateral hemisphere was divided into histological infarct (histological cell death), non-infarct ischemic (no cell death but ADC decrease), and non-ischemic (no cell death or ADC decrease) areas for comparisons of imaging parameters. The levels of hyperO2ΔR1 and ADC were measured voxel-wise from the infarct core to the non-ischemic region. The correlation between areas of hyperO2ΔR1-derived infarction and histological cell death was evaluated. RESULTS: HyperO2ΔR1 increased only in the infarct area (p ≤ 0.046) compared to the other areas. ADC decreased stepwise from non-ischemic to infarct areas (p = 0.002 at all time points). The other parameters did not show consistent differences among the three areas across the three time points. HyperO2ΔR1 sharply declined from the core to the border of the infarct areas, whereas there was no change within the non-infarct areas. A hyperO2ΔR1 value of 0.04 s-1 was considered the criterion to identify histological infarction. ADC increased gradually from the infarct core to the periphery, without a pronounced difference at the border between the infarct and non-infarct areas. Areas of hyperO2ΔR1 higher than 0.04 s-1 on MRI were strongly positively correlated with histological cell death (r = 0.862; p < 0.001). CONCLUSION: HyperO2ΔR1 may be used as an accurate and early (2.5 hours after onset) indicator of histological infarction in acute stroke.

Fast T2-Weighted Imaging With Deep Learning-Based Reconstruction: Evaluation of Image Quality and Diagnostic Performance in Patients Undergoing Radical Prostatectomy.

BACKGROUND: Deep learning-based reconstruction (DLR) can potentially improve image quality by reduction of noise, thereby enabling fast acquisition of magnetic resonance imaging (MRI). However, a systematic evaluation of image quality and diagnostic performance of MRI using short acquisition time with DLR has rarely been investigated in men with prostate cancer. PURPOSE: To assess the image quality and diagnostic performance of MRI using short acquisition time with DLR for the evaluation of extraprostatic extension (EPE). STUDY TYPE: Retrospective. POPULATION: One hundred and nine men. FIELD STRENGTH/SEQUENCE: 3 T; turbo spin echo T2-weighted images (T2WI), echo-planar diffusion-weighted, and spoiled gradient echo dynamic contrast-enhanced images. ASSESSMENT: To compare image quality, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and subjective analysis using Likert scales on three T2WIs (MRI using conventional acquisition time, MRI using short acquisition time [fast MRI], and fast MRI with DLR) were performed. The diagnostic performance for EPE was evaluated by three independent readers. STATISTICAL TESTS: SNR, CNR, and image quality scores across the three imaging protocols were compared using Friedman tests. The diagnostic performance for EPE was assessed using the area under receiver operating characteristic curves (AUCs). P < 0.05 was considered statistically significant. RESULTS: Fast MRI with DLR demonstrated significantly higher SNR (mean ± SD, 14.7 ± 6.8 vs. 8.8 ± 4.9) and CNR (mean ± SD, 6.5 ± 6.3 vs. 3.4 ± 3.6) values and higher image quality scores (median, 4.0 vs. 3.0 for three readers) than fast MRI. The AUCs for EPE were significantly higher with the use of DLR (0.86 vs. 0.75 for reader 2 and 0.82 vs. 0.73 for reader 3) compared with fast MRI, whereas differences were not significant for reader 1 (0.81 vs. 0.74; P = 0.09). DATA CONCLUSION: DLR may be useful in reducing the acquisition time of prostate MRI without compromising image quality or diagnostic performance. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

Bosniak Classification of Cystic Renal Masses Version 2019: Comparison With Version 2005 for Class Distribution, Diagnostic Performance, and Interreader Agreement Using CT and MRI.

BACKGROUND. The Bosniak classification system for cystic renal masses (CRMs) was updated in 2019, requiring further investigation. OBJECTIVE. The purpose of this study was to compare versions 2005 and 2019 of the Bosniak classification system in terms of class distribution, diagnostic performance, interreader agreement, and intermodality agreement between CT and MRI. METHODS. This retrospective study included 100 patients (mean age, 52.4 ± 11.6 years; 68 men, 32 women) with 104 CRMs (74 malignant) who underwent CT, MRI, and resection between 2010 and 2019. Two radiologists independently evaluated CRMs in separate sessions for each combination of version and modality and assigned a Bosniak class. Diagnostic performance was compared using McNemar tests. Interreader and intermodality agreement were analyzed using weighted kappa coefficients. RESULTS. Across readers and modalities, the proportion of class IIF CRMs was higher for version 2019 than version 2005 (reader 1: 28.8-30.8% vs 6.7-12.5%; reader 2: 26.0-28.8% vs 8.7-19.2%), although 95% CIs overlapped for reader 2 on CT. The proportion of class III CRMs was lower for version 2019 than version 2005 (reader 1: 33.7-35.6% vs 49.0-51.9%; reader 2: 31.7-40.4% vs 37.5-52.9%), although 95% CIs overlapped for all comparisons. Version 2019 showed lower sensitivity for malignancy than version 2005 across readers and modalities (all p < .05); for example, using CT, sensitivity was 75.7% for both readers with version 2019 versus 85.1-87.8% with version 2005. However, version 2019 showed higher specificity than version 2005, which was significant (all p < .05) for reader 1. For example, using CT, specificity was 73.3% (reader 1) and 70.0% (reader 2) with version 2019 versus 50.0% (reader 1) and 56.7% (reader 2) with version 2005. Diagnostic accuracy was not different between versions (version 2005: 76.9-85.6%; version 2019: 74.0-78.8%). Interreader and intermodality agreement were substantial for version 2005 (κ = 0.676-0.782 and 0.711-0.723, respectively) and version 2019 (κ = 0.756-0.804 and 0.704-0.781, respectively). CONCLUSION. Use of version 2019 versus version 2005 of the Bosniak classification system results in a shift in CRM assignment from class III to class IIF. Version 2019 results in lower sensitivity, higher specificity, and similar accuracy versus version 2005. Interreader and intermodality agreement are similar between versions. CLINICAL IMPACT. Version 2019 facilitates recommending imaging surveillance for more CRMs.

Preoperative Assessment of Renal Sinus Invasion by Renal Cell Carcinoma according to Tumor Complexity and Imaging Features in Patients Undergoing Radical Nephrectomy.

OBJECTIVE: To identify the association between renal tumor complexity and pathologic renal sinus invasion (RSI) and evaluate the usefulness of computed tomography tumor features for predicting RSI in patients with renal cell carcinoma (RCC). MATERIALS AND METHODS: This retrospective study included 276 consecutive patients who underwent radical nephrectomy for RCC with a size of ≤ 7 cm between January 2014 and October 2017. Tumor complexity and anatomical renal sinus involvement were evaluated using two standardized scoring systems: the radius (R), exophytic or endophytic (E), nearness to collecting system or sinus (N), anterior or posterior (A), and location relative to polar lines (RENAL) nephrometry and preoperative aspects and dimensions used for anatomical classification (PADUA) system. CT-based tumor features, including shape, enhancement pattern, margin at the interface of the renal sinus (smooth vs. non-smooth), and finger-like projection of the mass, were also assessed by two independent radiologists. Univariable and multivariable logistic regression analyses were performed to identify significant predictors of RSI. The positive predictive value, negative predictive value (NPV), accuracy of anatomical renal sinus involvement, and tumor features were evaluated. RESULTS: Eighty-one of 276 patients (29.3%) demonstrated RSI. Among highly complex tumors (RENAL or PADUA score ≥ 10), the frequencies of RSI were 42.4% (39/92) and 38.0% (71/187) using RENAL and PADUA scores, respectively. Multivariable analysis showed that a non-smooth margin and the presence of a finger-like projection were significant predictors of RSI. Anatomical renal sinus involvement showed high NPVs (91.7% and 95.2%) but low accuracy (40.2% and 43.1%) for RSI, whereas the presence of a non-smooth margin or finger-like projection demonstrated comparably high NPVs (90.0% and 91.3% for both readers) and improved accuracy (67.0% and 73.9%, respectively). CONCLUSION: A non-smooth margin or the presence of a finger-like projection can be used as a preoperative CT-based tumor feature for predicting RSI in patients with RCC.

Magnetic Resonance Imaging for Drug Development.

Given the merit of high-resolution cross-sectional imaging, magnetic resonance imaging (MRI) has been utilized in many preclinical and clinical research fields. In addition to T2-weighted imaging for assessing anatomic changes by disease and therapeutic agents, diffusion-weighted imaging, dynamic contrast-enhanced MRI, and MR spectroscopy can provide disease- and drug-specific functional information in both in vivo and ex vivo status. Another advantage of MRI is its ability to bridge the preclinical and clinical experiments as it allows similar study methods and environments between animals and humans. Therefore, MRI can be used as a useful tool for drug development. Investigators have discovered a variety of MRI biomarkers that can quantitatively measure the biological alteration led by disease and treatment. In this chapter, a number of commonly used preclinical MRI biomarkers for drug development will be introduced and discussed, particularly being focused on their value for translational research.

Amide Proton Transfer-weighted 7-T MRI Contrast of Myelination after Cuprizone Administration.

Background Investigations of amide proton signal changes in the white matter of demyelinating diseases may provide important biophysical information for diagnostic and prognostic assessments. Purpose To evaluate amide proton signals in cuprizone-induced rats using amide proton transfer-weighted (APTw) MRI, which provides in vivo image contrast by changing amide proton concentrations during demyelination (DEM) and subsequent remyelination (REM). Materials and Methods In this animal study, APTw 7-T MRI was performed in 21 male Wistar rats divided into cuprizone-induced (n = 14) and control (n = 7) groups from February to August 2020. The cuprizone-induced group was further subdivided into DEM (n = 7) and REM (n = 7) groups. Seven weeks after cuprizone feeding, rats in the DEM group were killed prior to transmission electron microscopy and myelin staining, while rats in the REM group were changed to a normal chow diet and fed for 5 weeks. In each group, the APTw signals were calculated using a conventional magnetization transfer ratio at 3.5 ppm based on regions of interest in the corpus callosum. Statistical differences in APTw signals among the groups were analyzed with one-way analysis of variance followed by Tukey post hoc tests. Results The mean APTw signals in the control and DEM groups were -4.42% ± 0.60 (standard deviation) (95% CI: -4.98, -3.86) and -2.57% ± 0.48 (95% CI: -3.01, -2.12), respectively, indicating higher in vivo APTw signals in the DEM lesion (P < .001). After REM, mean APTw signal in the REM group was -3.83% ± 0.67 (95% CI: -4.45, -3.22), similar to that in the control group (P = .18) and lower than that in the DEM group (P < .001). Conclusion Significant amide proton transfer-weighted (APTw) metric changes coupled with the histologic characteristics of the demyelination and remyelination processes indicate the potential usefulness of APTw 7-T MRI to monitor earlier myelination processes. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by van Zijl in this issue.

Treatment of chemotherapy-induced cachexia with BST204: a multimodal validation study.

INTRODUCTION: Chemotherapy is a major etiology of cachexia. Ginseng products are known to have various anti-cachectic and health-promoting effects, such as inhibiting inflammation and promoting energy production. In particular, BST204, purified ginseng dry extract, contains multiple ginsenosides that can reduce chemotherapy-related fatigue and toxicity. OBJECTIVES: To investigate the effects of BST204 on the alleviation of chemotherapy-induced cachexia using a multimodal approach. METHODS: In a CT26 mouse syngeneic colon cancer model, cachexia was predominantly induced by chemotherapy with 5-fluorouracil (5-FU) than by tumor growth. BST204 at a dose of 100 or 200 mg/kg was administered to 5-FU-treated mice. RESULTS: BST204 significantly mitigated the decrease in tumor-excluded body weight (change in 5-FU group and BST204 groups: - 13% vs. - 6% on day 7; - 30% vs. - 20% on day 11), muscle volume (- 19% vs. - 11%), and fat volume (- 91% vs. - 56%). The anti-cachectic effect of BST204 was histologically demonstrated by an improved balance between muscle regeneration and degeneration and a decrease in muscle cross-sectional area reduction. CONCLUSION: Chemotherapy-induced cachexia was biochemically and metabolically characterized by activated inflammation, enhanced oxidative stress, increased protein degradation, decreased protein stabilization, reduced glucose-mediated energy production, and deactivated glucose-mediated biosynthesis. These adverse effects were significantly improved by BST204 treatment. Overall, our multimodal study demonstrated that BST204 could effectively alleviate chemotherapy-induced cachexia.

Performance of Prostate Imaging Reporting and Data System Version 2.1 for Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) was introduced in 2012 and updated to version 2.1 (v2.1) in early 2019 to improve diagnostic performance and interreader reliability. PURPOSE: To evaluate the diagnostic performance of PI-RADS v2.1 in comparison with v2. METHODS: A systematic review and meta-analysis of the literature was performed using MEDLINE, EMBASE, and Cochrane databases to identify studies evaluating the diagnostic performance of PI-RADS v2.1 for diagnosing clinically significant prostate cancer (csPCa). STUDY TYPE: Systematic review and meta-analysis. SUBJECT: One thousand two hundred forty-eight patients with 1406 lesions from 10 eligible articles. FIELD STRENGTH/SEQUENCE: Conventional MR sequences at 1.5 T and 3 T. ASSESSMENT: Two reviewers independently identified and reviewed the original articles reporting diagnostic performance of PI-RADS v2.1. STATISTICAL TESTS: Meta-analytic summary sensitivity and specificity were calculated using a bivariate random effects model. Meta-analytic sensitivity and specificity between PI-RADS v2 and v2.1 were compared. RESULTS: The pooled sensitivity and specificity of PI-RADS v2.1 were 87% (95% confidence intervals, 82-91%) and 74% (63-82%), respectively. In five studies available for a head-to-head comparison between PI-RADS v2.1 and v2, there were no significant differences in either sensitivity (90% [86-94%] vs. 88% [83-93%], respectively) or specificity (76% [59-93%] vs. 61% [39-83%], respectively; P = 0.37). The sensitivity and specificity were 81% (73-87%) and 82% (68-91%), respectively, for a PI-RADS score cutoff of ≥4, and 94% (88-97%) and 56% (35-97%) for ≥3. Regarding the zonal location, the sensitivity and specificity for the transitional zone only were 90% (84-96%) and 76% (62-90%) respectively, whereas for the whole gland they were 85% (79-91%) and 71% (57-85%). DATA CONCLUSION: PI-RADS v2.1 demonstrated good overall performance for the diagnosis of csPCa. PI-RADS v2.1 tended to show higher specificity than v2, but the difference lacked statistical significance. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 3.

Preoperative MRI-based estimation of risk for positive resection margin after radical prostatectomy in patients with prostate cancer: development and validation of a simple scoring system.

OBJECTIVES: To develop a simplified MRI-based model to predict the risk for positive surgical margins (PSMs) after radical prostatectomy (RP) in patients with prostate cancer (PCa). METHODS: Consecutive patients who underwent RP for PCa were retrospectively identified from a tertiary referral hospital. Patients who underwent RP between January 2014 and June 2014 were assigned as derivation cohort (n = 330) and those between January 2018 and February 2018 were assigned as validation cohort (n = 100). MRI-based predictors associated with PSM were assessed: tumor size, tumor-capsule contact length, the Prostate Imaging Reporting and Data System (PI-RADS) category, tumor location (tumor contact to the apex or posterolateral side near the neurovascular bundle), apical depth, and prostate volume. A prediction model was developed by using multivariable logistic regression, and then it was transformed into a scoring system. The prediction and calibration performance of this scoring system was evaluated using the C statistics and Hosmer-Lemeshow goodness-of-fit test. RESULTS: A total of 121 (36.7%) and 32 (32.0%) of patients in the derivation and validation cohorts had PSMs after RP. The scoring system consisted of the following variables: tumor-capsule contact length, PI-RADS category, tumor located at the apex and/or posterolateral side. This scoring system provided good prediction performance for PSM in the derivation (C statistics, 0.80 [95% CI: 0.76, 0.85]) and validation (C statistics, 0.77 [95% CI: 0.68, 0.87]) cohorts, and also showed good calibration in both cohorts (p = 0.83 and 0.86, respectively). CONCLUSIONS: An MRI-based scoring system can help estimate the risk of PSM after RP. KEY POINTS: • An MRI-based scoring system served as a tool to estimate the risk of positive surgical margin (C statistics, 0.80 and 0.77 in the derivation and validation cohorts, respectively) after radical prostatectomy. • Tumor with contact to the apex or posterolateral aspect, the tumor contact length to capsule, and higher PI-RADS category were independent predictors for the presence of positive resection margins after radical prostatectomy in men with prostate cancer. • High-risk patients as determined by the scoring system demonstrated adverse post-surgical outcomes compared with low- or intermediate-risk patients, in regard to longer length (mean length, 13.0 mm versus 3.9 mm in low risk or 6.2 mm in intermediate risk; p ≤ 0.001) and higher Gleason grade at the margin (grades 4 and 5 in 69.4% and 20.4% versus 16.7% and 16.7% in low risk or 46.7% and 5.4% in intermediate risk; p < 0.001).

Ancillary imaging and clinical features for the characterization of prostate lesions: A proposed approach to reduce false positives.

The relatively low specificity and positive predictive value of the Prostate Imaging-Reporting and Data System (PI-RADS) can lead to considerable false-positive results and unnecessary biopsies. The aim of this study was to propose ancillary features (AFs) indicating clinically significant prostate cancer (csPCa) or benign tissues in PI-RADS category ≥3 lesions and determine the usefulness of these AFs in reducing false-positive assessments of suspicious lesions in men at csPCa risk. This was a retrospective study, which included 199 men. A 3T, including turbo spin echo T2 -weighted, echo-planar diffusion-weighted, and spoiled gradient echo dynamic contrast-enhanced (DCE) images, was used. Five AFs (prostate-specific antigen density ≥0.15 ng/mL2 ; size ≥10 mm; heterogeneous T2 signal intensity; circumscribed nodule in the junction of peripheral and transition zone; and DCE time curves) indicating csPCa or non-csPCa were evaluated by three independent readers. The sensitivity and specificity of each AF were calculated. Inter-reader agreement was evaluated using κ statistics. Univariate and multivariate logistic regression analyses were conducted to determine significant AFs. The reduction in positive call rates and csPCa detection rates with combined AF use were calculated and compared with the findings obtained with PI-RADS use alone. The sensitivities and specificities of the AFs indicating csPCa were 72.1%-96.5% and 27.4%-75.2% for reader 1, 66.3%-96.5% and 23.9%-62.0% for reader 2, and 67.4%-96.5% and 34.5%-78.8% for reader 3, with moderate to substantial inter-reader agreement (Fleiss κ, 0.551-0.643). The combined use of two or more AFs for assessing PI-RADS ≥3 lesions resulted in a 19.6%-30.7% reduction in positive calls (p < .05) compared to PI-RADS use alone while preserving the csPCa detection rates (p ≥ .06) for three readers. The use of AFs in combination with PI-RADS can reduce positive calls and false positives without csPCa under-detection.

Temporal Changes in In Vivo Glutamate Signal during Demyelination and Remyelination in the Corpus Callosum: A Glutamate-Weighted Chemical Exchange Saturation Transfer Imaging Study.

BACKGROUND: Glutamate-weighted chemical exchange saturation transfer (GluCEST) is a useful imaging tool that can be used to detect changes in glutamate levels in vivo and could also be helpful in the diagnosis of brain myelin changes. We investigated glutamate level changes in the cerebral white matter of a rat model of cuprizone-administered demyelination and remyelination using GluCEST. METHOD: We used a 7 T pre-clinical magnetic resonance imaging (MRI) system. The rats were divided into the normal control (CTRL), cuprizone-administered demyelination (CPZDM), and remyelination (CPZRM) groups. GluCEST data were analyzed using the conventional magnetization transfer ratio asymmetry in the corpus callosum. Immunohistochemistry and transmission electron microscopy analyses were also performed to investigate the myelinated axon changes in each group. RESULTS: The quantified GluCEST signals differed significantly between the CPZDM and CTRL groups (-7.25 ± 1.42% vs. -2.84 ± 1.30%; p = 0.001). The increased GluCEST signals in the CPZDM group decreased after remyelination (-6.52 ± 1.95% in CPZRM) to levels that did not differ significantly from those in the CTRL group (p = 0.734). CONCLUSION: The apparent temporal signal changes in GluCEST imaging during demyelination and remyelination demonstrated the potential usefulness of GluCEST imaging as a tool to monitor the myelination process.

Signal alterations of glutamate-weighted chemical exchange saturation transfer MRI in lysophosphatidylcholine-induced demyelination in the rat brain.

PURPOSE: To compare in vivo glutamate-weighted chemical exchange saturation transfer (GluCEST-weighted) signal changes between in a rat model of demyelinated multiple sclerosis and control groups. PROCEDURES: Using a pre-clinical 7 T magnetic resonance imaging (MRI) system, CEST imaging was applied to a toxin (lysophosphatidylcholine; LPC) induced rat (MSLPC) and control (CTRL) groups to compare in vivo glutamate signal changes. The GluCEST-weighted signals were analyzed based on the magnetization transfer ratio asymmetry approach at 3.0 ppm on the region-of-interests (ROIs) in the corpus callosum and hippocampus at each hemispheric region. RESULTS: GluCEST-weighted signals were significantly changed between the CTRL and MSLPC groups, while higher glutamate signals were indicated in the MSLPC than the CTRL group ([MSLPC / CTRL]; hippocampus: [6.159 ± 0.790 / 4.336 ± 0.446] and corpus callosum: [-3.545 ± 0.945 / -6.038 ± 0.620], all p = 0.001). CONCLUSIONS: Our results show increased GluCEST-weighted signals in the LPC-induced demyelination rat brain compared with control. GluCEST-weighted imaging could be a useful tool for defining a biomarker to estimate the glutamate-related metabolism in MS.

Regional Mapping of Brain Glutamate Distributions Using Glutamate-Weighted Chemical Exchange Saturation Transfer Imaging.

PURPOSE: To investigate glutamate signal distributions in multiple brain regions of a healthy rat brain using glutamate-weighted chemical exchange saturation transfer (GluCEST) imaging. METHOD: The GluCEST data were obtained using a 7.0 T magnetic resonance imaging (MRI) scanner, and all data were analyzed using conventional magnetization transfer ratio asymmetry in eight brain regions (cortex, hippocampus, corpus callosum, and rest of midbrain in each hemisphere). GluCEST data acquisition was performed again one month later in five randomly selected rats to evaluate the stability of the GluCEST signal. To evaluate glutamate level changes calculated by GluCEST data, we compared the results with the concentration of glutamate acquired from 1H magnetic resonance spectroscopy (1H MRS) data in the cortex and hippocampus. RESULTS: GluCEST signals showed significant differences (all p ≤ 0.001) between the corpus callosum (-1.71 ± 1.04%; white matter) and other brain regions (3.59 ± 0.41%, cortex; 5.47 ± 0.61%, hippocampus; 4.49 ± 1.11%, rest of midbrain; gray matter). The stability test of GluCEST findings for each brain region was not significantly different (all p ≥ 0.263). In line with the GluCEST results, glutamate concentrations measured by 1H MRS also appeared higher in the hippocampus (7.30 ± 0.16 µmol/g) than the cortex (6.89 ± 0.72 µmol/g). CONCLUSION: Mapping of GluCEST signals in the healthy rat brain clearly visualize glutamate distributions. These findings may yield a valuable database and insights for comparing glutamate signal changes in pre-clinical brain diseases.

Comparison of biopsy strategies for prostate biopsy according to lesion size and PSA density in MRI-directed biopsy pathway.

PURPOSE: To investigate whether the detection of clinically significant prostate cancer (csPCa) and the added value of focal saturation biopsy and systematic biopsy (SBx) differ according to index lesion size, and to compare the current guidelines for csPCa detection. METHODS: This retrospective study included consecutive men who underwent MRI and subsequent SBx and MRI-targeted biopsy (TBx) for a suspicious lesion between April 2019 and February 2020. Lesion visibility on transrectal ultrasound (US) and added value of focal saturation biopsy and SBx were compared according to index lesion size using chi-square and McNemar tests. csPCa detection rates and the proportion of biopsy-indicated men were compared among four biopsy strategies based on current guidelines. RESULTS: Of 313 men evaluated (median age, 65; interquartile range 60‒71), csPCa was detected in 110 (35%). In lesions < 10 mm, greater US invisibility (42.7% of lesions < 10 mm versus 20.0% of lesions ≥ 10 mm; p < 0.001) and higher added value of focal saturation biopsy and SBx (11.1% and 17.1% in lesions < 10 mm versus 4.2% and 6.3% in lesions ≥ 10 mm) were observed, compared with lesions ≥ 10 mm. Consideration of prostate-specific antigen (PSA) density > 0.15 ng/mL/mL as a cutoff in unsuspicious MRI led to a 14% reduction (44/313) in men who needed biopsy. CONCLUSION: Determination of the biopsy strategy in terms of the need for focal saturation biopsy or SBx should be made considering lesion size. The use of PSA density in non-suspicious MRI can lead to a reduction in biopsy-indicated men.

Risk Stratification of Prostate Cancer According to PI-RADS® Version 2 Categories: Meta-Analysis for Prospective Studies.

PURPOSE: The Prostate Imaging Reporting and Data System (PI-RADS) version 2 (v2) categorizes the likelihood of clinically significant prostate cancer on magnetic resonance imaging and determines the diagnostic pathway. We determined clinically significant prostate cancer and all prostate cancer detection rates in each PI-RADS v2 category. MATERIALS AND METHODS: MEDLINE®, EMBASE® and Cochrane databases were searched for prospective studies reporting the detection rates of clinically significant prostate cancer or all prostate cancer. Random effects models were used to determine pooled detection rates of clinically significant prostate cancer and all prostate cancer for each PI-RADS category. The risk of bias was assessed with the Quality Assessment of Diagnostic Accuracy Studies-2. Meta-regression analysis was performed to identify factors affecting study heterogeneity. RESULTS: Thirteen prospective studies including 4,265 men who underwent magnetic resonance imaging targeted biopsy and/or systematic biopsy for a PI-RADS v2 category 3 or greater, or systematic biopsy for PI-RADS 1-2 were included. The pooled detection rates of clinically significant prostate cancer monotonically increased for each PI-RADS v2 category, ie 4% (95% CI 2-8) for category 1-2, 17% (95% CI 13-21) for category 3, 46% (95% CI 38-55) for category 4 and 75% (95% CI 73-78) for category 5. Substantial study heterogeneity was noted in clinically significant prostate cancer detection rates for categories 1-2 and 4, which were significantly affected by study subject selection (biopsy naïve patients only or not) and studies with a high risk of bias. CONCLUSIONS: PI-RADS v2 can be useful for the stratification of the risk of clinically significant prostate cancer in patients at risk for prostate cancer but the limitations in category 4 still remain.

Interreader Agreement with Prostate Imaging Reporting and Data System Version 2 for Prostate Cancer Detection: A Systematic Review and Meta-Analysis.

PURPOSE: We evaluated interreader agreement with PI-RADS® (Prostate Imaging Reporting and Data System) version 2 for detection of prostate cancer. MATERIALS AND METHODS: We searched MEDLINE®, Embase® and the Cochrane Library between 2015 and June 3, 2019 to identify original research reporting interreader agreement in the use of PI-RADS version 2. Quality of the retrieved studies was assessed by 2 independent reviewers using the Guidelines for Reporting Reliability and Agreement Studies. Pooled κ for PI-RADS version 2 was calculated, and a head-to-head comparison with version 1 was performed for the available studies. Subgroup analysis was performed according to zonal anatomy (peripheral or transitional zone), cutoff value (4 or higher, or 3 or higher) and specific imaging sequences (T2-weighted, diffusion-weighted and dynamic contrast enhanced). Meta-regression analysis was performed to assess the cause of study heterogeneity. RESULTS: A total of 30 studies (4,095 patients) were included. Pooled κ of PI-RADS version 2 was 0.61 (95% CI 0.55-0.67). In 4 studies evaluating head-to-head comparisons PI-RADS versions 1 and 2 showed similar pooled κ values (0.61, 95% CI 0.33-0.90 vs 0.68, 95% CI 0.57-0.79; p=0.61). Substantial interreader agreement was noted with a cutoff of 4 or higher (κ=0.61) and moderate agreement was observed with a cutoff of 3 or higher (κ=0.57), peripheral zone (κ=0.64), transitional zone (κ=0.49) and the 3 magnetic resonance imaging sequences (κ 0.42-0.58). Difference in reader experience was the single significant factor affecting study heterogeneity (p=0.01). CONCLUSIONS: PI-RADS version 2 provides substantial interreader agreement in overall scoring in patients with suspicious prostate cancer, with a similar level of agreement to version 1.

Radiomics-based prediction model for outcomes of PD-1/PD-L1 immunotherapy in metastatic urothelial carcinoma.

OBJECTIVES: To evaluate the usefulness of a radiomics-based prediction model for predicting response and survival outcomes of patients with metastatic urothelial carcinoma treated with immunotherapy targeting programmed cell death 1 (PD-1) and its ligand (PD-L1). METHODS: Sixty-two patients who underwent immunotherapy were divided into training (n = 41) and validation sets (n = 21). A total of 224 measurable lesions were identified on contrast-enhanced CT. A radiomics signature was constructed with features selected using a least absolute shrinkage and selection operator algorithm in the training set. A radiomics-based model was built based on a radiomics signature consisting of five reliable RFs and the presence of visceral organ involvement using multivariate logistic regression. According to a cutoff determined on the training set, patients in the validation set were assigned to either high- or low-risk groups. Kaplan-Meier analysis was performed to compare progression-free and overall survival between high- and low-risk groups. RESULTS: For predicting objective response and disease control, the areas under the receiver operating characteristic curves of the radiomics-based model were 0.87 (95% CI, 0.65-0.97) and 0.88 (95% CI, 0.67-0.98) for the validation set, providing larger net benefit determined by decision curve analysis than without radiomics-based model. The high-risk group in the validation set showed shorter progression-free and overall survival than the low-risk group (log-rank p = 0.044 and p = 0.035). CONCLUSIONS: The radiomics-based model may predict the response and survival outcome in patients treated with PD-1/PD-L1 immunotherapy for metastatic urothelial carcinoma. This approach may provide important and decision tool for planning immunotherapy. KEY POINTS: • A radiomics-based model was built based on radiomics features and the presence of visceral organ involvement for prediction of outcomes in metastatic urothelial carcinoma treated with immunotherapy. • This prediction model demonstrated good prediction of treatment response and higher net benefit than no model in the independent validation set. • This radiomics-based model demonstrated significant associations with progression-free and overall survival between low-risk and high-risk groups.