4D flow MRI in abdominal vessels: prospective comparison of k-t accelerated free breathing acquisition to standard respiratory navigator gated acquisition

Volumetric phase-contrast magnetic resonance imaging with three-dimensional velocity encoding (4D flow MRI) has shown utility as a non-invasive tool to examine altered blood flow in chronic liver disease. Novel 4D flow MRI pulse sequences with spatio-temporal acceleration can mitigate the long acquisition times of standard 4D flow MRI, which are an impediment to clinical adoption. The purpose of our study was to demonstrate feasibility of a free-breathing, spatio-temporal (k-t) accelerated 4D flow MRI acquisition for flow quantification in abdominal vessels and to compare its image quality, flow quantification and inter-observer reproducibility with a standard respiratory navigator-gated 4D flow MRI acquisition. Ten prospectively enrolled patients (M/F: 7/3, mean age = 58y) with suspected portal hypertension underwent both 4D flow MRI acquisitions. The k-t accelerated acquisition was approximately three times faster (3:11 min ± 0:12 min/9:17 min ± 1:41 min, p < 0.001) than the standard respiratory-triggered acquisition. Vessel identification agreement was substantial between acquisitions and observers. Average flow had substantial inter-sequence agreement in the portal vein and aorta (CV < 15%) and poorer agreement in hepatic and splenic arteries (CV = 11-38%). The k-t accelerated acquisition recorded reduced velocities in small arteries and reduced splenic vein flow. Respiratory gating combined with increased acceleration and spatial resolution are needed to improve flow measurements in these vessels.

Performance of native and gadoxetate-enhanced liver and spleen T1 mapping for noninvasive diagnosis of clinically significant portal hypertension: preliminary results

PURPOSE

In this preliminary study, our aim was to assess the utility of quantitative native-T₁ (T₁-pre), iron-corrected T₁ (cT₁) of the liver/spleen and T₁ mapping of the liver obtained during hepatobiliary phase (T₁-HBP) post-gadoxetate disodium, compared to spleen size/volume and APRI (aspartate aminotransferase-to-platelet ratio index) for noninvasive diagnosis of clinically significant portal hypertension [CSPH, defined as hepatic venous pressure gradient (HVPG) ≥ 10 mm Hg].

METHODS

Forty-nine patients (M/F: 27/22, mean age 53y) with chronic liver disease, HVPG measurement and MRI were included. Breath-held T₁ and cT₁ measurements were obtained using an inversion recovery Look-Locker sequence and a T2* corrected modified Look-Locker sequence, respectively. Liver T₁-pre (n = 49), spleen T₁ (obtained pre-contrast, n = 47), liver and spleen cT₁ (both obtained pre-contrast, n = 30), liver T₁-HBP (obtained 20 min post gadoxetate disodium injection, n = 36) and liver T₁ uptake (ΔT₁, n = 36) were measured. Spleen size/volume and APRI were also obtained. Spearman correlation coefficients were used to assess the correlation between each of liver/spleen T₁/cT₁ parameters, spleen size/volume and APRI with HVPG. ROC analysis was performed to determine the performance of measured parameters for diagnosis of CSPH.

RESULTS

There were 12/49 (24%) patients with CSPH. Liver T₁-pre (r = 0.287, p = 0.045), liver T₁-HBP (r = 0.543, p = 0.001), liver ΔT₁ (r =  - 0.437, p = 0.008), spleen T₁ (r = 0.311, p = 0.033) and APRI (r = 0.394, p = 0.005) were all significantly correlated with HVPG, while liver cT₁, spleen cT₁ and spleen size/volume were not. The highest AUCs for the diagnosis of CSPH were achieved with liver T₁-HBP, liver ΔT₁ and spleen T₁: 0.881 (95%CI 0.76-1.0, p = 0.001), 0.852 (0.72-0.98, p = 0.002) and 0.781 (0.60-0.95, p = 0.004), respectively.

CONCLUSION

Our preliminary results demonstrate the potential of liver T₁ mapping obtained during HBP post gadoxetate disodium for the diagnosis of CSPH. These results require further validation.

Prostate heterogeneity correlates with clinical features on multiparametric MRI

BACKGROUND

Prostate heterogeneity on multi-parametric MRI (mpMRI) may confound image interpretation by obscuring lesions; systematic biopsy may have a role in this context.

PURPOSE

To determine if prostate heterogeneity (1) correlates with clinical risk factors for prostate cancer and (2) associates with higher-grade tumor in systematic biopsy (SB), compared with MRI-directed target biopsy (MDTB), i.e., SB > MDTB, thus providing a rationale for combined biopsy.

METHODS

IRB-approved retrospective study included men who underwent mpMRI, SB, and MDTB between 2015 and 2017. Regions of interest were applied to the entire transition zone (TZ) and peripheral zone (PZ) on T2-weighted imaging (T2WI), apparent diffusion coefficient maps (ADC), and early dynamic contrast-enhanced (DCE) images on the midgland slice. Mean signal intensities and standard deviation (SD) of each zone were calculated. SD served as a measure of heterogeneity. Spearman's rank correlation analysis of clinical and imaging variables was performed. Univariate logistic regression was used to determine if any imaging variable associated with SB > MDTB.

RESULTS

93 patients were included. Significant correlations included age and TZ ADC heterogeneity (rho = 0.34, p = 0.013), PSA density, and mean TZ ADC (rho = - 0.29, p = 0.049). PZ T2WI heterogeneity correlated with PZ ADC heterogeneity (rho = 0.48, p < 0.001). PZ DCE heterogeneity correlated with TZ DCE heterogeneity (rho = 0.46, p < 0.001). TZ ADC heterogeneity was associated with SB > MDTB prior to multiple comparison correction (p = 0.032). p value after correction was 0.24.

CONCLUSION

TZ ADC heterogeneity correlated with age and may reflect prostatic hyperplasia and/or prostate cancer. PZ heterogeneity, possibly a measure of prostatitis, correlated with TZ hyperplasia and/or inflammation. TZ ADC heterogeneity was associated with SB > MDTB with p value of < 0.05 prior to multiple correction; future investigation is needed to further elucidate significance of ADC heterogeneity in prostate imaging.

Predictors of acute deep venous thrombosis in patients hospitalized for COVID-19

ABSTRACT

Deep venous thrombosis (DVT) is associated with high mortality in coronavirus disease 2019 (COVID-19) but there remains uncertainty about the benefit of anti-coagulation prophylaxis and how to decide when ultrasound screening is indicated. We aimed to determine parameters predicting which COVID-19 patients are at risk of DVT and to assess the benefit of prophylactic anti-coagulation.Adult hospitalized patients with positive severe acute respiratory syndrome coronavirus-2 reverse transcription-polymerase chain reaction (RT-PCR) undergoing venous duplex ultrasound for DVT assessment (n = 451) were retrospectively reviewed. Clinical and laboratory data within 72 hours of ultrasound were collected. Using split sampling and a 10-fold cross-validation, a random forest model was developed to find the most important variables for predicting DVT. Different d-dimer cutoffs were examined for classification of DVT. We also compared the rate of DVT between the patients going and not going under thromboprophylaxis.DVT was found in 65 (14%) of 451 reverse transcription-polymerase chain reaction positive patients. The random forest model, trained and cross-validated on 2/3 of the original sample (n = 301), had area under the receiver operating characteristic curve = 0.91 (95% confidence interval [CI]: 0.85-0.97) for prediction of DVT in the test set (n = 150), with sensitivity = 93% (95%CI: 68%-99%) and specificity = 82% (95%CI: 75%-88%). The following variables had the highest importance: d-dimer, thromboprophylaxis, systolic blood pressure, admission to ultrasound interval, and platelets. Thromboprophylaxis reduced DVT risk 4-fold from 26% to 6% (P < .001), while anti-coagulation therapy led to hemorrhagic complications in 14 (22%) of 65 patients with DVT including 2 fatal intra-cranial hemorrhages. D-dimer was the most important predictor with area under curve = 0.79 (95%CI: 0.73-0.86) by itself, and a 5000 ng/mL threshold at 7 days postCOVID-19 symptom onset had 75% (95%CI: 53%-90%) sensitivity and 81% (95%CI: 72%-88%) specificity. In comparison with d-dimer alone, the random forest model showed 68% versus 32% specificity at 95% sensitivity, and 44% versus 23% sensitivity at 95% specificity.D-dimer >5000 ng/mL predicts DVT with high accuracy suggesting regular monitoring with d-dimer in the early stages of COVID-19 may be useful. A random forest model improved the prediction of DVT. Thromboprophylaxis reduced DVT in COVID-19 patients and should be considered in all patients. Full anti-coagulation therapy has a risk of life-threatening hemorrhage.

Magnetic Resonance Imaging Radiomics-Based Machine Learning Prediction of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions

BACKGROUND

While Prostate Imaging Reporting and Data System (PI-RADS) 4 and 5 lesions typically warrant prostate biopsy and PI-RADS 1 and 2 lesions may be safely observed, PI-RADS 3 lesions are equivocal.

PURPOSE

To construct and cross-validate a machine learning model based on radiomics features from T₂ -weighted imaging (T₂ WI) of PI-RADS 3 lesions to identify clinically significant prostate cancer (csPCa), that is, pathological Grade Group ≥ 2.

STUDY TYPE

Single-center retrospective study.

POPULATION

A total of 240 patients were included (training cohort, n = 188, age range 43-82 years; test cohort, n = 52, age range 41-79 years). Eligibility criteria were 1) magnetic resonance imaging (MRI)-targeted biopsy between 2015 and 2020; 2) PI-RADS 3 index lesion identified on multiparametric MRI; (3) biopsy performed within 1 year of MRI. The percentages of csPCa lesions were 10.6% and 15.4% in the training and test cohorts, respectively.

FIELD STRENGTH/SEQUENCE

A 3 T; T₂ WI turbo-spin echo, diffusion-weighted spin-echo echo planar imaging, dynamic contrast-enhanced MRI with time-resolved T1-weighted imaging.

ASSESSMENT

Multislice volumes-of-interest (VOIs) were drawn in the PI-RADS 3 index lesions on T₂ WI. A total of 107 radiomics features (first-order histogram and second-order texture) were extracted from the segmented lesions.

STATISTICAL TESTS

A random forest classifier using the radiomics features as input was trained and validated for prediction of csPCa. The performance of the machine learning classifier, prostate specific antigen (PSA) density, and prostate volume for csPCa prediction was evaluated using receiver operating characteristic (ROC) analysis.

RESULTS

The trained random forest classifier constructed from the T₂ WI radiomics features good and statistically significant area-under-the-curves (AUCs) of 0.76 (P = 0.022) for prediction of csPCa in the test set. Prostate volume and PSA density showed moderate and nonsignificant performance (AUC 0.62, P = 0.275 and 0.61, P = 0.348, respectively) for csPCa prediction in the test set.

CONCLUSION

The machine learning classifier based on T₂ WI radiomic features demonstrated good performance for prediction of csPCa in PI-RADS 3 lesions.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: 2.

Multivariate analysis of CT imaging, laboratory, and demographical features for prediction of acute kidney injury in COVID-19 patients: a Bi-centric analysis

PURPOSE

To develop and externally validate a multivariate prediction model for the prediction of acute kidney injury (AKI) in COVID-19, based on baseline renal perfusion from contrast-enhanced CT together with clinical and laboratory parameters.

METHODS

In this retrospective IRB-approved study, we identified COVID-19 patients who had a standard-of-care contrast-enhanced abdominal CT scan within 5 days of their COVID-19 diagnosis at our institution (training set; n = 45, mean age 65 years, M/F 23/22) and at a second institution (validation set; n = 41, mean age 61 years, M/F 22/19). The CT renal perfusion parameter, cortex-to-aorta enhancement index (CAEI), was measured in both sets. A multivariate logistic regression model for predicting AKI was constructed from the training set with stepwise feature selection with CAEI together with demographical and baseline laboratory/clinical data used as input variables. Model performance in the training and validation set was evaluated with ROC analysis.

RESULTS

AKI developed in 16 patients (35.6%) of the training set and in 6 patients (14.6%) of the validation set. Baseline CAEI was significantly lower in the patients that ultimately developed AKI (P = 0.003). Logistic regression identified a model combining baseline CAEI, blood urea nitrogen, and gender as most significant predictor of AKI. This model showed excellent diagnostic performance for prediction of AKI in the training set (AUC = 0.89, P < 0.001) and good performance in the validation set (AUC 0.78, P = 0.030).

CONCLUSION

Our results show diminished renal perfusion preceding AKI and a promising role of CAEI, combined with laboratory and demographic markers, for prediction of AKI in COVID-19.

MRI Mapping of Renal T1: Basic Concept

In renal MRI, measurement of the T₁ relaxation time of water molecules may provide a valuable biomarker for a variety of pathological conditions. Due to its sensitivity to the tissue microenvironment, T₁ has gained substantial interest for noninvasive imaging of renal pathology, including inflammation and fibrosis. In this chapter, we will discuss the basic concept of T₁ mapping and different T₁ measurement techniques and we will provide an overview of emerging preclinical applications of T₁ for imaging of kidney disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

Early effect of 90Y radioembolisation on hepatocellular carcinoma and liver parenchyma stiffness measured with MR elastography: initial experience

OBJECTIVES

To quantify hepatocellular carcinoma (HCC) and liver parenchyma stiffness using MR elastography (MRE) and serum alpha fetoprotein (AFP), before and 6 weeks (6w) after ⁹⁰Y radioembolisation (RE), and to assess the value of baseline tumour and liver stiffness (TS/LS) and AFP in predicting response at 6w and 6 months (6 m).

METHODS

Twenty-three patients (M/F 18/5, mean age 68.3 ± 9.3 years) scheduled to undergo RE were recruited into this prospective single-centre study. Patients underwent an MRI exam at baseline and 6w following RE (range 39-47 days) which included MRE using a prototype 2D EPI sequence. TS, peritumoural LS/LS remote from the tumour, tumour size, and AFP were measured at baseline and at 6w. Treatment response was determined using mRECIST at 6w and 6 m.

RESULTS

MRE was technically successful in 17 tumours which were classified at 6w as complete response (CR, n = 7), partial response (PR, n = 4), and stable disease (SD, n = 6). TS and peritumoural LS were significantly increased following RE (p = 0.016, p = 0.039, respectively), while LS remote from tumour was unchanged (p = 0.245). Baseline TS was significantly lower in patients who achieved CR at 6w (p = 0.014). Baseline TS, peritumoural LS (both AUC = 0.857), and AFP (AUC = 0.798) showed fair/excellent diagnostic performance in predicting CR at 6w, but were not significant predictors of OR or CR at 6 m.

CONCLUSION

Our initial results suggest that HCC TS and peritumoural LS increase early after RE. Baseline TS, peritumoural LS, and AFP were all significant predictors of CR to RE at 6w. These results should be confirmed in a larger study.

KEY POINTS

• Magnetic resonance elastography-derived tumour stiffness and peritumoural liver stiffness increase significantly at 6 weeks post radioembolisation whereas liver stiffness remote from the tumour is unchanged. • Baseline tumour stiffness and peritumoural liver stiffness are lower in patients who achieve complete response at 6 weeks post radioembolisation. • Baseline tumour size is significantly correlated with baseline tumour stiffness.

Integrated quantitative susceptibility and R2 * mapping for evaluation of liver fibrosis: An ex vivo feasibility study

To develop a method for noninvasive evaluation of liver fibrosis, we investigated the differential sensitivities of quantitative susceptibility mapping (QSM) and R₂ * mapping using corrections for the effects of liver iron. Liver fibrosis is characterized by excessive accumulation of collagen and other extracellular matrix proteins. While collagen increases R₂ * relaxation, measures of R₂ * for fibrosis are confounded by liver iron, which may be present in the liver over a wide range of concentrations. The diamagnetic collagen contribution to susceptibility values measured by QSM is much less than the contribution of highly paramagnetic iron. In 19 ex vivo liver explants with and without fibrosis, QSM (χ), R₂ * and proton density fat fraction (PDFF) maps were constructed from multiecho gradient-recalled echo (mGRE) sequence acquisition at 3 T. Median parameter values were recorded and differences between the MRI parameters in nonfibrotic vs. advanced fibrotic/cirrhotic samples were evaluated using Mann-Whitney U tests and receiver operating characteristic analyses. Logistic regression with stepwise feature selection was employed to evaluate the utility of combined MRI measurements for detection of fibrosis. Median R₂ * increased in fibrotic vs. nonfibrotic liver samples (P = .041), while differences in χ and PDFF were nonsignificant (P = .545 and P = .395, respectively). Logistic regression identified the combination of χ and R₂ * significant for fibrosis detection (logit [prediction] = -8.45 + 0.23 R₂ * - 28.8 χ). For this classifier, a highly significant difference between nonfibrotic vs. advanced fibrotic/cirrhotic samples was observed (P = .002). The model exhibited an AUC of 0.909 (P = .003) for detection of advanced fibrosis/cirrhosis, which was substantially higher compared with AUCs of the individual parameters (AUC 0.591-0.784). An integrated QSM and R₂ * analysis of mGRE 3 T imaging data is promising for noninvasive diagnostic assessment of liver fibrosis.

Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid-enhanced MRI

OBJECTIVES

To (1) develop a fully automated deep learning (DL) algorithm based on gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI and (2) compare the diagnostic performance of DL vs. MR elastography (MRE) for noninvasive staging of liver fibrosis.

METHODS

This single-center retrospective study included 355 patients (M/F 238/117, mean age 60 years; training, n = 178; validation, n = 123; test, n = 54) who underwent gadoxetic acid-enhanced abdominal MRI, including HBP and MRE, and pathological evaluation of the liver within 1 year of MRI. Cropped liver HBP images from a custom-written fully automated liver segmentation were used as input for DL. A transfer learning approach based on the ImageNet VGG16 model was used. Different DL models were built for the prediction of fibrosis stages F1-4, F2-4, F3-4, and F4. ROC analysis was performed to evaluate the performance of DL in training, validation, and test sets and of MRE liver stiffness in the test set.

RESULTS

AUC values of DL were 0.99/0.70/0.77 (F1-4), 0.92/0.71/0.91 (F2-4), 0.91/0.78/0.90 (F3-4), and 0.98/0.83/0.85 (F4) for training/validation/test sets, respectively. The AUCs of MRE liver stiffness in the test set were 0.86 (F1-4), 0.87 (F2-4), 0.92 (F3-4), and 0.86 (F4). AUCs of MRE and DL were not significantly different for any of the fibrosis stages (p > 0.134).

CONCLUSIONS

The fully automated DL models based on HBP gadoxetic acid MRI showed good-to-excellent diagnostic performance for staging of liver fibrosis, with similar diagnostic performance to MRE. After validation in independent sets, the DL algorithm may allow for noninvasive liver fibrosis assessment without the need for additional MRI hardware.

KEY POINTS

• The developed deep learning algorithm, based on routine standard-of-care gadoxetic acid-enhanced MRI data, showed good-to-excellent diagnostic performance for noninvasive staging of liver fibrosis. • The diagnostic performance of the deep learning algorithm was equivalent to that of MR elastography in a separate test set.

Noninvasive imaging assessment of portal hypertension

Portal hypertension (PH) is a spectrum of complications of chronic liver disease (CLD) and cirrhosis, with manifestations including ascites, gastroesophageal varices, splenomegaly, hypersplenism, hepatic hydrothorax, hepatorenal syndrome, hepatopulmonary syndrome and portopulmonary hypertension. PH can vary in severity and is diagnosed via invasive hepatic venous pressure gradient measurement (HVPG), which is considered the reference standard. Accurate diagnosis of PH and assessment of severity are highly relevant as patients with clinically significant portal hypertension (CSPH) are at higher risk for developing acute variceal bleeding and mortality. In this review, we discuss current and upcoming noninvasive imaging methods for diagnosis and assessment of severity of PH.

Characterization of solid renal neoplasms using MRI-based quantitative radiomics features

PURPOSE

To assess the diagnostic value of magnetic resonance imaging (MRI)-based radiomics features using machine learning (ML) models in characterizing solid renal neoplasms, in comparison/combination with qualitative radiologic evaluation.

METHODS

Retrospective analysis of 125 patients (mean age 59 years, 67% males) with solid renal neoplasms that underwent MRI before surgery. Qualitative (signal and enhancement characteristics) and quantitative radiomics analyses (histogram and texture features) were performed on T2-weighted imaging (WI), T1-WI pre- and post-contrast, and DWI. Mann-Whitney U test and receiver-operating characteristic analysis were used in a training set (n = 88) to evaluate diagnostic performance of qualitative and radiomics features for differentiation of renal cell carcinomas (RCCs) from benign lesions, and characterization of RCC subtypes (clear cell RCC [ccRCC] and papillary RCC [pRCC]). Random forest ML models were developed for discrimination between tumor types on the training set, and validated on an independent set (n = 37).

RESULTS

We assessed 104 RCCs (51 ccRCC, 29 pRCC, and 24 other subtypes) and 21 benign lesions in 125 patients. Significant qualitative and quantitative radiomics features (area under the curve [AUC] between 0.62 and 0.90) were included for ML analysis. Models with best diagnostic performance on validation sets showed AUC of 0.73 (confidence interval [CI] 0.5-0.96) for differentiating RCC from benign lesions (using combination of qualitative and radiomics features); AUC of 0.77 (CI 0.62-0.92) for diagnosing ccRCC (using radiomics features), and AUC of 0.74 (CI 0.53-0.95) for diagnosing pRCC (using qualitative features).

CONCLUSION

ML models incorporating MRI-based radiomics features and qualitative radiologic assessment can help characterize renal masses.

4D flow MRI for the assessment of renal transplant dysfunction: initial results

OBJECTIVES

(1) Determine inter-observer reproducibility and test-retest repeatability of 4D flow parameters in renal allograft vessels; (2) determine if 4D flow measurements in the renal artery (RA) and renal vein (RV) can distinguish between functional and dysfunctional allografts; (3) correlate haemodynamic parameters with estimated glomerular filtration rate (eGFR), perfusion measured with dynamic contrast-enhanced MRI (DCE-MRI) and histopathology.

METHODS

Twenty-five prospectively recruited renal transplant patients (stable function/chronic renal allograft dysfunction, 12/13) underwent 4D flow MRI at 1.5 T. 4D flow coronal oblique acquisitions were performed in the transplant renal artery (RA) (velocity encoding parameter, VENC = 120 cm/s) and renal vein (RV) (VENC = 45 cm/s). Test-retest repeatability (n = 3) and inter-observer reproducibility (n = 10) were assessed by Cohen's kappa, coefficient of variation (CoV) and Bland-Altman statistics. Haemodynamic parameters were compared between patients and correlated to the estimated glomerular filtration rate, DCE-MRI parameters (n = 10) and histopathology from allograft biopsies (n = 15).

RESULTS

For inter-observer reproducibility, kappa was > 0.99 and 0.62 and CoV of flow was 12.6% and 7.8% for RA and RV, respectively. For test-retest repeatability, kappa was > 0.99 and 0.5 and CoV of flow was 27.3% and 59.4%, for RA and RV, respectively. RA (p = 0.039) and RV (p = 0.019) flow were both significantly reduced in dysfunctional allografts. Both identified chronic allograft dysfunction with good diagnostic performance (RA: AUC = 0.76, p = 0.036; RV: AUC = 0.8, p = 0.018). RA flow correlated negatively with histopathologic interstitial fibrosis score ci (ρ = - 0.6, p = 0.03).

CONCLUSIONS

4D flow parameters had better repeatability in the RA than in the RV. RA and RV flow can identify chronic renal allograft dysfunction, with RA flow correlating with histopathologic interstitial fibrosis score.

KEY POINTS

• Inter-observer reproducibility of 4D flow measurements was acceptable in both the transplant renal artery and vein, but test-retest repeatability was better in the renal artery than in the renal vein. • Blood flow measurements obtained with 4D flow MRI in the renal artery and renal vein are significantly reduced in dysfunctional renal transplants. • Renal transplant artery flow correlated negatively with histopathologic interstitial fibrosis score.

Assessment of Hepatocellular Carcinoma Response to 90Y Radioembolization Using Dynamic Contrast Material-enhanced MRI and Intravoxel Incoherent Motion Diffusion-weighted Imaging

PURPOSE

To quantify diffusion and perfusion changes in hepatocellular carcinoma (HCC) induced by yttrium 90 (⁹⁰Y) radioembolization and to assess the value of dynamic contrast material-enhanced (DCE) MRI and intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for predicting HCC response.

MATERIALS AND METHODS

Institutional review board approval was obtained for this prospective study (clinical trial registry NCT01871545). Twenty-four participants with HCC (mean age, 69 years ± 9 [standard deviation], 18 men) underwent multiparametric MRI, including IVIM DWI and gadoxetic acid DCE MRI before (n = 24) and 6 weeks (n = 21) after radioembolization. IVIM DWI and DCE MRI histogram parameters were quantified in HCCs and liver parenchyma. HCC response was assessed by using modified Response Evaluation Criteria in Solid Tumors at 6 weeks and 6-12 months after radioembolization. Logistic regression analysis was used to evaluate the diagnostic performance of baseline MRI and clinical parameters for prediction of response.

RESULTS

Twenty-five HCCs were analyzed (mean size, 3.6 cm ± 1.9). Radioembolization resulted in significantly decreased perfusion (DCE MRI arterial flow, P = .002; IVIM pseudodiffusion coefficient [D*], P = .014). Multivariate logistic regression selected combined serum α-fetoprotein and portal flow (F _p ) skewness (area under the curve [AUC] = 0.924) and combined D* standard deviation and F _p kurtosis (AUC = 0.916) for prediction of objective and complete response at 6 weeks, respectively. Standard deviation of DCE MRI parameter arterial fraction was selected as the optimal predictor for complete response at 6-12 months (AUC = 0.857).

CONCLUSION

Diffusion and perfusion MRI can be used to evaluate the response of HCC to radioembolization. Pretreatment DCE MRI histogram parameters may be useful for radioembolization treatment stratification. Supplemental material is available for this article. © RSNA, 2020.

MRI radiomics features predict immuno-oncological characteristics of hepatocellular carcinoma

OBJECTIVE

To assess the value of qualitative and quantitative MRI radiomics features for noninvasive prediction of immuno-oncologic characteristics and outcomes of hepatocellular carcinoma (HCC).

METHODS

This retrospective, IRB-approved study included 48 patients with HCC (M/F 35/13, mean age 60y) who underwent hepatic resection or transplant within 4 months of abdominal MRI. Qualitative imaging traits, quantitative nontexture related and texture features were assessed in index lesions on contrast-enhanced T1-weighted and diffusion-weighted images. The association of imaging features with immunoprofiling and genomics features was assessed using binary logistic regression and correlation analyses. Binary logistic regression analysis was also employed to analyse the association of radiomics, histopathologic and genomics features with radiological early recurrence of HCC at 12 months.

RESULTS

Qualitative (r = - 0.41-0.40, p < 0.042) and quantitative (r = - 0.52-0.45, p < 0.049) radiomics features correlated with immunohistochemical cell type markers for T-cells (CD3), macrophages (CD68) and endothelial cells (CD31). Radiomics features also correlated with expression of immunotherapy targets PD-L1 at protein level (r = 0.41-0.47, p < 0.029) as well as PD1 and CTLA4 at mRNA expression level (r = - 0.48-0.47, p < 0.037). Finally, radiomics features, including tumour size, showed significant diagnostic performance for assessment of early HCC recurrence (AUC 0.76-0.80, p < 0.043), while immunoprofiling and genomic features did not (p = 0.098-0929).

CONCLUSIONS

MRI radiomics features may serve as noninvasive predictors of HCC immuno-oncological characteristics and tumour recurrence and may aid in treatment stratification of HCC patients. These results need prospective validation.

KEY POINTS

• MRI radiomics features showed significant associations with immunophenotyping and genomics characteristics of hepatocellular carcinoma. • Radiomics features, including tumour size, showed significant associations with early hepatocellular carcinoma recurrence after resection.

Magnetic resonance elastography vs. point shear wave ultrasound elastography for the assessment of renal allograft dysfunction

PURPOSE

To investigate the utility of magnetic resonance elastography (MRE) vs. ultrasound (US) point shear wave elastography (pSWE) for the assessment of chronic renal allograft dysfunction, prediction of outcome and determine the correlation with Banff pathology scores.

METHODS

In this IRB approved prospective study, 27 enrolled patients with functional (n = 15) and chronic dysfunctional (n = 12) renal allografts underwent same day 2D MRE and pSWE. Histogram parameters [including mean, median, standard deviation, kurtosis and skewness] of the magnitude of the complex shear modulus (MRE) and median Young's modulus (pSWE) were measured in the cortex (MRE and pSWE) and combined corticomedullary regions (MRE). Histopathology was available for 16 patients (4 functional, 12 dysfunctional).

RESULTS

MRE and pSWE stiffness were not significantly different between functional and dysfunctional groups (p range 0.139-0.347). The skewness of MRE corticomedullary stiffness was significantly lower (p = 0.04) in patients with chronic dysfunction and correlated significantly with Banff histopathologic scores (range r=-0.518-0.567, p = 0.035-0.040). MRE cortical and corticomedullary mean stiffness showed strong performance in predicting graft loss/relist (AUC 0.958, p = 0.011 for both). Reliable pSWE measurements were obtained in 13 patients (48 %). pSWE stiffness did not correlate with Banff scores and did not predict outcome.

CONCLUSIONS

The skewness of MRE corticomedullary stiffness is sensitive to changes in chronic allograft dysfunction, while mean/median MRE renal stiffness and median US stiffness did not differentiate patients with stable function vs those with chronic renal allograft dysfunction. MRE corticomedullary mean stiffness appears to be a predictor of graft loss/relist. pSWE was not found to be a useful method for assessing renal allografts.

Rapid stromal remodeling by short-term VEGFR2 inhibition increases chemotherapy delivery in esophagogastric adenocarcinoma

Anti-angiogenic agents combined with chemotherapy is an important strategy for the treatment of solid tumors. However, survival benefit is limited, urging the improvement of combination therapies. We aimed to clarify the effects of vascular endothelial growth factor receptor 2 (VEGFR2) targeting on hemodynamic function and penetration of drugs in esophagogastric adenocarcinoma (EAC). Patient-derived xenograft (PDX) models of EAC were subjected to long-term and short-term treatment with anti-VEGFR2 therapy followed by chemotherapy injection or multi-agent dynamic contrast-enhanced (DCE-) MRI and vascular casting. Long-term anti-VEGFR2-treated tumors showed a relatively lower flow and vessel density resulting in reduced chemotherapy uptake. On the contrary, short-term VEGFR2 targeting resulted in relatively higher flow, rapid vasodilation, and improved chemotherapy delivery. Assessment of the extracellular matrix (ECM) revealed that short-term anti-angiogenic treatment drastically remodels the tumor stroma by inducing nitric oxide synthesis and hyaluronan degradation, thereby dilating the vasculature and improving intratumoral chemotherapy delivery. These previously unrecognized beneficial effects could not be maintained by long-term VEGFR2 inhibition. As the identified mechanisms are targetable, they offer direct options to enhance the treatment efficacy of anti-angiogenic therapy combined with chemotherapy in EAC patients.

Splenic T1ρ as a noninvasive biomarker for portal hypertension

BACKGROUND

There is a need for noninvasive methods for the diagnosis and monitoring of portal hypertension (PH).

PURPOSE

To 1) assess the correlation of liver and spleen T₁ and T_1ρ measurements with portal pressures in patients with chronic liver disease, and 2) to compare the diagnostic performance of the relaxation parameters with radiological assessment of PH.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-five patients (M/F 16/9, mean age 56 years, range 21-78 years) undergoing portal pressure (hepatic venous pressure gradient [HVPG]) measurements.

FIELD STRENGTH/SEQUENCE

1.5T abdominal MRI scan, including T_1ρ and T₁ mapping.

ASSESSMENT

Liver and spleen T_1ρ and T₁ , radiological PH score, and (normalized) spleen length were evaluated.

STATISTICAL TESTS

Spearman correlation of all MRI parameters with HVPG was assessed. The diagnostic performance of the assessed parameters for prediction of PH (HVPG ≥5 mmHg) and clinically significant PH (CSPH, HVPG ≥10 mmHg) was determined by receiver operating characteristic (ROC) analysis.

RESULTS

The mean HVPG measurement was 7.8 ± 5.3 mmHg (PH, n = 18 [72%] including CSPH, n = 9 [36%]). PH score, (normalized) spleen length and spleen T_1ρ significantly correlated with HVPG, with the strongest correlation found for spleen T_1ρ (r = 0.613, P = 0.001). Spleen T_1ρ was the only parameter that showed significant diagnostic performance for assessment of PH (area under the curve [AUC] 0.817, P = 0.015) and CSPH (AUC = 0.778, P = 0.024). Normalized spleen length also showed significant diagnostic performance for prediction of CSPH, with a slightly lower AUC (= 0.764, P = 0.031). The radiological PH score, T_1ρ and T₁ of the liver and T₁ of the spleen, did not show significant diagnostic performance for assessment of CSPH (P > 0.075).

DATA CONCLUSION

Spleen T_1ρ showed a significant correlation with portal pressure and showed improved diagnostic performance for prediction of CSPH compared to radiological assessment. These initial results need confirmation in a larger cohort.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;52:787-794.

Luminal Water Imaging: Comparison With Diffusion-Weighted Imaging (DWI) and PI-RADS for Characterization of Prostate Cancer Aggressiveness

BACKGROUND

Luminal water imaging (LWI), a multicomponent T₂ mapping technique, has shown promise for prostate cancer (PCa) detection and characterization.

PURPOSE

To 1) quantify LWI parameters and apparent diffusion coefficient (ADC) in PCa and benign peripheral zone (PZ) tissues; and 2) evaluate the diagnostic performance of LWI, ADC, and PI-RADS parameters for differentiation between low- and high-grade PCa lesions.

STUDY TYPE

Prospective.

SUBJECTS

Twenty-six PCa patients undergoing prostatectomy (mean age 59 years, range 46-72 years).

FIELD STRENGTH/SEQUENCE

Multiparametric MRI at 3.0T, including diffusion-weighted imaging (DWI) and LWI T₂ mapping.

ASSESSMENT

LWI parameters and ADC were quantified in index PCa lesions and benign PZ.

STATISTICAL TESTS

Differences in MRI parameters between PCa and benign PZ were assessed using Wilcoxon signed tests. Spearman correlation of pathological grade group (GG) with LWI parameters, ADC, and PI-RADS was evaluated. The utility of each of the parameters for differentiation between low-grade (GG ≤2) and high-grade (GG ≥3) PCa was determined by Mann-Whitney U tests and ROC analyses.

RESULTS

Twenty-six index lesions were analyzed (mean size 1.7 ± 0.8 cm, GG: 1 [n = 1; 4%], 2 [n = 14, 54%], 3 [n = 8, 31%], 5 [n = 3, 12%]). LWI parameters and ADC both showed high diagnostic performance for differentiation between benign PZ and PCa (highest area under the curve [AUC] for LWI parameter T_2,short [AUC = 0.98, P < 0.001]). The LWI parameters luminal water fraction (LWF) and amplitude of long T₂ component A_long significantly correlated with GG (r = -0.441, P = 0.024 and r = -0.414, P = 0.036, respectively), while PI-RADS, ADC, and the other LWI parameters did not (P = 0.132-0.869). LWF and A_long also showed significant differences between low-grade and high-grade PCa (AUC = 0.776, P = 0.008 and AUC = 0.758, P = 0.027, respectively). Maximum diagnostic performance for discrimination of high-grade PCa was found with combined LWI parameters (AUC 0.891, P = 0.001).

DATA CONCLUSION

LWI parameters, in particular in combination, showed superior diagnostic performance for differentiation between low-grade and high-grade PCa compared to ADC and PI-RADS assessment. J. Magn. Reson. Imaging 2020;52:271-279.

Multiparametric magnetic resonance imaging shows promising results to assess renal transplant dysfunction with fibrosis

Here we assessed the diagnostic value of a quantitative multiparametric magnetic resonance imaging (mpMRI) protocol for evaluation of renal allograft dysfunction with fibrosis. Twenty-seven renal transplant patients, including 15 with stable functional allografts (eGFR mean 71.5 ml/min/1.73m²), and 12 with chronic dysfunction/established fibrosis (eGFR mean 30.1 ml/min/1.73m²), were enrolled in this prospective single-center study. Sixteen of the patients had renal biopsy (mean 150 days) before the MRI. All patients underwent mpMRI at 1.5T including intravoxel-incoherent motion diffusion-weighted imaging, diffusion tensor imaging, blood oxygen level dependent (BOLD R₂*) and T₁ quantification. True diffusion D, pseudodiffusion D*, perfusion fraction PF, apparent diffusion coefficient (ADC), fractional anisotropy (FA), R₂* and T₁ were calculated for cortex and medulla. ΔT₁ was calculated as (100x(T₁ Cortex-T₁ Medulla)/T₁ Cortex). Test-retest repeatability and inter-observer reproducibility were assessed in four and ten patients, respectively. mpMRI parameters had substantial test-retest and interobserver repeatability (coefficient of variation under 15%), except for medullary PF and D* (coefficient of variation over 25%). Cortical ADC, D, medullary ADC and ΔT₁ were all significantly decreased, while cortical T₁ was significantly elevated in fibrotic allografts. Cortical T₁ showed positive correlation to the Banff fibrosis and tubular atrophy scores. The combination of ΔT₁ and cortical ADC had excellent cross-validated diagnostic performance for detection of chronic dysfunction with fibrosis. Cortical ADC and T₁ had good performance for predicting eGFR decline at 18 months (4 or more ml/min/1.73m²/year). Thus, the combination of cortical ADC and T₁ measurements shows promising results for the non-invasive assessment of renal allograft histology and outcomes.

Volumetric quantitative histogram analysis using diffusion-weighted magnetic resonance imaging to differentiate HCC from other primary liver cancers

OBJECTIVE

To evaluate the ability of volumetric quantitative apparent diffusion coefficient (ADC) histogram parameters and LI-RADS categorization to distinguish hepatocellular carcinoma (HCC) from other primary liver cancers [intrahepatic cholangiocarcinoma (ICC) and combined HCC-ICC].

METHODS

Sixty-three consecutive patients (44 M/19F; mean age 62 years) with primary liver cancers and pre-treatment MRI including diffusion-weighted imaging (DWI) were included in this IRB-approved single-center retrospective study. Tumor type was categorized pathologically. Qualitative tumor features and LI-RADS categorization were assessed by 2 independent observers. Lesion volume of interest measurements (VOIs) were placed on ADC maps to extract first-order radiomics (histogram) features. ADC histogram metrics and qualitative findings were compared. Binary logistic regression and AUROC were used to assess performance for distinction of HCC from ICC and combined tumors.

RESULTS

Sixty-five lesions (HCC, n = 36; ICC, n = 17; and combined tumor, n = 12) were assessed. Only enhancement pattern (p < 0.015) and capsule were useful for tumor diagnosis (p < 0.014). ADC 5th/10th/95th percentiles were significant for discrimination between each tumor types (all p values < 0.05). Accuracy of LI-RADS for HCC diagnosis was 76.9% (p < 0.0001) and 69.2% (p = 0.001) for both observers. The combination of male gender, LI-RADS, and ADC 5th percentile yielded an AUROC/sensitivity/specificity/accuracy of 0.90/79.3%/88.9%/81.5% and 0.89/86.2%/77.8%/80.0% (all p values < 0.027) for the diagnosis of HCC compared to ICC and combined tumors for both observers, respectively.

CONCLUSION

The combination of quantitative ADC histogram parameters and LI-RADS categorization yielded the best prediction accuracy for distinction of HCC compared to ICC and combined HCC-ICC.

T1ρ mapping for assessment of renal allograft fibrosis

BACKGROUND

There is an unmet need for noninvasive methods to diagnose and stage renal allograft fibrosis.

PURPOSE

To investigate the utility of T_1ρ measured with MRI for the assessment of fibrosis in renal allografts.

STUDY TYPE

Institutional Review Board (IRB)-approved prospective.

SUBJECTS

Fifteen patients with stable functional allograft (M/F 9/6, mean age 56 years) and 12 patients with allograft dysfunction and established fibrosis (M/F 6/6, mean age 51 years).

FIELD STRENGTH/SEQUENCE

T_1ρ imaging at 1.5T using a custom-developed sequence.

ASSESSMENT

Average T_1ρ in the cortex and medulla was quantified and T_1ρ repeatability (expressed by the coefficient of variation [CV]) was measured in four patients.

STATISTICAL TESTS

Differences in T_1ρ values between the 2 groups were assessed using Mann-Whitney U-tests. Diagnostic performance of T_1ρ for differentiation between functional and fibrotic allografts was evaluated using receiver operating characteristic (ROC) analysis. Spearman correlations of T_1ρ with Masson's trichrome-stained fractions and serum estimated glomerular filtration rate (eGFR) were assessed.

RESULTS

Higher T_1ρ repeatability was found for cortex compared with medulla (mean CV T_1ρ cortex 7.4%, medulla 13.3%). T_1ρ values were significantly higher in the cortex of fibrotic vs. functional allografts (111.8 ± 17.2 msec vs. 99.0 ± 11.0 msec, P = 0.027), while there was no difference in medullary T_1ρ values (122.6 ± 20.8 msec vs. 124.3 ± 20.8 msec, P = 0.789). Cortical T_1ρ significantly correlated with Masson's trichrome-stained fractions (r = 0.515, P = 0.044) and eGFR (r = -0.546, P = 0.004), and demonstrated an area under the curve (AUC) of 0.77 for differentiating between functional and fibrotic allografts (sensitivity and specificity of 75.0% and 86.7%, using threshold of 106.9 msec).

DATA CONCLUSION

Our preliminary results suggest that T_1ρ is a potential imaging biomarker of renal allograft fibrosis. These results should be verified in a larger study.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1085-1091.

Diffusion and perfusion MRI quantification in ileal Crohn's disease

OBJECTIVES

To quantify intravoxel incoherent motion (IVIM)-DWI and dynamic contrast-enhanced (DCE)-MRI parameters in normal and abnormal ileal segments in Crohn's disease (CD) patients and to assess the association of these parameters with clinical and MRI-based measurements of CD activity.

METHODS

In this prospective study, 27 CD patients (M/F 18/9, mean age 42 years) underwent MR enterography, including IVIM-DWI and DCE-MRI. IVIM-DWI and DCE-MRI parameters were quantified in normal and abnormal small bowel segments, the latter identified by the presence of inflammatory changes. MRI parameter differences between normal and abnormal bowel were tested using Wilcoxon signed-rank tests. IVIM-DWI and DCE-MRI parameters were correlated with clinical data (C-reactive protein, Harvey-Bradshaw Index), conventional MRI parameters (wall thickness, length of involvement) and MRI activity scores (MaRIA, Clermont). Diagnostic performance of (combined) parameters for differentiation between normal and abnormal bowel was determined using ROC analysis.

RESULTS

The DCE-MRI parameters peak concentration C_peak, upslope, area-under-the-curve at 60s (AUC60), K^trans and v_e were significantly increased (p<0.023), while IVIM-DWI parameters perfusion fraction (PF) and ADC were significantly decreased (p<0.001) in abnormal bowel segments. None of the DCE-MRI and IVIM-DWI parameters correlated with clinical parameters (p>0.105). DCE-MRI parameters exhibited multiple significant correlations with wall thickness (C_peak, upslope, AUC60, K^trans; r range 0.431-0.664, p<0.025) and MaRIA/Clermont scores (C_peak, AUC60, K^trans; r range 0.441-0.617, p<0.021). Combined K^trans+v_e+PF+ADC showed highest AUC (0.963) for differentiation between normal and abnormal bowel, while ADC performed best for individual parameters (AUC=0.800).

CONCLUSIONS

DCE-MRI and IVIM-DWI, particularly when used in combination, are promising for non-invasive evaluation of small bowel CD.

KEY POINTS

• IVIM-DWI and DCE-MRI parameters were significantly different between normal and abnormal bowel segments in CD patients. • DCE-MRI parameters showed a significant association with wall thickness and MRI activity scores. • Combination of IVIM-DWI and DCE-MRI parameters led to the highest diagnostic performance for differentiation between normal and abnormal bowel segments, while ADC showed the highest diagnostic performance of individual parameters.

Improved Evaluation of Antivascular Cancer Therapy Using Constrained Tracer-Kinetic Modeling for Multiagent Dynamic Contrast-Enhanced MRI

Dynamic contrast-enhanced MRI (DCE-MRI) is a promising technique for assessing the response of tumor vasculature to antivascular therapies. Multiagent DCE-MRI employs a combination of low and high molecular weight contrast agents, which potentially improves the accuracy of estimation of tumor hemodynamic and vascular permeability parameters. In this study, we used multiagent DCE-MRI to assess changes in tumor hemodynamics and vascular permeability after vascular-disrupting therapy. Multiagent DCE-MRI (sequential injection of G5 dendrimer, G2 dendrimer, and Gd-DOTA) was performed in tumor-bearing mice before, 2 and 24 hours after treatment with vascular disrupting agent DMXAA or placebo. Constrained DCE-MRI gamma capillary transit time modeling was used to estimate flow F, blood volume fraction v_b, mean capillary transit time t_c, bolus arrival time t_d, extracellular extravascular fraction v_e, vascular heterogeneity index α^-1 (all identical between agents) and extraction fraction E (reflective of permeability), and transfer constant K^trans (both agent-specific) in perfused pixels. F, v_b, and α^-1 decreased at both time points after DMXAA, whereas t_c increased. E (G2 and G5) showed an initial increase, after which, both parameters restored. K^trans (G2 and Gd-DOTA) decreased at both time points after treatment. In the control, placebo-treated animals, only F, t_c, and K^trans Gd-DOTA showed significant changes. Histologic perfused tumor fraction was significantly lower in DMXAA-treated versus control animals. Our results show how multiagent tracer-kinetic modeling can accurately determine the effects of vascular-disrupting therapy by separating simultaneous changes in tumor hemodynamics and vascular permeability.Significance: These findings describe a new approach to measure separately the effects of antivascular therapy on tumor hemodynamics and vascular permeability, which could help more rapidly and accurately assess the efficacy of experimental therapy of this class. Cancer Res; 78(6); 1561-70. ©2018 AACR.

Advanced Diffusion-weighted Imaging Modeling for Prostate Cancer Characterization: Correlation with Quantitative Histopathologic Tumor Tissue Composition-A Hypothesis-generating Study

Purpose To correlate quantitative diffusion-weighted imaging (DWI) parameters derived from conventional monoexponential DWI, stretched exponential DWI, diffusion kurtosis imaging (DKI), and diffusion-tensor imaging (DTI) with quantitative histopathologic tumor tissue composition in prostate cancer in a preliminary hypothesis-generating study. Materials and Methods This retrospective institutional review board-approved study included 24 patients with prostate cancer (mean age, 63 years) who underwent magnetic resonance (MR) imaging, including high-b-value DWI and DTI at 3.0 T, before prostatectomy. The following parameters were calculated in index tumors and nontumoral peripheral zone (PZ): apparent diffusion coefficient (ADC) obtained with monoexponential fit (ADC_ME), ADC obtained with stretched exponential modeling (ADC_SE), anomalous exponent (α) obtained at stretched exponential DWI, ADC obtained with DKI modeling (ADC_DKI), kurtosis with DKI, ADC obtained with DTI (ADC_DTI), and fractional anisotropy (FA) at DTI. Parameters in prostate cancer and PZ were compared by using paired Student t tests. Pearson correlations between tumor DWI and quantitative histologic parameters (nuclear, cytoplasmic, cellular, stromal, luminal fractions) were determined. Results All DWI parameters were significantly different between prostate cancer and PZ (P < .012). ADC_ME, ADC_SE, and ADC_DKI all showed significant negative correlation with cytoplasmic and cellular fractions (r = -0.546 to -0.435; P < .034) and positive correlation with stromal fractions (r = 0.619-0.669; P < .001). ADC_DTI and FA showed correlation only with stromal fraction (r = 0.512 and -0.413, respectively; P < .045). α did not correlate with histologic parameters, whereas kurtosis showed significant correlations with histopathologic parameters (r = 0.487, 0.485, -0.422 for cytoplasmic, cellular, and stromal fractions, respectively; P < .040). Conclusion Advanced DWI methods showed significant correlations with histopathologic tissue composition in prostate cancer. These findings should be validated in a larger study. ^© RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on November 10, 2017.

DCE-MRI of the prostate using shutter-speed vs. Tofts model for tumor characterization and assessment of aggressiveness

PURPOSE

To quantify Tofts model (TM) and shutter-speed model (SSM) perfusion parameters in prostate cancer (PCa) and noncancerous peripheral zone (PZ) and to compare the diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to Prostate Imaging and Reporting and Data System (PI-RADS) classification for the assessment of PCa aggressiveness.

MATERIALS AND METHODS

Fifty PCa patients (mean age 60 years old) who underwent MRI at 3.0T followed by prostatectomy were included in this Institutional Review Board-approved retrospective study. DCE-MRI parameters (K^trans , v_e , k_ep [TM&SSM] and intracellular water molecule lifetime τ_i [SSM]) were determined in PCa and PZ. Differences in DCE-MRI parameters between PCa and PZ, and between models were assessed using Wilcoxon signed-rank tests. Receiver operating characteristic (ROC) analysis for differentiation between PCa and PZ was performed for individual and combined DCE-MRI parameters. Diagnostic performance of DCE-MRI parameters for identification of aggressive PCa (Gleason ≥8, grade group [GG] ≥3 or pathology stage pT3) was assessed using ROC analysis and compared with PI-RADSv2 scores.

RESULTS

DCE-MRI parameters were significantly different between TM and SSM and between PZ and PCa (P < 0.037). Diagnostic performances of TM and SSM for differentiation of PCa from PZ were similar (highest AUC TM: K^trans +k_ep 0.76, SSM: τ_i +k_ep 0.80). PI-RADS outperformed TM and SSM DCE-MRI for identification of Gleason ≥8 lesions (AUC PI-RADS: 0.91, highest AUC DCE-MRI: K^trans +τ_i SSM 0.61, P = 0.002). The diagnostic performance of PI-RADS and DCE-MRI for identification of GG ≥3 and pT3 PCa was not significantly different (P > 0.213).

CONCLUSION

SSM DCE-MRI did not increase the diagnostic performance of DCE-MRI for PCa characterization. PI-RADS outperformed both TM and SSM DCE-MRI for identification of aggressive cancer.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:837-849.

Comparison Between 3-Scan Trace and Diagonal Body Diffusion-Weighted Imaging Acquisitions: A Phantom and Volunteer Study

Diagonal diffusion-weighted imaging (dDWI) uses simultaneous maximized application of 3 orthogonal gradient systems as opposed to sequential acquisition in 3 directions in conventional 3-scan trace DWI (tDWI). Several theoretical advantages of dDWI vs. tDWI include reduced artifacts and increased sharpness. We compared apparent diffusion coefficient (ADC) quantification and image quality between monopolar dDWI and tDWI in a dedicated diffusion phantom (b = 0/500/900/2000 s/mm²) and in the abdomen (b = 50/400/800 s/mm²) and pelvis (b = 50/1000/1600 s/mm²) of 2 male volunteers at 1.5 T and 3.0 T. Phantom estimated signal-to-noise ratio (eSNR) was also measured. Two independent observers assessed the image quality on a 5-point scale. In the phantom, image quality was similar between tDWI and dDWI, with equivalent ADC quantification (mean coefficient of variation [CV] between sequences: 1.4% ± 1.2% at 1.5 T and 0.7% ± 0.7% at 3.0 T). Phantom eSNR was similar for both tDWI and dDWI, except for a significantly lower eSNR for b900 of dDWI at 3.0 T (P = .006). In the volunteers, the CV values between tDWI and dDWI were higher than those in the phantom (CV range: abdominal organs, 1.3%-13.3%; pelvic organs, 0.6%-5.7%). A trend toward significant better image quality for dDWI compared with tDWI was observed for b800 (abdomen) at 3.0 T and for b1000 and b1600 (pelvis) at 1.5 T (P = .063 to .066). Our data suggest that dDWI may provide better image quality than tDWI without affecting ADC quantification, needing confirmation in a future clinical study.

Quantitative Multi-Parametric Magnetic Resonance Imaging of Tumor Response to Photodynamic Therapy

Objective

The aim of this study was to characterize response to photodynamic therapy (PDT) in a mouse cancer model using a multi-parametric quantitative MRI protocol and to identify MR parameters as potential biomarkers for early assessment of treatment outcome.

Methods

CT26.WT colon carcinoma tumors were grown subcutaneously in the hind limb of BALB/c mice. Therapy consisted of intravenous injection of the photosensitizer Bremachlorin, followed by 10 min laser illumination (200 mW/cm²) of the tumor 6 h post injection. MRI at 7 T was performed at baseline, directly after PDT, as well as at 24 h, and 72 h. Tumor relaxation time constants (T₁ and T₂) and apparent diffusion coefficient (ADC) were quantified at each time point. Additionally, Gd-DOTA dynamic contrast-enhanced (DCE) MRI was performed to estimate transfer constants (K^trans) and volume fractions of the extravascular extracellular space (v_e) using standard Tofts-Kermode tracer kinetic modeling. At the end of the experiment, tumor viability was characterized by histology using NADH-diaphorase staining.

Results

The therapy induced extensive cell death in the tumor and resulted in significant reduction in tumor growth, as compared to untreated controls. Tumor T₁ and T₂ relaxation times remained unchanged up to 24 h, but decreased at 72 h after treatment. Tumor ADC values significantly increased at 24 h and 72 h. DCE-MRI derived tracer kinetic parameters displayed an early response to the treatment. Directly after PDT complete vascular shutdown was observed in large parts of the tumors and reduced uptake (decreased K^trans) in remaining tumor tissue. At 24 h, contrast uptake in most tumors was essentially absent. Out of 5 animals that were monitored for 2 weeks after treatment, 3 had tumor recurrence, in locations that showed strong contrast uptake at 72 h.

Conclusion

DCE-MRI is an effective tool for visualization of vascular effects directly after PDT. Endogenous contrast parameters T₁, T₂, and ADC, measured at 24 to 72 h after PDT, are also potential biomarkers for evaluation of therapy outcome.

Intravoxel incoherent motion diffusion-weighted imaging of hepatocellular carcinoma: Is there a correlation with flow and perfusion metrics obtained with dynamic contrast-enhanced MRI?

PURPOSE

To assess the correlation between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) metrics in hepatocellular carcinoma (HCC) and liver parenchyma.

MATERIALS AND METHODS

Twenty-five patients with HCC (M/F 23/2, mean age 58 years) underwent abdominal MRI at 1.5 or 3.0T, including IVIM-DWI (with 16 b-values) and DCE-MRI (3D FLASH sequence, mean temporal resolution of 2.3 sec). IVIM-DWI parameters (pseudodiffusion coefficient, D*, diffusion coefficient, D, and perfusion fraction, PF) were quantified in HCC lesions and liver parenchyma using a Bayesian fitting algorithm. DCE-MRI parameters (arterial flow, Fa , portal flow, Fp , total flow, Ft , mean transit time, MTT, distribution volume, DV, and arterial fraction, ART) were quantified using a dual-input single-compartment model. Correlations between IVIM-DWI and DCE-MRI parameters were assessed using a Spearman correlation test.

RESULTS

Thirty-three HCC lesions (average size 5.0 ± 3.6 cm) were analyzed. D, D*, and PF were all significantly lower in HCC vs. liver (P < 0.05). Significantly higher Fa and ART and lower Fp were observed in HCC vs. liver (P < 0.001). Significant moderate to strong negative correlations were observed between ART and D* (r = -0.443, P = 0.028), ART and PF (r = -0.536, P = 0.006), ART and PFxD* (r = -0.655, P < 0.001), Fa and PF (r = 0.455, P = 0.023), and Fa and PFxD* (r = -0.475, P = 0.018) in liver parenchyma. There was no significant correlation between IVIM-DWI and DCE-MRI metrics in HCC lesions.

CONCLUSION

IVIM-DWI and DCE-MRI provide nonredundant information in HCC, while they correlate in liver parenchyma. These findings may be secondary to predominant portal inflow in the liver and tortuous vasculature and tissue heterogeneity in tumors. J. MAGN. RESON. IMAGING 2016;44:856-864.