Quantitative Dynamic Contrast-enhanced Magnetic Resonance Research Articles

Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging and Positron Emission Tomography (PET) for Distinguishing Metastatic Lymph Nodes from Nonmetastatic Among Patients with Rectal Cancer: A Systematic Review and Meta-Analysis

Abstract Objective The objective of this research was to assess the proficiency of quantitative dynamic contrast-enhanced magnetic resonance imaging (QDCE-MRI) and positron emission tomography (PET) imaging in distinguishing between metastatic and nonmetastatic lymph nodes in cases of rectal carcinoma. Method This meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses standards. Two independent reviewers systematically searched databases including PubMed, Embase, Web of Science, and the Cochrane Library. The research took place in July 2022, with no restriction on the initial date of publication. For the analysis, we utilized Stata software (version 16.0), Review Manager (version 5.3), and the Open Meta-Analyst computational tool. Results A total of 19 studies consisting of 1,451 patients were included in the current meta-analysis. The differences between metastatic and nonmetastatic lymph node parameters were significant by using short axis and Ktrans (6.9 ± 4 vs. 5.4 ± 0.5, 0.22 ± 0.1 vs. 0.14 ± 0.1, respectively). Contrast-enhanced MRI (CE-MRI) showed 73% sensitivity, 71% specificity, and 79% accuracy in detecting metastatic lymph nodes among rectal cancer patients based on six included studies (n = 530). The overall sensitivity, specificity, and accuracy of QDCE-MRI using Ktrans was calculated to be 80, 79, and 80%, respectively. Furthermore, PET-computed tomography (CT) showed a sensitivity of 80%, specificity of 91%, and accuracy of 86% in distinguishing metastatic lymph nodes. Quality utility analysis showed that using CE-MRI, QDCE-MRI, and PET-CT would increase the posttest probability to 69, 73, and 85%, respectively. Conclusion QDCE-MRI demonstrates a commendable sensitivity and specificity, but slightly overshadowed by the higher specificity of PET-CT at 91%, despite comparable sensitivities. However, the heterogeneity in PET-CT sensitivity across studies and its high specificity indicate variability that can influence clinical decision-making. Thus, combining these imaging techniques and perhaps newer methods like PET/MRI could enhance diagnostic accuracy, reduce variability, and improve patient management strategies in rectal cancer.

Automatic removal of large blood vasculature for objective assessment of brain tumors using quantitative dynamic contrast-enhanced magnetic resonance imaging.

The presence of a normal large blood vessel (LBV) in a tumor region can impact the evaluation of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and tumor classification. Hence, there is a need for automatic removal of LBVs from brain tissues including intratumoral regions for achieving an objective assessment of tumors. This retrospective study included 103 histopathologically confirmed brain tumor patients who underwent MRI, including DCE-MRI data acquisition. Quantitative DCE-MRI analysis was performed for computing various parameters such as wash-out slope (Slope-2), relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), blood plasma volume fraction (Vp), and volume transfer constant (Ktrans). An approach based on data-clustering algorithm, morphological operations, and quantitative DCE-MRI maps was proposed for the segmentation of normal LBVs in brain tissues, including the tumor region. Here, three widely used data-clustering algorithms were evaluated on two types of quantitative maps: (a) Slope-2, and (b) a new proposed combination of rCBV and Slope-2 maps. Fluid-attenuated inversion recovery-MRI hyperintense lesionswere also automatically segmented using deep learning-based architecture. The accuracy of LBV segmentation was qualitatively assessed blindly by two experienced observers, and Likert scoring was also obtained from each individual and compared using Cohen's Kappa test, and multiple statistical features from quantitative DCE-MRI parameters were obtained in the segmented tumor. t-test and receiver operating characteristic (ROC) curve analysis were performed for comparing the effect of removal of LBVs on parameters as well as on tumor grading. k-means clustering exhibited better accuracy and computational efficiency. Tumors, in particular high-grade gliomas (HGGs), showed a high contrast compared with normal tissues (relative % difference = 18.5%) on quantitative maps after the removal of LBVs. Statistical features (95th percentile values) of all parameters in the tumor region showed a statistically significant difference (p< 0.05) between with and without LBV maps. Similar results were obtained for the ROC curve analysis for differentiation between low-grade gliomas and HGGs. Moreover, after the removal of LBVs, the rCBV, rCBF, and Vp maps show better visualization of tumor regions.

Bi-regional dynamic contrast-enhanced MRI for prediction of microvascular invasion in solitary BCLC stage A hepatocellular carcinoma

ObjectivesTo construct a combined model based on bi-regional quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), as well as clinical-radiological (CR) features for predicting microvascular invasion (MVI) in solitary Barcelona Clinic Liver Cancer (BCLC) stage A hepatocellular carcinoma (HCC), and to assess its ability for stratifying the risk of recurrence after hepatectomy.MethodsPatients with solitary BCLC stage A HCC were prospective collected and randomly divided into training and validation sets. DCE perfusion parameters were obtained both in intra-tumoral region (ITR) and peritumoral region (PTR). Combined DCE perfusion parameters (CDCE) were constructed to predict MVI. The combined model incorporating CDCE and CR features was developed and evaluated. Kaplan–Meier method was used to investigate the prognostic significance of the model and the survival benefits of different hepatectomy approaches.ResultsA total of 133 patients were included. Total blood flow in ITR and arterial fraction in PTR exhibited the best predictive performance for MVI with areas under the curve (AUCs) of 0.790 and 0.792, respectively. CDCE achieved AUCs of 0.868 (training set) and 0.857 (validation set). A combined model integrated with the α-fetoprotein, corona enhancement, two-trait predictor of venous invasion, and CDCE could improve the discrimination ability to AUCs of 0.966 (training set) and 0.937 (validation set). The combined model could stratify the prognosis of HCC patients. Anatomical resection was associated with a better prognosis in the high-risk group (p < 0.05).ConclusionThe combined model integrating DCE perfusion parameters and CR features could be used for MVI prediction in HCC patients and assist clinical decision-making.Critical relevance statementThe combined model incorporating bi-regional DCE-MRI perfusion parameters and CR features predicted MVI preoperatively, which could stratify the risk of recurrence and aid in optimizing treatment strategies.Key PointsMicrovascular invasion (MVI) is a significant predictor of prognosis for hepatocellular carcinoma (HCC).Quantitative DCE-MRI could predict MVI in solitary BCLC stage A HCC; the combined model improved performance.The combined model could help stratify the risk of recurrence and aid treatment planning.Graphical

Quantitative dynamic contrast-enhanced magnetic resonance imaging in head and neck cancer: A systematic comparison of different modelling approaches

Background and purposeDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) describes tissue microvasculature and has prognostic and predictive potential in radiotherapy for head and neck cancer (HNC). However, lack in standardization of DCE-MRI hinders comparison of studies and clinical implementation. This study investigated the accuracy and robustness of the population arterial input function (AIF), correlations between pharmacokinetic parameters and their association to T stage and human papillomavirus (HPV) status for HNC. Materials and methodsDCE-MRI was acquired for 44 HNC patients. Population AIFs were calculated with six different approaches. DCE-MRI was analysed in primary and lymph node tumours using Tofts model (TM) with population AIFs and individual AIFs, extended TM (ETM) with individual AIFs, Brix model (BM), and areas under the curve (AUCs). Intraclass correlation, concordance correlation, Pearson correlation and Whitney Mann U test helped examining the robustness and accuracy of population AIF, correlations between DCE-MRI parameters and their association to T stage and HPV status, respectively. ResultsThe population AIF was robust but differed from individual AIFs. There was significant correlation between KtransTM/ETM and ve, TM/ETM, and KtransTM/ETM and Kep, TM/ETM. ABrix and AUCs correlated for lymph nodes. Kep, Brix correlated with ABrix, KtransTM/ETM and Kep, TM/ETM for primary tumours. Kep, TM significantly decreased with increasing T stage. Both the correlations and the parameters’ association to T stage were stronger for HPV negative lesions. ConclusionsIndividual AIF was preferred for accurate pharmacokinetic modelling of DCE-MRI. DCE-MRI parameters and their correlations were affected by the lesion type, HPV status and T staging.

Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Parameters Could Predict International Society of Urological Pathology Risk Groups of Prostate Cancers on Radical Prostatectomy.

The International Society of Urological Pathology (ISUP) grade and positive surgical margins (PSMs) after radical prostatectomy (RP) may reflect the prognosis of prostate cancer (PCa) patients. This study aimed to investigate whether DCE-MRI parameters (i.e., Ktrans, kep, and IAUC) could predict ISUP grade and PSMs after RP. Forty-five PCa patients underwent preoperative DCE-MRI. The clinical characteristics and DCE-MRI parameters of the 45 patients were compared between the low- and high-risk (i.e., ISUP grades III-V) groups and between patients with or without PSMs after RP. Multivariate logistic regression analysis was used to identify the significant predictors of placement in the high-risk group and PSMs. The DCE parameter Ktrans-max was significantly higher in the high-risk group than in the low-risk group (p = 0.028) and was also a significant predictor of placement in the high-risk group (odds ratio [OR] = 1.032, 95% confidence interval [CI] = 1.005-1.060, p = 0.021). Patients with PSMs had significantly higher prostate-specific antigen (PSA) titers, positive biopsy core percentages, Ktrans-max, kep-median, and kep-max than others (all p < 0.05). Of these, positive biopsy core percentage (OR = 1.035, 95% CI = 1.003-1.068, p = 0.032) and kep-max (OR = 1.078, 95% CI = 1.012-1.148, p = 0.020) were significant predictors of PSMs. Preoperative DCE-MRI parameters, specifically Ktrans-max and kep-max, could potentially serve as preoperative imaging biomarkers for postoperative PCa prognosis based on their predictability of PCa risk group and PSM on RP, respectively.

Nomogram based on quantitative dynamic contrast-enhanced magnetic resonance imaging, apparent diffusion coefficient, and clinicopathological features for early prediction of pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy.

The aim of this study was to develop two nomograms for predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) for breast cancer based on quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), and clinicopathological characteristics at two time-points: before and after two cycles of NACT, respectively. 3.0 T MRI scans were performed before and after 2 cycles of NACT in 215 patients. A total of 74 female patients with stage II-III breast cancer were included. According to univariate and multivariate logistic regression analysis, nomogram model 1 and nomogram model 2 were developed based on the independent predictors for pCR before and after 2 cycles of NACT, respectively. Nomogram performance was assessed with the area under the receiver operating characteristic curve (AUC) and calibration slope. The independent predictors of pCR were different at the two time points. Both nomograms were found to effectively predict pCR: nomogram model 2 based on Ki67, ΔKtrans%, and ΔADC% after 2 cycles of NACT showed better predictive discrimination [AUC =0.900 (0.829, 0.970) vs. 0.833 (0.736, 0.930)] and calibration ability (mean absolute error of the agreement: 0.017 vs. 0.051) compared to nomogram model 1 based on pre-NACT HER2, Ki67, and Ktrans. Nomograms based on quantitative DCE-MRI parameters, ADC, and clinicopathological characteristics can predict pCR in breast cancer and facilitate individualized decision-making for NACT.

Intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging for neoadjuvant chemotherapy response evaluation in patients with osteosarcoma

ObjectivesThis study aims to explore the role of quantitative intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters in characterizing changes in osteosarcoma (OS) patients receiving neoadjuvant chemotherapy (NACT). Material and methodsTwenty-seven patients with histologically proven OS were examined prospectively and divided into good-response group (n = 14) and poor-response group (n = 13). IVIM and DCE-MRI sequences were performed at baseline (pre-NACT) and after three cycles of NACT (post-NACT). Apparent diffusion coefficient (ADC) and IVIM bi-exponential model parameters, including diffusion coefficient (D-Bi), perfusion coefficient (D*-Bi), and perfusion fraction (f-Bi), were evaluated. DCE-MRI parameters, including quantitative parameters (volume transfer constant [Ktrans], elimination rate constant [Kep], and extravascular extracellular space volume ratio [Ve]) and semi-quantitative parameters (initial area under the gadolinium curve [IAUGC] and contrast enhancement rate [CER]), were also measured. ResultsD-Bi, D*-Bi, and f-Bi post-NACT and ΔD-Bi were statistically different between the good- and poor-response groups (Z1 = − 3.348, Z2 = − 2.572, Z3 = − 2.378, t = 2.235, P < 0.05). ADC, f-Bi, Ktrans, IAUGC, Kep, and CER post-NACT were statistically different from those at pre-NACT (P < 0.05). The receiver operating characteristic curve showed that f-Bi post-NACT had the best performance among all parameters, with area under the curve of 0.769, sensitivity of 1, and specificity of 0.538. The correlation analysis showed that the efficacy of NACT was negatively correlated with D-Bi, D*-Bi post-NACT, and ΔD-Bi (r1 = − 0.530, r2 = − 0.411, r3 = − 0.434, P1 = 0.008, P2 = 0.046, P3 = 0.034) and significantly positively correlated with f-Bi post-NACT (r = 0.482, P = 0.017). ConclusionsThe IVIM quantitative parameters D-Bi, D*-Bi, and f-Bi post-NACT and ΔD-Bi could be used as noninvasive imaging biomarkers for early response assessment of NACT in OS.

Diagnostic efficacy of diffusion-weighted imaging and semiquantitative and quantitative dynamic contrast-enhanced magnetic resonance imaging in salivary gland tumors.

Increased use of functional magnetic resonance imaging (MRI) methods such as diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI consisting of sequential contrast series, allows us to obtain more information on the microstructure, cellularity, interstitial distance, and vascularity of tumors, which has increased the discrimination power for benign and malignant salivary gland tumors (SGTs). In the last few years, quantitative DCE MRI data containing T1 perfusion parameters (Ktrans, Kep and Ve), were reported to contribute to the differentiation of benign or malignant subtypes in SGTs. To evaluate the diagnostic efficacy of DWI and semiquantitative and quantitative perfusion MRI parameters in SGTs. Diffusion MRI [apparent diffusion coefficient (ADC) value] with a 1.5 T MR machine, semiquantitative perfusion MRI [time intensity curve (TIC) pattern], and quantitative perfusion MRI examinations (Ktrans, Kep and Ve) of 73 tumors in 67 patients with histopathological diagnosis performed from 2017 to 2021 were retrospectively evaluated. In the ADC value and semiquantitative perfusion MRI measurements, cystic components of the tumors were not considered, and the region of interest (ROI) was manually placed through the widest axial section of the tumor. TIC patterns were divided into four groups: Type A = Tpeak > 120 s; type B = Tpeak ≤ 120 s, washout ratio (WR) ≥ 30%; type C = Tpeak ≤ 120 s, WR < 30%; and type D = flat TIC. For the quantitative perfusion MRI analysis, a 3D ROI was placed in the largest solid component of the tumor, and the Ktrans, Kep and Ve values were automatically generated. The majority of SGTs were located in the parotid glands (86.3%). Of all the SGTs, 68.5% were benign and 31.5% were malignant. Significant differences were found for ADC values among pleomorphic adenomas (PMAs), Warthin's tumors (WTs), and malignant tumors (MTs) (P < 0.001). PMAs had type A and WTs had type B TIC pattern while the vast majority of MTs and other benign tumors (OBTs) (54.5% and 45.5%, respectively) displayed type C TIC pattern. PMAs showed no washout, while the highest mean WR was observed in WTs (59% ± 11%). Ktrans values of PMAs, WTs, OBTs, and MTs were not significantly different. Kep values of PMAs and WTs were significantly different from those of OBTs and MTs. Mean Ve value of WTs was significantly different from those of PMAs, OBTs, and MTs (P < 0.001). The use of quantitative DCE parameters along with diffusion MRI and semiquantitative contrast-enhanced MRI in SGTs could improve the diagnostic accuracy.

Intravoxel incoherent motion diffusion-weighted imaging in quantitative evaluation of Ileal Crohn's disease – A comparison with dynamic contrast-enhanced magnetic resonance imaging and ileocolonoscopy

ObjectivesTo investigate the prospective role of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in evaluating terminal ileal Crohn's disease (CD) inflammation quantitatively, compared with quantitative dynamic contrastenhanced magnetic resonance imaging (DCE-MRI) and ileocolonoscopic segmental score. MethodsFifty CD patients underwent magnetic resonance enterography (MRE) including IVIM-DWI and quantitative DCE-MRI from Jan. 2017 to Nov. 2019. ADC, D, D* and f value of IVIM-DWI and Ktrans, Kep, and Ve value of DCE-MRI in normal (n = 50) and inflamed bowel segments (n = 50), defined during the clinical MRI analysis, were calculated and compared using Wilcoxon signed-rank tests respectively.Receiver operating characteristic (ROC) analysis was performed. Correlations between IVIM-DWI and DCE-MRI parameters in comparison with ileocolonoscopic segmental score were assessed using Spearman's rank correlation analysis. ResultsFor IVIM-DWI, ADC, D, D* and f value showed significant differences respectively between normal and inflamed bowel segments (p < 0.05). ADC value presented the highest diagnostic accuracy (AUC = 0.813) and sensitivity (92%), and D value presented the highest specificity (84%) for the evaluation of inflamed bowel segments. For DCE-MRI, Ktrans value presented the highest diagnostic accuracy (AUC = 0.835), the highest sensitivity for Kep value (88%) and the highest specificity for Ve value (96%). ADC, f and Ktrans value had high correlations with ileocolonoscopic score respectively (r = −0.739-0.876, p < 0.01). The logarithm of normalized signal intensity/b-values for IVIM-DWI could also indicate directly the evident difference between the normal and inflamed bowel segments of terminal ileal CD. ConclusionIVIM-DWI will be another promising noninvasive tool to provide precise quantitative-indicators in evaluating inflamed bowel segments of terminal ileal CD with little contrast-agent damage worries.

Arterial input function for quantitative dynamic contrast-enhanced MRI to diagnose prostate cancer.

PURPOSE This study aims to analyze the ability of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to distinguish between prostate cancer (PCa) and benign lesions in transition zone (TZ) and peripheral zone (PZ) using different methods for arterial input function (AIF) determination. Study endpoints are identification of a standard AIF method and optimal quantitative perfusion parameters for PCa detection. METHODS DCE image data of 50 consecutive patients with PCa who underwent multiparametric MRI were analyzed retrospectively with three different methods of AIF acquisition. First, a region of interest was manually defined in an artery (AIFm); second, an automated algorithm was used (AIFa); and third, a population-based AIF (AIFp) was applied. Values of quantitative parameters after Tofts (Ktrans, ve, and kep) in PCa, PZ, and TZ in the three different AIFs were analyzed. RESULTS Ktrans and kep were significantly higher in PCa than in benign tissue independent from the AIF method. Whereas in PZ, Ktrans and kep could differentiate PCa (P < .001), in TZ only kep using AIFpdemonstrated a significant difference (P = .039). The correlations of the perfusion parameters that resulted from AIFm and AIFa were higher than those that resulted from AIFp, and the absolute values of Ktrans, kep, and ve were significantly lower when using AIFp. The values of quantitative perfusion parameters for PCa were similar regardless of whether PCa was located in PZ or TZ. CONCLUSION Ktrans and kep were able to differentiate PCa from benign PZ independent of the AIF method. AIFaseems to be the most feasible method of AIF determination in clinical routine. For TZ, none of the quantitative perfusion parameters provided satisfying results.

Preoperative prediction of extramural venous invasion in rectal cancer by dynamic contrast-enhanced and diffusion weighted MRI: a preliminary study

BackgroundTo explore the value of the quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in assessing preoperative extramural venous invasion (EMVI) in rectal cancer.MethodsEighty-two rectal adenocarcinoma patients who had underwent MRI preoperatively were enrolled in this study. The differences in quantitative DCE-MRI and DWI parameters including Krans, Kep and ADC values were analyzed between MR-detected EMVI (mrEMVI)-positive and -negative groups. Multivariate logistic regression analysis was performed to build the combined prediction model for pathologic EMVI (pEMVI) with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) curve.ResultsOf the 82 patients, 24 were mrEMVI-positive and 58 were -negative. In the mrEMVI positive group, the Ktrans and Kep values were significantly higher than those in the mrEMVI negative group (P < 0.01), but the ADC values were significantly lower (P < 0.01). A negative correlation was observed between the Ktrans vs ADC values and Kep vs ADC values in patients with rectal cancer. Among the four quantitative parameters, Ktrans and ADC value were independently associated with mrEMVI by multivariate logistic regression analysis. ROC analysis showed that combined prediction model based on quantitative DCE parameters and ADC values had a good prediction efficiency for pEMVI in rectal cancer.ConclusionThe quantitative DCE-MRI parameters, Krans, Kep and ADC values play important role in predicting EMVI of rectal cancer, with Ktrans and ADC value being independent predictors of EMVI in rectal cancer.

Feasibility of Intravoxel Incoherent Motion (IVIM) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in Differentiation of Benign Parotid Gland Tumors.

Simple SummaryMultiparametric magnetic resonance imaging gains recognition in the diagnostic algorithm of salivary gland tumors, providing data from different diffusion-weighted imaging (DWI) models and dynamic contrast enhanced sequences (DCE-MRI). The aim of this prospective study is to identify quantitative intravoxel incoherent motion and DCE-MRI parameters of the most frequent benign parotid tumors, pleomorphic adenomas and Warthin tumors, to compare their utility and diagnostic accuracy. With a precise pre-treatment diagnostic tool, patients can potentially avoid unnecessary diagnostic procedures and be offered optimal treatment. Aim: The aim of this prospective study is to identify quantitative intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging parameters of the most frequent benign parotid tumors, compare their utility and diagnostic accuracy. Methods: The study group consisted of 52 patients with 64 histopathologically confirmed parotid focal lesions. Parametric maps representing apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (FP) and transfer constant (Ktrans), reflux constant (Kep), extra-vascular extra-cellular volume fraction (Ve), and initial area under curve in 60 s (iAUC) have been obtained from multiparametric MRI. Results: Statistically significant (p < 0.001) inter-group differences were found between pleomorphic adenomas (PA) and Warthin tumors (WT) in all tested parameters but iAUC. Receiver operating characteristic curves were constructed to determine the optimal cut-off levels of the most significant parameters allowing differentiation between WT and PA. The Area Under the Curve (AUC) values and thresholds were for ADC: 0.931 and 1.05, D: 0.896 and 0.9, Kep: 0.964 and 1.1 and Ve: 0.939 and 0.299, respectively. Lesions presenting with a combination of ADC, D, and Ve values superior to the cut-off and Kep values inferior to the cut-off are classified as pleomorphic adenomas. Lesions presenting with combination of ADC, D, and Ve values inferior to the cut-off and Kep values superior to the cut-off are classified as Warthin tumors. Conclusions: DWI, IVIM and quantitative analysis of DCE-MRI derived parameters demonstrated distinctive features of PAs and WT and as such they seem feasible in differentiation of benign parotid gland tumors.

Abstract P3-03-03: Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting

Abstract Background: Early and accurate prediction of response to neoadjuvant therapy (NAT) would empower personalization of breast cancer treatment regimens based on expected response. Noninvasive, quantitative dynamic contrast-enhanced (DCE-MRI) and diffusion-weighted magnetic resonance imaging (DW-MRI), when performed during the course of NAT, can accurately predict the ultimate pathological response. While these techniques have been incorporated into clinical trials in the academic setting, they have not yet been translated to the community setting, where most cancer patients receive their care. Implementation of quantitative MRI in the community setting widely expands the potential impact it can provide by 1) allowing community settings to participate in clinical trials that require quantitative MRI, and 2) advancing quantitative MRI towards standard-of-care for prediction of response in breast cancer. Methods: Women with locally advanced breast cancer (N = 28) were imaged four times during the course of NAT: 1) prior to the start of NAT, 2) after 1 cycle of NAT, 3) after 2-4 cycles of NAT, and 4) 1 cycle after MRI #3. Imaging data was acquired on 3T Siemens Skyra scanners equipped with breast coils and sited in a community hospital and radiology clinic, respectively. DW-MRI and DCE-MRI were acquired over 10 slices of 5 mm thickness. DW-MRI was acquired with diagonal monopolar diffusion-encoding gradients with b-values of 0, 200, and 800 s/mm2 in a total scan time of 1 minute 39 seconds. Voxel wise tumor cellularity was quantified using the apparent diffusion coefficient (ADC). For DCE-MRI, a gadolinium-based contrast agent was administered intravenously at 2 mL/sec after the acquisition of baseline scans. DCE-MRI data was acquired dynamically with a temporal resolution of 7.27 seconds for a total acquisition time of 8 minutes. The volume transfer constant Ktrans was calculated using Patlak analysis of DCE-MRI data to characterize the tumor vasculature. The tumor was semi-automatically segmented using a manually drawn region of interest followed by fuzzy c-means clustering of DCE-MRI data to identify a functional tumor volume. Measurements of tumor volume were combined with both ADC and Ktrans to yield metrics of tumor cellularity and bulk tumor flow, respectively. Results: Women who achieved pathological complete response at the time of surgery (pCR; n=8) displayed significantly different treatment-induced changes in MRI-derived tumor parameters versus women who did not achieve pCR (non-pCR, n=20). After 1 cycle of NAT, women who achieved pCR had smaller functional tumor volume and lower cellularity (p &amp;lt; 0.05) than non-pCR study participants. At the third and fourth MRI, tumor volume, ADC, Ktrans, cellularity, and bulk tumor flow were all significantly different between the pCR and non-pCR cohorts (p &amp;lt; 0.05). Of note, longest tumor diameter was not predictive of pCR at any time point in this study. Conclusions: This study demonstrates that quantitative DCE- and DW-MRI can be implemented successfully in community care facilities within standard-of-care settings for imaging locally advanced breast cancer. Metrics extracted from the change in DW-MRI (ADC) and DCE-MRI (Ktrans) can accurately predict pathological complete response to neoadjuvant therapy and may be more sensitive to tumor response than the RECIST criteria. Furthermore, incorporating quantitative metrics with tumor volume further increases the ability to predict pathological response to NAT in locally advanced breast cancer. While there are still challenges to address to effectively implement these quantitative metrics into the clinical workflow, this study is first in its kind to transition a decade’s worth of quantitative MRI advancements from academic settings into standard-of-care. Citation Format: John Virostko, Anna G Sorace, Kalina P Slavkova, Anum S Kazerouni, Angela M Jarrett, Julie C DiCarlo, Stefanie Woodard, Sarah Avery, Boone W Goodgame, Debra Patt, Thomas E Yankeelov. Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-03-03.

Disposable point-of-care portable perfusion phantom for quantitative DCE-MRI.

To develop a disposable point-of-care portable perfusion phantom (DP4) and validate its clinical utility in a multi-institutional setting for quantitative dynamic contrast-enhanced magnetic resonance imaging (qDCE-MRI). The DP4 phantom was designed for single-use and imaged concurrently with a human subject so that the phantom data can be utilized as the reference to detect errors in qDCE-MRI measurement of human tissues. The change of contrast-agent concentration in the phantom was measured using liquid chromatography-mass spectrometry. The repeatability of the contrast enhancement curve (CEC) was assessed with five phantoms in a single MRI scanner. Five healthy human subjects were recruited to evaluate the reproducibility of qDCE-MRI measurements. Each subject was imaged concurrently with the DP4 phantom at two institutes using three 3T MRI scanners from three different vendors. Pharmacokinetic (PK) parameters in the regions of liver, spleen, pancreas, and paravertebral muscle were calculated based on the Tofts model (TM), extended Tofts model (ETM), and shutter speed model (SSM). The reproducibility of each PK parameter over three measurements was evaluated with the intraclass correlation coefficient (ICC) and compared before and after DP4-based error correction. The contrast-agent concentration in the DP4 phantom was linearly increased over 10 min (0.17mM/min, measurement accuracy: 96%) after injecting gadoteridol (100mM) at a constant rate (0.24ml/s, 4ml). The repeatability of the CEC within the phantom was 0.997 when assessed by the ICC. The reproducibility of the volume transfer constant, Ktrans , was the highest of the PK parameters regardless of the PK models. The ICCs of Ktrans in the TM, ETM, and SSM before DP4-based error correction were 0.34, 0.39, and 0.72, respectively, while those increased to 0.93, 0.98, and 0.86, respectively, after correction. The DP4 phantom is reliable, portable, and capable of significantly improving the reproducibility of qDCE-MRI measurements.

Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging for the Analysis of Microvascular Permeability in Peritumor Brain Edema of Fibrous Meningiomas

Introduction: This study aims to analyze the permeability of intra- and peri-meningiomas regions and compare the microvascular permeability between peritumoral brain edema (PTBE) and non-PTBE using DCE-MRI. Methods: This was a retrospective of patients with meningioma who underwent surgery. The patients were grouped as PTBE and non-PTBE. The DCE-MRI quantitative parameters, including volume transfer constant (K^trans), rate constant (K_ep), extracellular volume (V_e), and mean plasma volume (V_p), obtained using the extended Tofts-Kety 2-compartment model. Logistic regression analysis was conducted to explore the risk factor of PTBE. Results: Sixty-three patients, diagnosed as fibrous meningioma, were included in this study. They were 17 males and 46 females, aged from 32 to 88 years old. K_ep and V_p were significantly lower in patients with PTBE compared with those without (K_ep: 0.1852 ± 0.0369 vs. 0.5087 ± 0.1590, p = 0.010; V_p: 0.0090 ± 0.0020 vs. 0.0521 ± 0.0262, p = 0.007), while there were no differences regarding K^trans and V_e (both p > 0.05). The multivariable analysis showed that tumor size ≥10 cm³ (OR = 4.457, 95% CI: 1.322–15.031, p = 0.016) and V_p (OR = 0.572, 95%CI: 0.333–0.981, p = 0.044) were independently associated with PTBE in patients with meningiomas. Conclusion: DCE-magnetic resonance imaging·Meningioma·Blood vessel MRI can be used to quantify the microvascular permeability of PTBE in patients with meningioma.

The Assessment of Prostate Cancer Aggressiveness Using a Combination of Quantitative Diffusion-Weighted Imaging and Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

ObjectiveTo explore the value of combining dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters with apparent diffusion coefficient (ADC) values in the diagnosis of prostate cancer.MethodsThe clinical data of 146 patients with prostate lesions, including 87 patients with prostate cancer (PCa) and 59 with benign prostatic hyperplasia (BPH), were collected. After DCE-MRI and diffusion-weighted imaging (DWI) prostate scans, the magnitude of the DCE-MRI transfer constant (Ktrans), rate constant (kep), the volume of the extravascular extracellular space (ve), and the ADC between the groups were compared, and the correlations between the DCE-MRI parameters and Gleason scores were analyzed. The diagnostic efficacy of these quantitative parameters was assessed by the area under the receiver operating characteristic (ROC) curve.ResultsThe DCE-MRI parameters Ktrans and kep were significantly greater in the PCa group than in the BPH group (p < 0.05). The ROC curve showed the area under the Ktrans, kep, and ADC curves to be 0.665, 0.658, and 0.782, respectively. When all three quantitative indicators were combined, the area under the ROC curve was 0.904, with sensitivity and specificity rates of 83.6% and 93.7%, respectively. The Gleason scores were positively correlated with the Ktrans, kep, and ve (r = 0.39, 0.572, 0.30, respectively; p < 0.05) and negatively correlated with the ADC (r = –0.525; p < 0.05).ConclusionThe DCE-MRI quantitative parameters Ktrans and kep, as well as the ADC value, provided effective references for the differential diagnosis of PCa and BPH, as well as more precise and reliable quantitative parameters for grading the aggressiveness of PCa.

Evaluation of microvascular permeability of skeletal muscle and texture analysis based on DCE-MRI in alloxan-induced diabetic rabbits.

To estimate the microvascular permeability and perfusion of skeletal muscle by using quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and explore the feasibility of using texture analysis (TA) to evaluate subtle structural changes of diabetic muscles. Twenty-four rabbits were randomly divided into diabetic (n = 14) and control (n = 10) groups, and underwent axial DCE-MRI of the multifidus muscle (0, 4, 8, 12, and 16 weeks after alloxan injection). The pharmacokinetic model was used to calculate the permeability parameters; texture parameters were extracted from volume transfer constant (Ktrans) map. The two-sample t test/Mann-Whitney U test, repeated measures analysis of variance/Friedman test, and Pearson correlations were used for data analysis. In the diabetic group, Ktrans and rate constant (Kep) increased significantly at week 8 and then showed a decreasing trend. Extravascular extracellular space volume fraction (Ve) increased and plasma volume fraction (Vp) decreased significantly from the 8th week. Skewness began to decrease at the 4th week. Median Ktrans and entropy increased significantly, while inverse difference moment decreased from the 8th week. Energy decreased while contrast increased only at week 8. Muscle fibre cross-sectional area was negatively correlated with Ve. The capillary-to-fibre ratio was positively correlated with Vp (p < 0.05, all). Quantitative DCE-MRI can be used to evaluate microvascular permeability and perfusion in diabetic skeletal muscle at an early stage; TA based on Ktrans map can identify microarchitectural modifications in diabetic muscles. • Four quantitative parameters of DCE-MRI can be used to evaluate microvascular permeability and perfusion of skeletal muscle in diabetic models at early stages. • Texture analysis based on Ktrans map can identify subtle structural changes in diabetic muscles.

Dynamic contrast-enhanced MRI of nasopharyngeal carcinoma: correlation of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters with hypoxia-inducible factor 1α expression and tumor grade/stage

Abnormal microangiogenesis and microenvironmental disturbances within the Nasopharyngeal carcinoma (NPC) can exacerbate tumor hypoxia, which may increase radiotherapy resistance and thus lead to poor prognosis in NPC patients. A non-invasive imaging technique, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which can reflect the tumor blood perfusion and angiogenesis status, was used to investigate the relationships of DCE-MRI parameters with hypoxia-inducible factor 1 alpha (HIF-1α) expression and tumor grades in NPC patients. 42 treatment-naive patients with pathologically confirmed NPC were enrolled in this analysis. Plain magnetic resonance scans and DCE-MRI scans were performed before treatment, and post-processing was performed to calculate the relative enhancement (RE), maximum relative enhancement (MRE), maximum enhancement (ME), wash-in rate (WIR), wash-out rate (WOR), time to peak (TTP), and area under the curve (AUC). Immunohistochemistry was used to detect HIF-1α expression in electronasopharyngeal fiberoscopic specimens. The clinical grade/stage of NPC was jointly assessed by an experienced radiologist and a radiotherapist. The potential correlations of the DCE-MRI parameters with HIF-1α expression and clinical grades were analyzed. The statistical analysis was performed using SPSS 17.0 software package. Among DCE-MRI parameters, RE, ME, and MRE were associated with the positive expression of HIF-lα in NPC and could reflect the hypoxic status in the local microenvironment of the cancer foci in vivo. RE, ME, and MRE were significantly higher in the positive HIF-1α expression group than in the negative HIF-1α expression group (F=5.281, P=0.027; F=11.923, P=0.001; F=6.228, P=0.017). RE, ME, and MRE were significantly correlated with clinical grade (F=3.646, P=0.021; F=3.204, P=0.034, F=3.050, P=0.040) and T stage (F=6.578, P=0.001; F=3.540, P=0.023; F=4.384, P=0.010). The values of RE, MRE, and ME gradually increased as the clinical grade and T stage increased. DCE-MRI is a valuable imaging technique for the noninvasive evaluation of hypoxia in NPC, the development of individualized treatment protocols, and the prediction of efficacy.

Value of quantitative dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging in predicting extramural venous invasion in locally advanced gastric cancer and prognostic significance.

Extramural venous invasion (EMVI) has been found to be related to poor prognosis in gastric cancer. Preoperative diagnosis of EMVI is challenging, as it can only be detected by surgical pathology. The present study aimed to investigate the value of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) in predicting EMVI preoperatively, and to determine the relationship between prediction results and prognosis in patients with locally advanced gastric cancer (LAGC). Between January, 2015, and June, 2017, 79 LAGC patients underwent MRI preoperatively were enrolled in this study. Pathological EMVI (pEMVI) was used as the gold standard for diagnosis. The differences in quantitative DCE-MRI and DWI parameters between groups with different pEMVI status were analyzed. Multivariate logistic regression was used to build the combined prediction model for pEMVI with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) analysis. Patients were grouped based on MRI-predicted EMVI (mrEMVI). Kaplan-Meier analysis was used to investigate the relationship between mrEMVI and 2-year recurrence-free survival (RFS). Of the 79 LAGC patients who underwent MRI, 29 were pEMVI positive and 50 were pEMVI negative. Among the patients' clinical and pathological characteristics, only postoperative staging showed a significant difference between the 2 groups (P=0.015). The pEMVI-positive group had higher volume transfer constant (Ktrans) and rate constant (kep), and lower apparent diffusion coefficient (ADC) values than the negative group (0.189 vs. 0.082 min-1, 0.687 vs. 0.475 min-1, and 1.230×10-3 vs. 1.463×10-3 mm2/s, respectively; P<0.05). Quantitative parameters, Ktrans and kep, and ADC values, were independently associated with pEMVI which odds ratio values were 3.66, 2.65, and 0.30 (P<0.05), respectively, using multivariate logistic regression. ROC analysis showed that the area under the curve, sensitivity, specificity, positive predictive value, and negative predictive value in predicting pEMVI using combined Ktrans, kep, and ADC values were 0.879, 72.4%, 96%, 91.3%, and 85.7%, respectively. A total of 23 cases were considered to be mrEMVI positive, and 56 cases were considered to be mrEMVI negative, according to the predictive results. The median RFS of the mrEMVI-positive group was significant lower than the negative group (21.7 vs. 31.2 months), and the 2-year RFS rate in the mrEMVI-positive group was significantly lower than that of the negative group (43.6% vs. 72.5%, P=0.010). The quantitative DCE-MRI parameters, Ktrans and kep, and DWI parameter, ADC, are independent predictors of pEMVI in LAGC; mrEMVI was confirmed to be a poor prognostic predictor for RFS.

Quantitative volume and dynamic contrast-enhanced MRI derived perfusion of the infrapatellar fat pad in patellofemoral pain.

Patellofemoral pain (PFP) is a common knee condition and possible precursor of knee osteoarthritis (OA). Inflammation, leading to an increased perfusion, or increased volume of the infrapatellar fat pad (IPFP) may induce knee pain. The aim of the study was to compare quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters, as imaging biomarkers of inflammation, and volume of the IPFP between patients with PFP and controls and between patients with and without IPFP edema or joint effusion. Patients with PFP and healthy controls were included and underwent non-fat suppressed 3D fast-spoiled gradient-echo (FSPGR) and DCE-MRI. Image registration was applied to correct for motion. The IPFP was delineated on FSPGR using Horos software. Volume was calculated and quantitative perfusion parameters were extracted by fitting extended Tofts' pharmacokinetic model. Differences in volume and DCE-MRI parameters between patients and controls were tested by linear regression analyses. IPFP edema and effusion were analyzed identically. Forty-three controls and 35 PFP patients were included. Mean IPFP volume was 26.04 (4.18) mL in control subjects and 27.52 (5.37) mL in patients. Median Ktrans was 0.017 (0.016) min-1 in control subjects and 0.016 (0.020) min-1 in patients. None of the differences in volume and perfusion parameters were statistically significant. Knees with effusion showed a higher perfusion of the IPFP compared to knees without effusion in patients only. The IPFP has been implicated as source of knee pain, but higher DCE-MR blood perfusion, an imaging biomarker of inflammation, and larger volume are not associated with PFP. Patient's knees with effusion showed a higher perfusion, pointing towards inflammation.