Dynamic Contrast-enhanced Research Articles

The utility of ultrafast MRI and conventional DCE-MRI for predicting histologic aggressiveness in patients with breast cancer.

Prediction of histologic prognostic markers is important for determining management strategy and predicting prognosis. To identify important features of ultrafast and conventional dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) that can predict histopathologic prognostic markers in patients with breast cancer. Preoperative MRI scans of 158 consecutive women (mean age = 54.0 years; age range = 29-86 years) with 163 breast cancers between February 2021 and August 2022 were retrospectively reviewed. Inter-observer agreements for ultrafast MRI parameters were analyzed by two radiologists. The qualitative and quantitative MRI parameters were correlated with histopathologic prognostic markers including molecular subtypes and histologic invasiveness. Inter-observer agreements for ultrafast MRI parameters were excellent (intraclass correlation coefficients of area under the kinetic curve [AUC], maximum slope [MS], maximum enhancement [ME], and slope = 0.987, 0.844, 0.822, and 0.760, respectively). Triple-negative breast cancers (TNBC) were significantly associated with rim enhancement (odds ratio [OR] = 9.4, P = 0.003) and peritumoral edema (OR = 17.9, P = 0.002), compared to luminal cancers. Invasive cancers were associated with lesion type-mass, increased delayed washout, angiovolume, ME, slope, MS, and AUC, compared to in situ cancers. In regression analysis, the combination of MS (>46.2%/s) (OR = 5.7, P = 0.046) and delayed washout (>17.5%) (OR = 17.6, P = 0.01), and that of AUC (>27,410.3) (OR = 9.6, P = 0.04), delayed washout (>17.5%) (OR = 8.9, P = 0.009), and lesion-type mass (OR = 4.6, P = 0.04) were predictive of histologic invasiveness. Conventional DCE-MRI with ultrafast imaging can provide useful information for predicting histologic underestimation and aggressive molecular subtype. MS and AUC on ultrafast MRI can be potential imaging markers for predicting histologic upgrade from DCIS to invasive cancer with high reliability.

Discrimination Between Benign and Malignant Lesions With Restriction Spectrum Imaging MRI in an Enriched Breast Cancer Screening Cohort.

Breast cancer screening with dynamic contrast-enhanced MRI (DCE-MRI) is recommended for high-risk women but has limitations, including variable specificity and difficulty in distinguishing cancerous (CL) and high-risk benign lesions (HRBL) from average-risk benign lesions (ARBL). Complementary non-invasive imaging techniques would be useful to improve specificity. To evaluate the performance of a previously-developed breast-specific diffusion-weighted MRI (DW-MRI) model (BS-RSI3C) to improve discrimination between CL, HRBL, and ARBL in an enriched screening population. Prospective. Exactly 187 women, either with mammography screening recommending additional imaging (N = 49) or high-risk individuals undergoing routine breast MRI (N = 138), before the biopsy. Multishell DW-MRI echo planar imaging sequence with a reduced field of view at 3.0 T. A total of 72 women had at least one biopsied lesion, with 89 lesions categorized into ARBL, HRBL, CL, and combined CLs and HRBLs (CHRLs). DW-MRI data were processed to produce apparent diffusion coefficient (ADC) maps, and estimate signal contributions (C1, C2, and C3-restricted, hindered, and free diffusion, respectively) from the BS-RSI3C model. Lesion regions of interest (ROIs) were delineated on DW images based on suspicious DCE-MRI findings by two radiologists; control ROIs were drawn in the contralateral breast. One-way ANOVA and two-sided t-tests were used to assess differences in signal contributions and ADC values among groups. P-values were adjusted using the Bonferroni method for multiple testing, P = 0.05 was used for the significance level. Receiver operating characteristics (ROC) curves and intra-class correlations (ICC) were also evaluated. C1, √C1C2, and were significantly different in HRBLs compared with ARBLs (P-values < 0.05). The had the highest AUC (0.821) in differentiating CHRLs from ARBLs, performing better than ADC (0.696), especially in non-mass enhancement (0.776 vs. 0.517). This study demonstrated the BS-RSI3C could differentiate HRBLs from ARBLs in a screening population, and separate CHRLs from ARBLs better than ADC. 2.

Blood–brain barrier breakdown in dementia with Lewy bodies

BackgroundBlood–brain barrier (BBB) dysfunction has been viewed as a potential underlying mechanism of neurodegenerative disorders, possibly involved in the pathogenesis and progression of Alzheimer’s disease (AD). However, a relation between BBB dysfunction and dementia with Lewy bodies (DLB) has yet to be systematically investigated. Given the overlapping clinical features and neuropathology of AD and DLB, we sought to evaluate BBB permeability in the context of DLB and determine its association with plasma amyloid-β (Aβ) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).MethodsFor this prospective study, we examined healthy controls (n = 24, HC group) and patients diagnosed with AD (n = 29) or DLB (n = 20) between December 2020 and April 2022. Based on DCE-MRI studies, mean rates of contrast agent transfer from intra- to extravascular spaces (Ktrans) were calculated within regions of interest. Spearman’s correlation and multivariate linear regression were applied to analyze associations between Ktrans and specific clinical characteristics.ResultsIn members of the DLB (vs HC) group, Ktrans values of cerebral cortex (p = 0.024), parietal lobe (p = 0.007), and occipital lobe (p = 0.014) were significantly higher; and Ktrans values of cerebral cortex (p = 0.041) and occipital lobe (p = 0.018) in the DLB group were significantly increased, relative to those of the AD group. All participants also showed increased Ktrans values of parietal (β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upbeta$$\\end{document} = 0.391; p = 0.001) and occipital (β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upbeta$$\\end{document} = 0.357; p = 0.002) lobes that were significantly associated with higher scores of the Clinical Dementia Rating, once adjusted for age and sex. Similarly, increased Ktrans values of cerebral cortex (β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upbeta$$\\end{document} = 0.285; p = 0.015), frontal lobe (β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upbeta$$\\end{document} = 0.237; p = 0.043), and parietal lobe (β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upbeta$$\\end{document} = 0.265; p = 0.024) were significantly linked to higher plasma Aβ1-42/Aβ1-40 ratios, after above adjustments.ConclusionBBB leakage is a common feature of DLB and possibly is even more severe than in the setting of AD for certain regions of the brain. BBB leakage appears to correlate with plasma Aβ1-42/Aβ1-40 ratio and dementia severity.

Perfusion-weighted imaging with dynamic contrast enhancement (PWI/DCE) morphologic, qualitative, semiquantitative, and radiomics features predicting undifferentiated pleomorphic sarcoma (UPS) treatment response

Undifferentiated pleomorphic sarcoma (UPS) is the largest subgroup of soft tissue sarcomas. This study determined the value of perfusion-weighted imaging with dynamic-contrast-enhancement (PWI/DCE) morphologic, qualitative, and semiquantitative features for predicting UPS pathology-assessed treatment effect (PATE). This retrospective study included 33 surgically excised extremity UPS patients with pre-surgical MRI. Volumetric tumor segmentation from PWI/DCE was obtained at Baseline (BL), Post-Chemotherapy (PC), and Post-Radiation Therapy (PRT). The surgical specimens’ PATE separated cases into Responders (R) (≥ 90%, 16 patients), Partial-Responders (PR) (89 − 31%, 10 patients), and Non-Responders (NR) (≤ 30%, seven patients). Seven semiquantitative kinetic parameters and maps were extracted from time-intensity curves (TICs), and 107 radiomic features were derived. Statistical analyses compared R vs. PR/NR. At PRT, 79% of R displayed a “Capsular” morphology (P = 1.49 × 10-7), and 100% demonstrated a TIC-type II (P = 8.32 × 10-7). 80% of PR showed “Unipolar” morphology (P = 1.03 × 10-5), and 60% expressed a TIC-type V (P = 0.06). Semiquantitative wash-in rate (WiR) was able to separate R vs. PR/NR (P = 0.0078). The WiR radiomics displayed significant differences in the first_order_10 percentile (P = 0.0178) comparing R vs. PR/NR at PRT. The PWI/DCE TIC-type II curve, low WiR, and “Capsular” enhancement represent PRT patterns typically observed in successfully treated UPS and demonstrate potential for UPS treatment response assessment.

Elevated cerebral perfusion in neonatal encephalopathy is associated with neurodevelopmental impairments.

Neonatal encephalopathy (NE) represents a primary cause of neonatal death and neurodevelopmental impairments. In newborns with NE, cerebral hyperperfusion is related to an increased risk of severe adverse outcomes, but less is known about the link between perfusion and mild to moderate developmental impairments or developmental delay. Using arterial spin labelling perfusion MRI, we investigated the link between perfusion in 36 newborns with NE and developmental outcome at 2 years. 53% of the infants demonstrated a normal outcome at 24 months, while two had cerebral palsy with impairments in cognitive, motor, and language domains, and three infants died. The remaining infants showed mild or moderate delays in development in one or two domains. Hyperperfusion across the whole brain was associated with more adverse outcome, including an increased risk of death or severe disability such as cerebral palsy. Among the surviving infants, higher perfusion in the bilateral basal ganglia, thalamus, hippocampus and cerebellum during the neonatal period was related to a poorer cognitive outcome at 2 years. Hyperperfusion in infants with NE was associated with a more adverse outcome and lower cognitive outcome scores. In addition to severe adverse outcomes, altered perfusion is also related to mild to moderate impairment following HIE. Neonates with neonatal encephalopathy (NE) show increased cerebral perfusion globally, which is linked to a more adverse outcome. Higher perfusion in the bilateral basal ganglia, thalamus, hippocampus and cerebellum during the neonatal period was related to a poorer cognitive outcome at 2 years. In addition to severe adverse outcomes altered perfusion is related to mild to moderate impairment following NE. To improve neurodevelopmental outcomes, it is important to improve our understanding of the factors influencing cerebral perfusion in infants with NE.

The application value of support vector machine model based on multimodal MRI in predicting IDH-1mutation and Ki-67 expression in glioma

PurposeTo investigate the application value of support vector machine (SVM) model based on diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) and amide proton transfer- weighted (APTW) imaging in predicting isocitrate dehydrogenase 1(IDH-1) mutation and Ki-67 expression in glioma.MethodsThe DWI, DCE and APTW images of 309 patients with glioma confirmed by pathology were retrospectively analyzed and divided into the IDH-1 group (IDH-1(+) group and IDH-1(-) group) and Ki-67 group (low expression group (Ki-67 ≤ 10%) and high expression group (Ki-67 > 10%)). All cases were divided into the training set, and validation set according to the ratio of 7:3. The training set was used to select features and establish machine learning models. The SVM model was established with the data after feature selection. Four single sequence models and one combined model were established in IDH-1 group and Ki-67 group. The receiver operator characteristic (ROC) curve was used to evaluate the diagnostic performance of the model. Validation set data was used for further validation.ResultsBoth in the IDH-1 group and Ki-67 group, the combined model had better predictive efficiency than single sequence model, although the single sequence model had a better predictive efficiency. In the Ki-67 group, the combined model was built from six selected radiomics features, and the AUC were 0.965 and 0.931 in the training and validation sets, respectively. In the IDH-1 group, the combined model was built from four selected radiomics features, and the AUC were 0.997 and 0.967 in the training and validation sets, respectively.ConclusionThe radiomics model established by DWI, DCE and APTW images could be used to detect IDH-1 mutation and Ki-67 expression in glioma patients before surgery. The prediction performance of the radiomics model based on the combination sequence was better than that of the single sequence model.

Tumor infiltrating lymphocytes and change in tumor load on MRI to assess response and prognosis after neoadjuvant chemotherapy in breast cancer.

In this study, we aimed to explore if the combination of tumor infiltrating lymphocytes (TILs) and change in tumor load on dynamic contrast-enhanced magnetic resonance imaging leads to better assessment of response to neoadjuvant chemotherapy (NAC) in patients with breast cancer, compared to either alone. In 190 NAC treated patients, MRI scans were performed before and at the end of treatment. The percentage of stromal TILs (%TILs) was assessed in pre-NAC biopsies according to established criteria. Prediction models were developed with linear regression by least absolute shrinkage and selection operator and cross validation (CV), with residual cancer burden as the dependent variable. Discrimination for pathological complete response (pCR) was evaluated using area under the receiver operating characteristic curves (AUC). We used Cox regression analysis for exploring the association between %TILs and recurrence-free survival (RFS). Fifty-one patients reached pCR. In all patients, the %TILs model and change in MRI tumor load model had an estimated CV AUC of 0.69 (95% confidence interval (CI) 0.53-0.78) and 0.69 (95% CI 0.61-0.79), respectively, whereas a model combining the variables resulted in an estimated CV AUC of 0.75 (95% CI 0.66-0.83). In the group with tumors that were ER positive and HER2 negative (ER+/HER2-) and in the group with tumors that were either triple negative or HER2 positive (TN&HER2+) separately, the combined model reached an estimated CV AUC of 0.72 (95% CI 0.60-0.88) and 0.70(95% CI 0.59-0.82), respectively. A significant association was observed between pre-treatment %TILS and RFS (hazard ratio (HR) 0.72 (95% CI 0.53-0.98), for every standard deviation increase in %TILS, p = 0.038). The combination of TILs and MRI is informative of response to NAC in patients with both ER+/HER2- and TN&HER2+ tumors.

A novel methodology for mapping interstitial fluid dynamics in murine brain tumors using DCE-MRI

We present a comprehensive methodology for measuring heterogeneous interstitial fluid flow in murine brain tumors using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) coupled with the computational tool, Lymph4D. This four-part protocol encompasses glioma cell preparation, tumor inoculation, MRI imaging protocol, and histological verification using Evans Blue. While conventional DCE-MRI analysis primarily focuses on vascular perfusion, our methods reveal untapped potential to extract crucial information about interstitial fluid dynamics, including directions, velocities, and diffusion coefficients. This methodology extends beyond glioma research, with applicability to conditions routinely imaged with DCE-MRI, thereby offering a versatile tool for investigating interstitial fluid dynamics across a wide range of diseases and conditions. Our methodology holds promise for accelerating discoveries and advancements in biomedical research, ultimately enhancing diagnostic and therapeutic strategies for a wide range of diseases and conditions.

The role of multiparametric MRI in predicting lymphovascular invasion in breast cancer patients.

Background: This study aims to investigate the efficacy of multifactorial MRI in diagnosing breast cancer, specifically in the context of predicting lymphovascular invasion (LVI).Materials & methods: The patients were stratified into two groups: the primary group (100 patients) and the validation group (100 patients), based on essential characteristics. Multifactorial MRI, encompassing tumor size evaluation, diffusion coefficient assessment and dynamic contrast enhancement, was employed for patient examination.Results: Statistically significant differences were observed in tumor size, diffusion coefficient and dynamic contrast enhancement between groups with LVI (LVI+) and those without (LVI-). Key parameters were identified for predicting the degree of invasion.Conclusion: The results affirm the effectiveness of multifactorial MRI in forecasting LVI.

Prediction of axillary lymph node metastasis using a magnetic resonance imaging radiomics model of invasive breast cancer primary tumor

BackgroundThis study investigated the clinical value of breast magnetic resonance imaging (MRI) radiomics for predicting axillary lymph node metastasis (ALNM) and to compare the discriminative abilities of different combinations of MRI sequences.MethodsThis study included 141 patients diagnosed with invasive breast cancer from two centers (center 1: n = 101, center 2: n = 40). Patients from center 1 were randomly divided into training set and test set 1. Patients from center 2 were assigned to the test set 2. All participants underwent preoperative MRI, and four distinct MRI sequences were obtained. The volume of interest (VOI) of the breast tumor was delineated on the dynamic contrast-enhanced (DCE) postcontrast phase 2 sequence, and the VOIs of other sequences were adjusted when required. Subsequently, radiomics features were extracted from the VOIs using an open-source package. Both single- and multisequence radiomics models were constructed using the logistic regression method in the training set. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and precision of the radiomics model for the test set 1 and test set 2 were calculated. Finally, the diagnostic performance of each model was compared with the diagnostic level of junior and senior radiologists.ResultsThe single-sequence ALNM classifier derived from DCE postcontrast phase 1 had the best performance for both test set 1 (AUC = 0.891) and test set 2 (AUC = 0.619). The best-performing multisequence ALNM classifiers for both test set 1 (AUC = 0.910) and test set 2 (AUC = 0.717) were generated from DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging single-sequence ALNM classifiers. Both had a higher diagnostic level than the junior and senior radiologists.ConclusionsThe combination of DCE postcontrast phase 1, T2-weighted imaging, and diffusion-weighted imaging radiomics features had the best performance in predicting ALNM from breast cancer. Our study presents a well-performing and noninvasive tool for ALNM prediction in patients with breast cancer.

Understanding the Importance of Blood-Brain Barrier Alterations in Brain Arteriovenous Malformations and Implications for Treatment: A Dynamic Contrast-Enhanced-MRI-Based Prospective Study.

The major clinical implication of brain arteriovenous malformations (bAVMs) is spontaneous intracranial hemorrhage. There is a growing body of experimental evidence proving that inflammation and blood-brain barrier (BBB) dysfunction are involved in both the clinical course of the disease and the risk of bleeding. However, how bAVM treatment affects perilesional BBB disturbances is yet unclear. We assessed the permeability changes of the BBB using dynamic contrast-enhanced MRI (DCE-MRI) in a series of bAVMs (n = 35), before and at a mean of 5 (±2) days after treatment. A set of cerebral cavernous malformations (CCMs) (n = 16) was used as a control group for the assessment of the surgical-related collateral changes. The extended Tofts pharmacokinetic model was used to extract permeability (Ktrans) values in the lesional, perilesional, and normal brain tissues. In patients with bAVM, the permeability of BBB was higher in the perilesional of bAVM tissue compared with the rest of the brain parenchyma (mean Ktrans 0.145 ± 0.104 vs 0.084 ± 0.035, P = .004). Meanwhile, no significant changes were seen in the perilesional brain of CCM cases (mean Ktrans 0.055 ± 0.056 vs 0.061 ± 0.026, P = .96). A significant decrease in BBB permeability was evident in the perilesional area of bAVM after surgical resection (mean Ktrans 0.145 ± 0.104 vs 0.096 ± 0.059, P = .037). This benefit in BBB permeability reduction after surgery seemed to surpass the relative increase in permeability inherent to the surgical manipulation. In contrast to CCMs, BBB permeability in patients with bAVM is increased in the perilesional parenchyma, as assessed using DCE-MRI. However, bAVM surgical resection seems to reduce BBB permeability in the perilesional tissue. No evidence of the so-called breakthrough phenomenon was detected in our series. DCE-MRI could become a valuable tool to follow the longitudinal course of BBB damage throughout the natural history and clinical course of bAVMs.

Evaluation of Middle Cerebral Artery Culprit Plaque Inflammation in Ischemic Stroke Using CAIPIRINHA-Dixon-TWIST Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

Middle cerebral artery (MCA) plaques are a leading cause of ischemic stroke (IS). Plaque inflammation is crucial for plaque stability and urgently needs quantitative detection. To explore the utility of Controlled Aliasing in Parallel Imaging Results in Higher Acceleration (CAIPIRINHA)-Dixon-Time-resolved angiography With Interleaved Stochastic Trajectories (TWIST) (CDT) dynamic contrast-enhanced MRI (DCE-MRI) for evaluating MCA culprit plaque inflammation changes over stroke time and with diabetes mellitus (DM). Prospective. Ninety-four patients (51.6 ± 12.23 years, 32 females, 23 DM) with acute IS (AIS; N = 43) and non-acute IS (non-AIS; 14 days < stroke time ≤ 3 months; N = 51). 3-T, CDT DCE-MRI and three-dimensional (3D) Sampling Perfection with Application optimized Contrast using different flip angle Evolution (3D-SPACE) T1-weighted imaging (T1WI). Stroke time (from initial IS symptoms to MRI) and DM were registered. For 94 MCA culprit plaques, Ktrans from CDT DCE-MRI and enhancement ratio (ER) from 3D-SPACE T1WI were compared between groups with and without AIS and DM. Shapiro-Wilk test, Bland-Altman analysis, Passing and Bablok test, independent t-test, Mann-Whitney U test, Chi-squared test, Fisher's exact test, receiver operating characteristics (ROC) with the area under the curve (AUC), DeLong's test, and Spearman rank correlation test with the P-value significance level of 0.05. Ktrans and ER of MCA culprit plaques were significantly higher in AIS than non-AIS patients (Ktrans = 0.098 s-1 vs. 0.037 s-1; ER = 0.86 vs. 0.55). Ktrans showed better AUC for distinguishing AIS from non-AIS patients (0.87 vs. 0.75) and stronger negative correlation with stroke time than ER (r = -0.60 vs. -0.34). DM patients had significantly higher Ktrans and ER than non-DM patients in IS and AIS groups. Imaging by CDT DCE-MRI may allow to quantitatively evaluate MCA culprit plaques over stroke time and DM. 2 TECHNICAL EFFICACY: Stage 2.

Multi-parametric magnetic resonance imaging of prostate cancer: correlation between Ktrans, Gleason score, and PI-RADS score

PurposeTo measure Ktrans and correlate it with Gleason score (GS) and PI-RADS score in patients with prostate cancer.MethodsThis retrospective study included patients with pathologically proven prostate cancer who had undergone clinically indicated 1.5 Tesla multi-parametric magnetic resonance imaging (MRI) examination between February and December 2020. T2-weighted (T2w) images, diffusion-weighted images (DWI), and dynamic contrast-enhanced (DCE) sequences were obtained. PI-RADS score was calculated for all tumor lesions. From DCE-MRI dataset, Ktrans was computed and compared between patients with clinically insignificant (GS ≤ 6) and clinically significant (GS ≥ 7) prostate cancer. Spearman rank-order correlation coefficient (ρ) was used to assess the correlation strength between Ktrans and GS and between Ktrans and PI-RADS score.ResultsTwenty-one patients (age: 67 ± 12 years; BMI: 26.63 ± 4.04 kg/m2) with a PSA of 7.91 ± 3.01 were included in the study. Seven patients (33.3%) had clinically insignificant prostate cancer, while 14 patients (66.7%) were diagnosed with clinically significant prostate cancer. Mean Ktrans value was 0.42 ± 0.20 min−1 (range: 0.15–0.75). Ktrans was significantly higher (0.50 ± 0.17 min−1) in clinically significant prostate cancer compared to clinical insignificant prostate cancer (0.23 ± 0.15 min−1; P = 0.001). Ktrans showed moderate significant correlation with GS (ρ = 0.575, P = 0.006), but showed no significant correlation with PI-RADS (ρ = 0.386, P = 0.069).ConclusionKtrans may discriminate between clinically insignificant and significant prostate cancer and shows moderate correlation with GS. Thus, MP-MRI may serve as an imaging biomarker in prostate cancer.

CT and MR imaging characteristics of primary hepatic lymphoma

BackgroundPrimary hepatic lymphoma (PHL) is a rare primary liver tumor. The purpose of this study was to investigate the crucial imaging characteristics of PHL.MethodsCT/MR data and clinical features of 16 patients with pathologically proven PHL were retrospectively reviewed. The assessed imaging characteristics included lesion distribution, growth appearance, density or signal characteristics, and typical signs during the dynamic enhancement.ResultsA total of sixteen patients were included in this study, ranging in age from 27 to 86 years (nine men and seven women; mean age, 62 years). Right upper abdominal pain, malaise, or first detection during physical examination were the chief complaint. Dynamic contrast-enhanced CT and MRI demonstrated focal masses in thirteen patients (13/16, 81%), and multiple nodules in three patients (3/16, 19%). The lesions showed vascular floating sign in 10 patients (10/16, 63%) and biliary pass-through sign in 6 patients (6/16, 37%). Necrosis in PHLs were observed in 10 patients (10/16, 63%) and presented target sign on T2WI in 5 out of 11 patients (5/11, 45%) undergoing MRI. After enhancement, PHLs had multinodular sign in the arterial phase in 10 patients (10/16, 63%), and presented washout of contrast medium in the portal-venous or delayed phase in 12 patients (12/16, 75%), pseudocapsule in the delayed phase in 15 patients (15/16, 94%), and double-ring sign in the delayed phase in 8 patients (8/16, 50%).ConclusionPHL is generally seen in elderly patients with elevated beta-2-microglobulin levels. Its distinctive imaging features including obviously low ADC value, biliary/vascular floating sign, multinodular sign and double-ring sign in the delayed phase, may help to diagnose and differentiate PHL.

The impact of benign tissue within cancerous regions in the prostate: Characterizing sparse and dense prostate cancers on whole-mount histopathology and on multiparametric MRI

PurposeTo establish the incidence, size, zonal location and Gleason Score(GS)/Gleason Grade Group(GG) of sparse versus dense prostate cancer (PCa) lesions and to identify the imaging characteristics of sparse versus dense cancers on multiparametric MRI (mpMRI). MethodsSeventy-six men with untreated PCa were scanned prior to prostatectomy with endorectal-coil 3 T MRI including T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced MRI. Cancerous regions were outlined and graded on the whole-mount, processed specimens, with tissue compositions estimated. Regions with cancer comprising <50 % and ≥ 50 % of the tissue were considered sparse and dense respectively. Regions of interest (ROI) were manually drawn on T2-weighted MRI. Within each patient, area-weighted ROI averages were calculated for each imaging measure for each tissue type, GS/GG, and sparse/dense composition. ResultsA large number of cancer regions were identified on histopathology (n = 1193: 939 (peripheral zone (PZ)) and 254 (transition zone (TZ))). Thirty-seven percent of these lesions were sparse. Sparse lesions were primarily low-grade with the majority of PZ and 100 % of TZ sparse lesions ≤GS3 + 3/GG1. Dense lesions were significantly larger than sparse lesions in both PZ and TZ, p < 0.0001. On imaging, 246/45 PZ and 109/8 TZ dense/sparse 2D cancerous ROIs were drawn. Sparse GS3 + 3 and sparse ≥GS3 + 4 cancers did not have significantly different MRI intensities to dense GS3 + 3 cancers, while sparse GS3 + 3/GG1 cancers differed from benign, p < 0.05. ConclusionHistopathologically identified prostate cancer lesions were sparse in 37 % of cases. Sparse cancers were entirely low grade in TZ and predominantly low-grade in PZ and generally small, thus likely posing lower risk for spread and progression than dense lesions. Sparse lesions were not distinguishable from dense lesions on mpMRI, but could be distinguished from benign tissues.

Longitudinal Magnetic Resonance Imaging of Changes in Lung Morphology and Perfusion in Children with Cystic Fibrosis From Infancy through Adolescence.

The progression of lung changes in cystic fibrosis (CF) from infancy through adolescence remains poorly understood due to limited longitudinal imaging data. To assess changes in lung morphology and perfusion in children with CF through the pediatric age range by longitudinal chest magnetic resonance imaging (MRI). 1112 annual chest MRI were performed in 226 patients with CF aged 0-18yr. MRI was assessed using a validated MRI scoring system. The MRI global score continuously increased from 5.5±4.6 at infancy (0yr) to 17.9±8.4 at adolescence (range 12-18yr), and the MRI morphology score from 5.0±3.9 to 12.4±6.0 (P<0.001). Bronchiectasis/wall thickening prevalence increased from 89.1% at infancy to approx. 100% from preschool age (1-5yr), and the subscore increased from 3.1±1.9 at infancy to 6.6±2.1 at adolescence (P<0.001). Mucus plugging prevalence increased from 55.4% at infancy to 83.5% at adolescence, and the subscore increased from 1.2±1.6 to 3.7±2.5 in the same period (P<0.001). Perfusion abnormalities were found in 44.4% at infancy, and increased to approx. 90% from preschool age (P<0.001). The MRI perfusion score increased from 1.1±1.6 at infancy to 5.6±3.0 at adolescence (P<0.001). Chronic Pseudomonas aeruginosa infection was associated with higher MRI scores from school age (6-11yr, P<0.05-0.001). This is the first study assessing longitudinal changes in lung morphology and perfusion in CF throughout the pediatric age range, providing percentiles as age-specific reference for lung disease severity. Our data may facilitate the use of MRI as an endpoint in clinical trials in children with CF.

The Role of Predictive and Prognostic MRI-Based Biomarkers in the Era of Total Neoadjuvant Treatment in Rectal Cancer.

The role of magnetic resonance imaging (MRI) in rectal cancer management has significantly increased over the last decade, in line with more personalized treatment approaches. Total neoadjuvant treatment (TNT) plays a pivotal role in the shift from traditional surgical approach to non-surgical approaches such as 'watch-and-wait'. MRI plays a central role in this evolving landscape, providing essential morphological and functional data that support clinical decision-making. Key MRI-based biomarkers, including circumferential resection margin (CRM), extramural venous invasion (EMVI), tumour deposits, diffusion-weighted imaging (DWI), and MRI tumour regression grade (mrTRG), have proven valuable for staging, response assessment, and patient prognosis. Functional imaging techniques, such as dynamic contrast-enhanced MRI (DCE-MRI), alongside emerging biomarkers derived from radiomics and artificial intelligence (AI) have the potential to transform rectal cancer management offering data that enhance T and N staging, histopathological characterization, prediction of treatment response, recurrence detection, and identification of genomic features. This review outlines validated morphological and functional MRI-derived biomarkers with both prognostic and predictive significance, while also exploring the potential of radiomics and artificial intelligence in rectal cancer management. Furthermore, we discuss the role of rectal MRI in the 'watch-and-wait' approach, highlighting important practical aspects in selecting patients for non-surgical management.

Radiomics analysis of cerebral blood flow suggests a possible link between perfusion homogeneity and poor glioblastoma multiforme prognosis

Objectives. This study investigates the association between cerebral blood flow (CBF) and overall survival (OS) in glioblastoma multiforme (GBM) patients receiving chemoradiation. Identifying CBF biomarkers could help predict patient response to this treatment, facilitating the development of personalized therapeutic strategies. Materials and Methods. This retrospective study analyzed CBF data from dynamic susceptibility contrast (DSC) MRI in 30 newly diagnosed GBM patients (WHO grade IV). Radiomics features were extracted from CBF maps, tested for robustness, and correlated with OS. Kaplan-Meier analysis was used to assess the predictive value of radiomic features significantly associated with OS, aiming to stratify patients into groups with distinct post-treatment survival outcomes. Results. While mean relative CBF and CBV failed to serve as independent prognostic markers for OS, the prognostic potential of radiomic features extracted from CBF maps was explored. Ten out of forty-three radiomic features with highest intraclass correlation coefficients (ICC > 0.9), were selected for characterization. While Correlation and Zone Size Variance (ZSV) features showed significant OS correlations, indicating prognostic potential, Kaplan-Meier analysis did not significantly stratify patients based on these features. Visual analysis of the graphs revealed a predominant association between the identified radiomic features and OS under two years. Focusing on this subgroup, Correlation, ZSV, and Gray-Level Nonuniformity (GLN) emerged as significant, suggesting that a lack of heterogeneity in perfusion patterns may be indicative of a poorer outcome. Kaplan-Meier analysis effectively stratified this cohort based on the features mentioned above. Receiver operating characteristic (ROC) analysis further validated their prognostic value, with ZSV demonstrating the highest sensitivity and specificity (0.75 and 0.85, respectively). Conclusion. Our findings underscored radiomics features sensitive to CBF heterogeneity as pivotal predictors for patient stratification. Our results suggest that these markers may have the potential to identify patients who are unlikely to benefit from standard chemoradiation therapy.

Quantitative Perfusion-Weighted Magnetic Resonance Imaging in Uveal Melanoma.

Perfusion-weighted imaging (PWI; magnetic resonance imaging [MRI]) has been shown to provide valuable biological tumor information in uveal melanoma (UM). Clinically used semiquantitative methods do not account for tumor pigmentation and eye movement. We hypothesize that a quantitative PWI method that incorporates these, provides a more accurate description of tumor perfusion than the current clinical method. The aim of this study was to test this in patients with UM before and after radiotherapy. Perfusion-weighted 3T MRIs were retrospectively analyzed in 47 patients with UM before and after radiotherapy. Tofts pharmacokinetic modeling was performed to determine vascular permeability (Ktrans), extracellular extravascular space (ve), and reflux rate (kep). These were compared with semiquantitative clinical parameters including peak intensity and outflow percentage. The effect of tumor pigmentation on peak intensity and outflow percentage was statistically significant (P < 0.01) and relative peak intensity was significantly different between melanotic and amelanotic tumors (1.5 vs. 1.9, P < 0.01). Before radiotherapy, median tumor Ktrans was 0.63 min-1 (range = 0.06-1.42 min-1), median ve was 0.23 (range = 0.09-0.63), and median kep was 2.3 min-1 (range = 0.6-5.0 min-1). After radiotherapy, 85% showed a decrease in Ktrans and kep (P < 0.01). Changes in tumor pigmentation before and after radiotherapy were small and not significant (median increase in T1 of 33 ms, P = 0.55). Quantitative PWI parameters decreased significantly after radiotherapy and can therefore can serve as an early biomarker for treatment response assessment. However, due to the nonsignificant changes in tumor pigmentation before and after radiotherapy, the current semiquantitative method appears to be sufficiently sensitive for detection of changes in tumor perfusion.

Magnetic resonance imaging patterns and perfusion changes of posterior reversible encephalopathy syndrome in children with clinical outcome correlation.

Posterior reversible encephalopathy syndrome (PRES) in children has a propensity towards atypical features on magnetic resonance (MR) imaging, with limited literature on perfusion changes and clinicoradiological correlation. We aimed to comprehensively study MR imaging patterns of pediatric PRES, including cerebral blood flow variations on arterial spin labeling, and looked for any MR biomarkers of poor clinical outcome. In this retrospective observational study conducted in a tertiary hospital setting, MR records over a 4-year period (May 2019 to May 2023) were systematically searched along with their clinical details. Patients with an age less than 18years and a clinicoradiological constellation consistent with PRES were included. MR scans were analyzed by two neuroradiologists with 8years' and 10years' experience. Association was sought with poor clinical outcome (defined as modified Rankin Scale score at discharge of > 2). A total of 45 patients (29 boys) were included in the study, with a mean age (± standard deviation) of 11.19 (± 4.53) years. On MR imaging, 95.6% of patients (n = 43) showed atypical features and/or atypical areas of involvement. The superior frontal sulcus (n = 18) was the most predominant MR pattern, and cerebellar involvement was not uncommon (n = 15). Unilateral involvement (n = 3), isolated central pattern (n = 1), and spinal cord involvement (PRES-SCI: n = 1) were also encountered. Brainstem involvement (n = 4) showed a characteristic "V-sign" of anterior medullary hyperintensity. Patchy restricted diffusion (46.6%), punctate hemorrhages (37.7%), and leptomeningeal contrast enhancement (36%) were not uncommon. Arterial spin labeling sequence (available in 24 patients) showed increased cerebral blood flow in the involved areas in 79.2% of patients. Univariate analysis showed a significant association of the presence of hemorrhage (P = 0.003), involvement of brainstem (P = 0.007), deep white matter (P = 0.008), and thalamus (P = 0.026) with poor clinical outcome. Multivariate regression analysis found that hemorrhage on MRI (P = 0.011, odds ratio 8) was an independent factor associated with poor clinical outcome. The conventionally described atypical features in PRES are common in children and therefore may no longer be considered exceptions. Raised perfusion on arterial spin labeling sequence was seen in the majority of cases. Hemorrhage on MRI was an independent predictor of poor clinical outcome in pediatric PRES.