Dynamic Contrast-enhanced Research Articles

Diagnostic Efficacy of Multimodal Ultrasound for Mass and Non-Mass Enhancements in Dynamic Contrast-Enhanced MRI of Idiopathic Granulomatous Mastitis and Breast Cancer

PurposeIdiopathic granulomatous mastitis (IGM) poses diagnostic challenges due to its diverse clinical and radiological presentations, often mimicking malignancies. This study aimed to assess the diagnostic efficacy of multimodal ultrasound for mass and non-mass enhancements in Dynamic Contrast-Enhanced MRI (DCE-MRI) of IGM and breast cancer. MethodsA retrospective analysis involved patients confirmed histopathologically with IGM and BC. All patients underwent conventional ultrasound (C-US), ultrasound elastography (UE), contrast-enhanced ultrasound (CEUS), and DCE-MR examinations. Blind experienced radiologists assessed imaging findings. Diagnostic accuracy, sensitivity, and specificity were calculated for mass and non-mass enhancements. ResultsFor mass enhancements (ME), multimodal ultrasound demonstrated strong efficacy (AUC = 0.8651, 95% CI: 0.7431 to 0.9871), exhibiting high sensitivity (83.3%) and specificity (92.4%) in differentiating IGM from breast cancer. However, for non-mass enhancements (NME), multimodal ultrasound showed limited accuracy (AUC = 0.6306) with lower sensitivity (65.6%) and specificity (81.2%) in distinguishing between IGM and breast cancer. ConclusionMultimodal ultrasound displayed good diagnostic efficacy for mass enhancements in DCE-MRI for idiopathic granulomatous mastitis and breast cancer, while for non-mass enhancement patterns, DCE-MRI remains the most valuable radiological modality for comprehensively assessing this condition's complexities.

Advancing Cancer Care: A Critical Review of MRI Imaging in Pretherapeutic Malignancy Assessment

Magnetic Resonance Imaging (MRI) has become an indispensable tool in the pretherapeutic assessment of malignancies, offering unparalleled soft tissue contrast, advanced functional imaging capabilities, and the ability to provide non-invasive, radiation-free evaluations. This critical review explores the role of MRI in accurately diagnosing, staging, and guiding treatment strategies for various cancers, including breast, prostate, liver, and brain malignancies. Advanced techniques such as diffusion-weighted imaging (DWI), dynamic contrast-enhanced MRI (DCE-MRI), and the integration of artificial intelligence are discussed for their potential to enhance diagnostic precision and treatment planning. Despite its significant advantages, including superior detection of occult lesions, MRI faces challenges such as high costs, accessibility, and occasional diagnostic pitfalls. This review emphasizes MRI's transformative impact on cancer management, discusses its limitations, and highlights ongoing innovations that aim to improve its clinical utility and accessibility. The findings underscore MRI’s pivotal role in enhancing personalized medicine and optimizing therapeutic outcomes for cancer patients.

Dynamic contrast-enhanced and diffusion-weighted MR imaging for predicting tumor growth of sporadic vestibular schwannomas: a prospective study.

Advanced MR imaging, such as diffusion-weighted (DWI) and dynamic contrast-enhanced (DCE) imaging, may provide valuable non-invasive information on intrinsic tumor biology. This study aims to evaluate apparent diffusion coefficient (ADC) and DCE-MRI-derived microvascular parameter values (Ktrans, ve, and vp) as potential imaging predictors for future sporadic vestibular schwannoma (VS) growth. In this prospective cohort study, patients with newly diagnosed unilateral sporadic VS and an initial wait-and-scan strategy were enrolled between January 2021 and January 2023. Patients underwent a single timepoint comprehensive MRI protocol, including DWI and DCE-MRI sequences. The estimated values of ADC, Ktrans, ve, and vp were calculated using established pipelines on a voxelwise basis within the delineated tumor region of interest. Associations of the estimated parameter values with volumetric growth were evaluated in uni- and multivariable logistic regression and survival analyses. Of the 110 analyzed patients, 70 (64%) exhibited growth during follow-up. A significant correlation was primarily observed between the DCE-MRI-derived parameters and VS growth. The combination of mean Ktrans (P<0.001) and ve (P<0.001) tumor values provided an internally validated model with an AUC of 0.85 for growth, yielding a sensitivity of 89% and specificity of 73% at the optimized cutoff value. Only the mean ADC values were found to be significantly higher in shrinking tumors (P=0.04). The strongly significant correlation observed between VS growth and Ktrans and ve tumor values indicates great potential of the non-invasive DCE-MRI for individualized VS management in clinical practice. External validation is needed to further substantiate these findings.

Hyperperfusion and blood-brain barrier disruption beyond the diffusion-restricted infarct one day after successful mechanical thrombectomy.

Patterns of the cerebral microcirculatory response with changes in the blood brain barrier and perfusion in patients with stroke and a large vessel occlusion are still unclear. We combined dynamic contrast enhancement (DCE) permeability and DSC perfusion MRI to detect such patterns beyond the borders of the diffusion-restricted infarct core after successful recanalization. Combined DCE permeability and DSC perfusion MRI were performed prospectively in patients within 24h after successful mechanical recanalization of acute middle cerebral artery occlusion. Perfusion alterations were visually assessed on CBF and CBV maps, blood-brain-barrier disruptions (BBBD) on ktrans-maps and quantitatively evaluated with an ipsi-to contralateral ratio. Additionally, logistic regression analysis was performed for favorable early clinical outcome (NIHSS ≤2 at discharge). N=38 patients were included in the study. Subtle hyperperfusion beyond the DWI-lesion was present in 13/38 patients (34%) on CBF-maps and elevated CBV in 15/38 patients (39%). In these patients, the ratios between ipsi-and contralateral white matter CBF (p=0.01) and CBV (p<0.01) were elevated compared to patients with normal readings. Subtle, but visually and quantitatively elevated ktrans-values outside the DWI-lesion were observed in 7/38 patients (18%). None of these perfusion alterations were related to clinical outcome. Combined DCE-permeability and DSC-perfusion imaging is feasible in patients 24 hours after successful thrombectomy and reveals subtle hyperperfusion and BBBD occuring frequently beyond the diffusion restricted infarct core. DCE = Dynamic Contrast Enhancement, BBBD = blood brain barrier disruption, MT = Mechanical thrombectomy.

A signal model for fat-suppressed T1-mapping and dynamic contrast-enhanced MRI with interrupted spoiled gradient-echo readout.

The conventional gradient-echo steady-state signal model is the basis of various spoiled gradient-echo (SPGR) based quantitative MRI models, including variable flip angle (VFA) MRI and dynamic contrast-enhanced MRI (DCE). However, including preparation pulses, such as fat suppression or saturation bands, disrupts the steady-state and leads to a bias in T1 and DCE parameter estimates. This work introduces a signal model that improves the accuracy of VFA T1-mapping and DCE for interrupted spoiled gradient-echo (I-SPGR) acquisitions. The proposed model was applied to a VFA T1-mapping I-SPGR sequence in the Gold Standard T1-phantom (3T), in the brain of four healthy volunteers (3 T), and to an abdominal DCE examination (1.5T). T1-values obtained with the proposed and conventional model were compared to reference T1-values. Bland-Altman analysis (phantom) and analysis of variance (in vivo) were used to test whether bias from both methods was significantly different (p= 0.05). The proposed model outperformed the conventional model by decreasing the bias in the phantom with respect to the phantom reference values (mean bias -2 vs. -35% at 3T) and in vivo with respect to the conventional SPGR (-6 vs. -37% bias in T1, p< 0.01). The proposed signal model estimated approximately 48% (depending on baseline T1) higher contrast concentrations in vivo, which resulted in decreased DCE pharmacokinetic parameter estimates of up to 35%. The proposed signal model improves the accuracy of quantitative parameter estimation from disrupted steady-state I-SPGR sequences. It therefore provides a flexible method for applying fat suppression, saturation bands, and other preparation pulses in VFA T1-mapping and DCE.

Tumor Morphology for Prediction of Poor Responses Early in Neoadjuvant Chemotherapy for Breast Cancer: A Multicenter Retrospective Study.

This multicenter and retrospective study investigated the additive value of tumor morphologic features derived from the functional tumor volume (FTV) tumor mask at pre-treatment (T0) and the early treatment time point (T1) in the prediction of pathologic outcomes for breast cancer patients undergoing neoadjuvant chemotherapy. A total of 910 patients enrolled in the multicenter I-SPY 2 trial were included. FTV and tumor morphologic features were calculated from the dynamic contrast-enhanced (DCE) MRI. A poor response was defined as a residual cancer burden (RCB) class III (RCB-III) at surgical excision. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive performance. The analysis was performed in the full cohort and in individual sub-cohorts stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status. In the full cohort, the AUCs for the use of the FTV ratio and clinicopathologic data were 0.64 ± 0.03 (mean ± SD [standard deviation]). With morphologic features, the AUC increased significantly to 0.76 ± 0.04 (p < 0.001). The ratio of the surface area to volume ratio between T0 and T1 was found to be the most contributing feature. All top contributing features were from T1. An improvement was also observed in the HR+/HER2- and triple-negative sub-cohorts. The AUC increased significantly from 0.56 ± 0.05 to 0.70 ± 0.06 (p < 0.001) and from 0.65 ± 0.06 to 0.73 ± 0.06 (p < 0.001), respectively, when adding morphologic features. Tumor morphologic features can improve the prediction of RCB-III compared to using FTV only at the early treatment time point.

Natural Evolution of Incomplete Reperfusion in Patients following Endovascular Therapy after Ischemic Stroke.

A third of endovascularly treated stroke patients experience incomplete reperfusion (expanded Thrombolysis in Cerebral Infarction, eTICI<3) and the natural evolution of this incomplete reperfusion remains unknown. We systematically reviewed literature and performed a meta-analysis on the natural evolution of incomplete reperfusion after endovascular therapy. A systematic review of MEDLINE, Embase and PubMed up until March 1, 2024 using a predefined strategy. Only full-text English written articles reporting rates of either favorable (i.e., delayed reperfusion or no new infarct) or unfavorable progression (i.e., persistent perfusion deficit or new infarct) of incompletely reperfused tissue were included. Primary outcome was the rate of delayed reperfusion and its association with functional independence (modified Rankin Scale, mRS 0-2) at 90 days post-intervention. Pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated using a random-effects model. Six studies involving 950 patients (50.7% female; median age 71, IQR 60-79) were included. Four studies assessed the evolution of incomplete reperfusion on MRI perfusion imaging, while two studies used DWI and NCCT imaging, where new infarct was used to denote unfavorable progression. Five studies defined incomplete reperfusion as eTICI2b50 or 2c. Delayed reperfusion occurred in 41% (IQR 33%-51%) of cases 24h post-intervention. Achieving delayed reperfusion was associated with higher likelihood of functional independence at 90 days (OR 2.5, 95%CI 1.9-3.4). Nearly half of eTICI<3 patients achieve delayed reperfusion, leading to favorable clinical outcome. This subgroup may derive limited or potentially harmful effects from pursuing additional reperfusion strategies (e.g., intra-arterial lytics or secondary thrombectomy). Accurately predicting the evolution of incomplete reperfusion could optimize patient selection for adjunctive reperfusion strategies at the end of an intervention.

Added prognostic value of DCE blood volume imaging in patients with suspected recurrent or residual glioblastoma – a hybrid [18F]FET PET/MRI study

Abstract Background MRI cerebral blood volume (CBV) measurements improves diagnosis of recurrent gliomas. The study investigated the prognostic value of dynamic contrast enhanced (DCE) CBV imaging in treated IDH wildtype glioblastoma when added to MRI or amino acid PET. Methods Hybrid [18F]FET PET/MRI with 2CXM (2-compartment exchange model) DCE from 86 adult patients with suspected recurrent or residual glioblastoma were retrospectively analysed. High CBV tumour volume (VOLCBV), and contrast enhancing (VOLCE) and [18F]FET active tumour (VOLFET) volumes were delineated. Absolute and fractional high CBV subvolumes within VOLCE and VOLFET were determined. Associations with overall survival (OS) were assessed by Cox analysis. Results Adjusted for MGMT status and steroid all total tumour volumes were individually associated with shorter OS. Adding VOLCBV to VOLCE, or VOLFET only the effect of VOLCBV was prognostic of OS (HR 1.327, p=0.042 and 1.352, p=0.011, respectively). High CBV subvolume within both VOLCE and VOLFET, were associated with shorter survival (HR 1.448, p=0.042 and 1.416, p=0011, respectively), and the low CBV subvolumes with longer survival (HR 0.504, p=0.002 and 0.365, p=0.001, respectively). The fraction of VOLCE and VOLFET with high CBV was a strong predictor of OS with shorter median OS in upper vs lower tertiles (8.3 vs 14.5 months and 7.1 vs 15.6 months, respectively, both p&amp;lt;0.001). Conclusions The high CBV tumour volume was a strong prognosticator of survival and allowed for separation of high and low risk subvolumes underlining the heterogeneous physiological environment represented in the contrast enhancing or metabolically active tumour volumes of treated glioblastoma.

Enhancing bone metastasis prediction in prostate cancer using quantitative mpMRI features, ISUP grade and PSA density: a machine learning approach.

Bone metastasis is a critical complication in prostate cancer, significantly impacting patient prognosis and quality of life. This study aims to enhance bone metastasis prediction using machine learning (ML) techniques by integrating dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion features, International Society of Urological Pathology (ISUP) grade, and prostate-specific antigen (PSA) density. A retrospective analysis was conducted on 122 patients with histopathologically confirmed prostate cancer who underwent multiparametric prostate magnetic resonance imaging (mpMRI). Quantitative mpMRI features, PSA density, and ISUP grades were extracted and normalized. The dataset was balanced using oversampling and divided into training (70%) and test (30%) sets. Various ML models were developed and evaluated using area under the curve (AUC) metrics. Bone metastases were present in 26 patients (21.3%) at diagnosis. IAUGC and MaxSlope showed a statistically significant association with bone metastasis (p = 0.035, p = 0.050 respectively). The optimal PSA density cut-off value of 0.24 yielded a sensitivity of 0.88, specificity of 0.60, and AUC of 0.77. Machine learning models were developed using the dataset created with IAUGC, MaxSlope, ISUP grade, and PSA density values. Among the ML models, XGBoost demonstrated superior performance with validation and test AUCs of 91.5% and 92.6%, respectively, along with high precision (93.3%) and recall (93.1%). Integrating quantitative mpMRI features, ISUP grade, and PSA density through machine learning algorithms, particularly XGBoost, significantly improves the accuracy of bone metastasis prediction in prostate cancer patients. This approach can potentially reduce the need for additional imaging modalities and associated radiation exposure.

Exam quality of ultrasound and dynamic contrast-enhanced abbreviated MRI and impact on early-stage HCC detection.

MRI is a potential alternative to ultrasound for hepatocellular carcinoma (HCC) detection. We evaluated the impact of ultrasound and dynamic abbreviated MRI (AMRI) exam quality on early-stage HCC detection. We conducted a multicenter case-control study among patients with cirrhosis (cases with early-stage HCC per Milan Criteria; controls without HCC) who underwent both a liver ultrasound and dynamic contrast-enhanced (DCE) AMRI within 6 months in 2012-2019. Two radiologists performed independent, blinded interpretations of both exams for HCC detection and scored exam quality as no/mild, moderate, or severe limitations. Associations between exam quality, patient characteristics, and HCC detection were assessed by odds ratios (OR). Of 216 cases and 432 controls, severe limitations were reported in 7% and 8% of ultrasounds and DCE-AMRIs, respectively. Severe limitations at ultrasound were associated with obesity (OR 2.08, 95%CI [1.32-3.32]) and metabolic dysfunction-associated steatotic liver disease (MASLD) (OR 1.98 [1.12-3.44]) but not for DCE-AMRI. Decompensated cirrhosis (Child-Pugh C) was associated with severe limitations for both ultrasound (OR 2.54 [1.37-4.58]) and DCE-AMRI (OR 3.96 [2.36-6.58]). Compared to exams with no/mild limitations, exams with severe limitations had lower sensitivity for ultrasound (79.6% vs. 21.7%, P < 0.001) and AMRI (86.1% vs. 50.0%, P = 0.001). In patients in whom ultrasound was severely limited, DCE-AMRI had significantly higher odds of early-stage HCC detection than ultrasound (OR 8.23 [1.25-54.02]). HCC detection by DCE-AMRI may be preferred in patients with severe limitations at ultrasound due to obesity and MASLD. Both modalities remain limited for patients with decompensated cirrhosis, for whom alternative strategies may be needed.

Performance of an AI-powered visualization software platform for precision surgery in breast cancer patients

Surgery remains the primary treatment modality in the management of early-stage invasive breast cancer. Artificial intelligence (AI)-powered visualization platforms offer the compelling potential to aid surgeons in evaluating the tumor’s location and morphology within the breast and accordingly optimize their surgical approach. We sought to validate an AI platform that employs dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to render three-dimensional (3D) representations of the tumor and 5 additional chest tissues, offering clear visualizations as well as functionalities for quantifying tumor morphology, tumor-to-landmark structure distances, excision volumes, and approximate surgical margins. This retrospective study assessed the visualization platform’s performance on 100 cases with ground-truth labels vetted by 2 breast-specialized radiologists. We assessed features including automatic AI-generated clinical metrics (e.g., tumor dimensions) as well as visualization tools including convex hulls at desired margins around the tumor to help visualize lumpectomy volume. The statistical performance of the platform’s automated features was robust and within the range of inter-radiologist variability. These detailed 3D tumor and surrounding multi-tissue depictions offer both qualitative and quantitative comprehension of cancer topology and may aid in formulating an optimal surgical approach for breast cancer treatment. We further establish the framework for broader data integration into the platform to enhance precision cancer care.

Loss of aquaporin-4 impairs cerebrospinal fluid solute clearance through cerebrospinal fluid drainage pathways

The aquaporin-4 (AQP4) water channel is essential in neurofluid dynamics. AQP4 loss impairs solute exchange between the cerebrospinal fluid (CSF) and interstitial fluid (ISF). However, whether AQP4 expression affects solute clearance from the CSF space to the extracranial space remains unclear. This study aimed to investigate this using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) following the intrathecal administration of gadolinium-based contrast agents (GBCAs) to AQP4 knockout (KO) rats. AQP4 KO rats showed reduced efflux of intrathecal GBCAs to the extracranial spaces through CSF drainage pathways and increased retention of intrathecal GBCAs in the CSF space compared with the controls. These results suggest that AQP4 loss impairs solute clearance from the CSF space to the extracranial spaces via the CSF drainage pathways. This study revealed a close relationship between AQP4 expression and CSF solute clearance, contributing to a better understanding of the function of AQP4 in neurofluid dynamics.

Prediction of genetic profile of breast carcinoma on MRI using a combination of DCE‐MRI, DWI, and MR spectroscopy: A prospective observational study

AbstractBackgroundClassification of breast cancer based on gene expression has emerged as the standard approach in its management, owing to the distinct prognoses and treatment responses observed among different subtypes. The aim of this study was to prospectively assess the imaging features of the molecular subtypes of breast cancer using multiparametric magnetic resonance imaging (mMRI) with the combined assessment of dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI), diffusion‐weighted imaging (DWI), and MR spectroscopy (MRS).MethodsThis was a prospective observational single‐center cohort study, which included women with BI‐RADS 4−5 lesions on mammography/ultrasound (US) who subsequently underwent 1.5 T MRI (encompassing DCE‐MRI, DWI, and MRS). The histological subtypes of breast cancer were assessed. Estrogen receptor (ER), progesterone receptor (PR), Ki‐67 status, and human epidermal growth receptor‐2 (HER2) expression, assessed by immunohistochemistry (IHC), defined four molecular subtypes: luminal A, luminal B, HER2‐enriched (Her2en), and triple‐negative breast carcinoma (TNBC). Statistical associations between the four molecular subtypes and MRI features were investigated.ResultsFifty patients were included in the study. Circumscribed margins were significantly correlated with triple‐negative tumors compared to others (78% versus 6%, p &lt; 0.001). Spiculated margins were observed in non‐triple negative tumors. Rim enhancement was significantly correlated to triple‐negative tumors compared to all other subtypes (71.4% versus 25%, p = 0.035). Mean apparent diffusion coefficient (ADC) values were significantly lower for luminal subtypes compared to non‐luminal subtypes (p &lt; 0.001). The total choline (tCho) signal‐to‐noise ratio (SNR) was higher in triple‐negative tumors. A combined algorithm using DCE‐MRI, DWI, and MRS can predict TNBC and Her2en with specificity of 86.6% and 100%, respectively, and sensitivity of 100% and 85.37%, respectively.ConclusionThe combination of mMRI with DCE‐MRI, DWI, and MRS can accurately differentiate the molecular subtypes of breast carcinoma.

Added-value of dynamic contrast-enhanced MRI to conventional MRI for the differentiation between inflammatory myofibroblastic tumor and squamous cell carcinoma in the sinonasal region.

The purpose of this study was to evaluate the additional value of dynamic contrast-enhanced (DCE) MRI and diffusion weighted MRI (DWI) in differentiation between inflammatory myofibroblastic tumor (IMT) and squamous cell carcinoma (SCC) in the sinonasal cavity. Patients with pathologically proven IMT and SCC in the sinonasal region were enrolled in this retrospective study. All participants underwent conventional MRI and dynamic contrast-enhanced MRI, while a subset of them performed DWI. All the MRI parameters were independently analyzed by two investigators. This retrospective study included 21 patients with IMT and 55 patients with SCC. Significant differences were found in the conventional MR imaging features including mass margin, T2 signal intensity and track sign of maxillary (p < 0.05). For DCE-MRI features, significant differences were found in progressive centripetal continual enhancement and CImax (p < 0.001 and p = 0.026, respectively). A marginal significant difference was found in ADC values between IMT (0.86 ± 0.59) and SCC (1.14 ± 0.25) (p = 0.061). The conventional MRI analysis revealed that the combination of mass margin and track sign of maxillary yielded an accuracy of 81.6%. Using a combination of progressive centripetal continual enhancement on DCE-MRI and track sign of maxillary in multivariate logistic regression analysis, the accuracy was elevated to 92.1%. The incorporation of DCE-MRI features into conventional MRI showed improved diagnostic performance in differentiating IMT from SCC in the sinonasal region. The novel progressive centripetal continual enhancement on DCE-MRI is the most effective feature of IMT.

Abstract 4137891: Treated HIV infection is not associated with carotid vascular inflammation or plaque progression as assessed by dynamic contrast magnetic resonance imaging

Background: Inflammation and immune dysregulation are thought to drive residual cardiovascular disease risk among persons living with HIV (PLWH) despite effective viral suppression with antiretroviral therapy (ART). Question: We investigated differences in carotid vascular inflammation and atherosclerosis in a longitudinal cohort of virally suppressed PLWH (n = 50; on stable ART with CD4 &gt;250 cells/mm 3 , viral load &lt;200 copies/mL for &gt;6 months) and HIV-uninfected controls (n = 51) matched for age, sex, hypertension, diabetes, smoking, hyperlipidemia, and family history of premature coronary artery disease. Methods&amp;Results: Participants were &gt; 40 years old at enrollment, 8% female, and had a high prevalence of cardiovascular risk factors ( Table 1 ). Measures of carotid inflammation and capillary permeability ( K trans ), neovascularization ( V p ), and wall thickness were assessed at baseline, 1 year, and change over 1 year by dynamic contrast-enhanced magnetic resonance imaging. Both PLWH and controls demonstrated a reduction in systolic and diastolic blood pressures and total cholesterol over 1 year; however, the difference was not significant by HIV status. PLWH had a significant reduction in triglycerides compared with controls (-48.8 mg/dL vs 12.8 mg/dL; p = 0.026). HIV was not associated with baseline, follow-up, or change in markers of systemic inflammation assessed by plasma cytokines (C-reactive protein, interleukin-6, interleukin-1ß), nor vascular inflammation or plaque as assessed by K trans , V p , carotid wall thickness, or percent wall volume ( Tables 2 &amp; 3 ). Conclusions: In contrast to other studies of chronically treated and virally suppressed PLWH, HIV infection was not associated with carotid inflammation or plaque.

Evaluations of a Cutaneous Wound Healing Model Using Oxygen Enhanced - Dynamic Contrast Enhanced Photoacoustic Imaging (OE-DCE PAI).

Preclinical models of cutaneous wound healing can be useful for improving clinical wound care. Oxygen Enhanced Photoacoustic imaging (OE PAI) can measure oxygenation, and Dynamic Contrast Enhanced (DCE) PAI can measure vascular perfusion. We investigated how a combined OE-DCE PAI protocol can measure vascular oxygenation and perfusion to a cutaneous healing model. We developed a cutaneous "punch" wound model and photographed the wounds to track healing for 9 days. We performed OE-DCE PAI on Day 0, 3, 6, and 9. OE PAI was performed with 21% O2 and 100% O2 breathing gases to measure oxyhemoglobin (HbO2), deoxyhemoglobin (Hb), total hemoglobin (HbT), and oxygen saturation (%sO2), along with changes in these parameters caused by a change in breathing gas (ΔHb, ΔHbO2, ΔHbT, ΔsO2). To perform DCE PAI, indocyanine green (ICG) was administered intravenously while monitoring the PAI signal for 10min as the agent washed through the wound area, which was used to evaluate the wash-out rate. The average wound size was significantly smaller only by Day 6. For comparison, OE PAI measured a significant increase in HbO2, Hb, HbT, and %sO2 immediately after creating the wound, which significantly decreased by Day 3 and continued to decrease towards values for normal tissue by Day 9. The vascular wash-out rate significantly increased by Day 3, and continued to increase during the healing process. Notably, the wash-out rate can be assessed at a single PAI absorbance wavelength and by simply comparing signal amplitudes without advanced analysis, which may facilitate clinical translation. OE-DCE PAI can monitor significant changes in vascular perfusion and oxygenation prior to significant changes in cutaneous wound size. These results establish OE-DCE PAI as a tool for future pre-clinical wound healing studies and eventual clinical translation.

Abstract 4134729: Quantitative, time-efficient viability cardiac magnetic resonance with delayed-phase dynamic contrast enhancement model: a pilot study in dogs with myocardial infarction

Introduction: Late gadolinium enhancement (LGE) is the gold standard for myocardial viability imaging, recommended by all major cardiology societies. In this study, we aimed to develop a time-efficient viability imaging technique utilizing a dynamic contrast enhancement(dDCE) model to shorten the LGE wait time, provide quantitative measures of the contrast washout procedure, and potentially enable a fast and quantitative mean for scar imaging. Methods: A canine study(n=10) was conducted on reperfused myocardial infarction(MI). A dDCE model using dynamic post-contrast T1 maps was adopted to depict the contrast washout process. dDCE maps were reconstructed using the whole dataset(dDCE 30min ) and a 5-minute subset of the T1 maps(dDCE 5min ). To test the dDCE models for shortening the LGE wait time, LGE dDCE images were synthesized using the dDCE 5min maps and compared to the clinical LGE images. Remote and MI dDCE parameters on dDCE 30min and dDCE 5min maps were compared to test the model's ability to extract physiological features. Results: dDCE 30min and dDCE 5min map showed a good visuospatial difference between remote and MI(Fig. 1A) and no quantitative difference (Fig.1B). v e and PS showed a significant elevation in MI than in remote (61.12±13.65% vs 13.43±5.00%, P =0.018; 44.62±21.40mL/g/min vs 0.42±0.55mL/g/min, P =0.018, respectively). v p and F p were significantly decreased in MI than in remote (4.17±2.06% vs 10.85±3.77%, P =0.02; 1.11±0.32mL/g/min vs 1.51±0.42mL/g/min, P =0.04, respectively). Representative LGE and LGE dDCE images showed high agreement in the presence of MI (Fig. 2A). Bland-Altman analysis showed good agreement between LGE and LGE dDCE images for the measurement of infarct area (bias, -1.74 ± 6.60 %, Fig. 2B) and transmuraltiy (bias, 1.86 ± 2.73 %, Fig. 2C). The simple liner regression showed strong correlations between LGE and LGE dDCE images for the infarct area (R 2 , 0.95; slope, 0.93, P &lt;0.01; Fig. 2D) and transmurality (R 2 , 0.97; slope, 0.93, P &lt;0.01; Fig. 2E). ROC analysis showed that the AUC was 0.97 (95% CI: 0.94 to 1.00) (Fig. 2F). Increased lesion-blood pool contrast by 10 folds on dDCE images improved subendocardial MI detection (Fig.3). Conclusions: The developed dDCE model provides comparable viability assessment ability to the standard LGE images without the prolonged wait time and reflects MI pathophysiological changes. It shows the potential for a rapid and quantitative myocardial viability imaging protocol using cardiac magnetic resonance.

NIMG-36. PERFUSION, DIFFUSION, AND ANATOMICAL MRI BIOMARKERS FOR ASSESSING HISTOLOGICALLY-CONFIRMED MALIGNANT TRANSFORMATION IN MOLECULAR SUBTYPES OF IDH-MUTANT GLIOMAS

Abstract BACKGROUND Isocitrate dehydrogenase-mutant (IDHm) gliomas often initially present as low-grade (grade 2) gliomas but are expected to later progress into more aggressive higher-grade (grade 3-4) gliomas through malignant transformation (MT). MT is often determined non-invasively by emergence of contrast-enhancement on post-contrast T1-weighted magnetic resonance imaging (MRI), but contrast-enhancement is an imperfect surrogate for histologically-confirmed MT. This study explored perfusion, diffusion, and anatomical MRI biomarkers besides contrast-enhancement to study histologically-confirmed MT in IDHm 1p/19q-intact astrocytomas (IDHm-A) and IDHm 1p/19q-co-deleted oligodendrogliomas (IDHm-O). METHODS N=64 patients with initial histopathological grade 2 IDH-mutant glioma diagnosis who underwent repeated tissue sampling and were classified as histologically-confirmed MT (n=35) or non-MT (n=29) were retrospectively studied. Pre-surgical anatomical MRI (n=64) and, if available, diffusion-weighted imaging (n=61) and dynamic susceptibility contrast perfusion MRI (n=53) were analyzed. Tumor volumes of interest were segmented on the whole T2/FLAIR-hyperintense tumor. Measurable contrast enhancement (&amp;gt;1000mm3), tumor volume, sphericity, median apparent diffusion coefficient (ADC), and normalized relative cerebral blood volume (nrCBV) were compared between MT vs. non-MT IDHm-A and IDHm-O. RESULTS 81% of contrast-enhancing IDHm-A and 100% of contrast-enhancing IDHm-O underwent MT, while 41% of MT IDHm-A and 62% of MT IDHm-O were non-enhancing. Tumor volumes were significantly larger in the MT vs. non-MT groups for both IDHm-A (P=0.02) and IDHm-O (P=0.04). Whole tumor nrCBV was significantly higher (P=0.002), whole tumor ADC trended lower (P=0.06), and non-enhancing tumor sphericity was significantly lower (P=0.03) in MT vs. non-MT IDHm-A. There were no significant differences in ADC, nrCBV, nor sphericity when comparing MT vs. non-MT IDHm-O (P&amp;gt;0.05). CONCLUSIONS Many MT IDHm-gliomas remain non-enhancing. Tumor volumes can determine MT for both IDHm-A and IDHm-O. Diffusion and perfusion MRI show differences for MT in IDHm-A but not IDHm-O, which may reflect the different tumor biology of these IDHm molecular subtypes and their need for separate imaging biomarkers.

Comparing DCE-MRI and DSA: Understanding the embolization of hypervascular spinal metastases.

This study aims to examine and compare the effectiveness of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and Digital Subtraction Angiography (DSA) in evaluating hypervascular spinal metastases. A comprehensive literature review was conducted, utilizing top-tier databases such as PubMed, Scopus and Google Scholar, to compile an authoritative and up-to-date overview of the current advancements in the field. We synthesized key studies focusing on the advantages, limitations and efficacy of both imaging techniques. DCE-MRI provides a non-invasive method for evaluating tissue morphology, perfusion and vascularity, offering valuable information for cancer diagnosis and treatment monitoring. In contrast, DSA is an invasive procedure primarily used for embolization and diagnosing cerebrovascular events. Both modalities have distinct features regarding image acquisition, contrast agents, resolution and accessibility. DCE-MRI shows promise for cancer-related applications, offering advantages over conventional MRI by incorporating anatomical and hemodynamic parameters. While DSA remains important for cases requiring critical vascular information, further research is necessary to explore its potential therapeutic benefits in assessing vessel patency. Continued investigations are crucial to uncover additional insights and therapeutic applications for both DCE-MRI and DSA in medical imaging.

NIMG-37. “SYNTHETIC” PERFUSION MRI WITH ADJUSTABLE ACQUISITION PARAMETERS IN BRAIN TUMORS USING DYNAMIC SPIN-AND-GRADIENT-ECHO ECHOPLANAR IMAGING

Abstract INTRODUCTION Dynamic susceptibility contrast (DSC) perfusion MRI can assess normalized relative cerebral blood volume (nrCBV) and percentage of signal recovery (PSR) in brain tumors, which can aid in differential diagnosis, molecular profiling, and identification of disease progression. However, CBV-optimized and PSR-optimized protocols differ in terms of acquisition parameters. Additionally, DSC dependency on acquisition parameters limits the universalizability of diagnostic cutoffs for nrCBV and PSR across institutions and scanners. This study aims to generate “synthetic” DSC datasets with adjustable synthetic acquisition parameters using dynamic spin-and-gradient-echo echoplanar imaging (dynamic SAGE-EPI) to: 1) simultaneously generate nrCBV and PSR with optimal acquisition parameters, 2) compare DSC datasets with heterogeneous external cohorts. METHODS Thirty-eight patients with contrast-enhancing brain tumors were prospectively imaged with dynamic SAGE-EPI during a non-preloaded single-dose contrast injection. Multiple synthetic DSC datasets with desired pulse sequence parameters were generated using the Bloch equations applied to the dual-echo gradient-echo (GE) data extracted from dynamic SAGE-EPI datasets, with or without optional preload simulation. For each patient, synthetic protocols were set to match guideline-compliant CBV-optimized protocols, PSR-optimized protocols, and protocols used in external cohorts from the literature, for comparison. RESULTS Dynamic SAGE-EPI allowed for simultaneous generation of CBV-optimized and PSR-optimized DSC datasets with a single contrast injection. Conversely, suboptimal PSR computation from guideline-compliant CBV-optimized protocols resulted in rank variations within the cohort (Spearman’s ρ=0.83-0.89, i.e. 31%-21% rank variation). Treatment-naïve glioblastoma exhibited lower parameter-matched PSR compared to the external cohorts of treatment-naïve primary CNS lymphomas (PCNSL) (p&amp;lt;0.0001), supporting a role of synthetic DSC for multicenter comparisons. CONCLUSIONS Dynamic SAGE-EPI allows for simultaneous generation of CBV-optimized and PSR-optimized DSC data with a single injection, facilitating use of a single perfusion protocol for all DSC applications. This approach may also be useful for comparisons of perfusion parameters across heterogeneous multicenter datasets.