Dynamic Contrast-enhanced Research Articles

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 < 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 < 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.

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 >250 cells/mm 3 , viral load <200 copies/mL for >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&Results: Participants were > 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 & 3 ). Conclusions: In contrast to other studies of chronically treated and virally suppressed PLWH, HIV infection was not associated with carotid inflammation or plaque.

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 <0.01; Fig. 2D) and transmurality (R 2 , 0.97; slope, 0.93, P <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 (>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>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.

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<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.

BIOM-54. AI-DRIVEN RISK-OF-PROGRESSION (AIRIP) CLASSIFIER FOR DISTINGUISHING RECURRENT BRAIN METASTASES FROM RADIATION TREATMENT EFFECT: A MULTI-INSTITUTIONAL COMPARATIVE STUDY WITH ADVANCED MULTIMODAL IMAGING

Abstract Following radiation therapy, a significant challenge in brain metastases (BM) management is differentiating radiation-induced-treatment effect (TrE) from tumor recurrence (TuR). TrE can be indistinguishable from TuR using conventional MRI. Advanced imaging techniques (e.g., perfusion MRI, PET/MRI) are not consistently used, and the standardized Response Assessment in Neuro-Oncology for brain metastases (RANO-BM) is sensitive to inter-reader variability. The performance of an artificial intelligence (AI)-driven risk-of-progression (AiRiP) classifier, which has been shown to capture pathophysiologic differences between TrE and TuR on routine MRI, was compared to that of clinical assessments and advanced imaging methods, in a multi-institutional setting. A total of n=261 lesions with pathologically-confirmed diagnoses in n=189 patients were analyzed. 115 lesions (73 TuR, 42 TrE) from site 1, 86 lesions (38 TuR, 48 TrE) from site 2, and 60 lesions (33 TuR, 27 TrE) from site 3 were used for training and testing the AiRiP-model. Gd-T1w, T2w, FLAIR MRI were preprocessed, and lesions were segmented by experts. Texture features (n=856) were extracted from each lesion. Random-forest classifier was employed for 3-fold cross-validation. Top-performing AiRiP-features, RANO-BM criteria, perfusion MRI and PET/MRI were evaluated in a sub-group analysis. For n=51 lesions on the test-set (site 3), 14 were classified as stable disease and 37 as TuR using RANO-BM (accuracy=54.1%). AiRiP-model achieved an accuracy of 76.5% on the same test-set and accurately classified 78.6% of the stable lesions as TrE or TuR. For another subset of lesions (n=27) on the same test-set, perfusion MRI and AiRiP-model achieved an accuracy of 59.3% and 70.4%, respectively. Lastly, for a subset of lesions (n=35) on the test-set (site 2), multimodal (perfusion, PET) imaging and AiRiP-model accurately classified 60% and 74.3% of lesions, respectively. 15 lesions were considered indeterminate via multimodal imaging, 73.3% of which AiRiP-model accurately classified as TrE or TuR. Our results suggest AI-driven models on conventional MRI may reliably distinguish TuR from TrE.

A scoping review of magnetic resonance angiography and perfusion image synthesis

IntroductionDeregulation of the cerebrovascular system has been linked to neurodegeneration, part of a putative causal pathway into etiologies such as Alzheimer's disease (AD). In medical imaging, time-of-flight magnetic resonance angiography (TOF-MRA) and perfusion MRI are the most common modalities used to study this system. However, due to lack of resources, many large-scale studies of AD are not acquiring these images; this creates a conundrum, as the lack of evidence limits our knowledge of the interaction between the cerebrovascular system and AD. Deep learning approaches have been used in recent developments to generate synthetic medical images from existing contrasts. In this review, we study the use of artificial intelligence in the generation of synthetic TOF-MRA and perfusion-related images from existing neuroanatomical and neurovascular acquisitions for the study of the cerebrovascular system.MethodFollowing the PRISMA reporting guidelines we conducted a scoping review of 729 studies relating to image synthesis of TOF-MRA or perfusion imaging, from which 13 met our criteria.ResultsStudies showed that T1-w, T2-w, and FLAIR can be used to synthesize perfusion map and TOF-MRA. Other studies demonstrated that synthetic images could have a greater signal-to-noise ratio compared to real images and that some models trained on healthy subjects could generalize their outputs to an unseen population, such as stroke patients.DiscussionThese findings suggest that generating TOF-MRA and perfusion MRI images holds significant potential for enhancing neurovascular studies, particularly in cases where direct acquisition is not feasible. This approach could provide valuable insights for retrospective studies of several cerebrovascular related diseases such as stroke and AD. While promising, further research is needed to assess their sensitivity and specificity, and ensure their applicability across diverse populations. The use of models to generate TOF-MRA and perfusion MRI using commonly acquired data could be the key for the retrospective study of the cerebrovascular system and elucidate its role in the development of dementia.

NIMG-57. EMBEDDED GRAPH DERIVED FROM PSEUDO-RESTING-STATE FUNCTIONAL MRI CAN PREDICT COGNITIVE IMPAIRMENT IN GLIOMA

Abstract Resting-state brain network analyses are of great interest in studying the neurocognition and measuring the functional connectivity (FC) patterns of glioma patients. However, resting-state functional MRI (rs-fMRI) is not assessed in clinical routine due to the scan time and cost. The current study used pseudo-resting-state functional MRI (pseudo-rs-fMRI) derived from dynamic susceptibility contrast (DSC) perfusion MRI to predict cognitive impairment in glioma. 37 glioma patients were enrolled consecutively in the current study with DSC perfusion MRI acquired and neurocognition assessed, where 24 glioma patients also got rs-fMRI collected. The pseudo-rs-fMRI was created by voxel-wise subtracting the Gamma-variate modeled signal of contrast agent bolus from the original DSC perfusion signal. Following the pre-processing of pseudo-rs-fMRI and full rs-fMRI, the functional connectivity network (FCN) was established for each patient. Graph embedding was implemented to learn and extract features of each node in the binarized FCN, and the decision tree classification algorithm was applied to distinguish cognitive impairment. FCNs of 24 patients with DSC perfusion and rs-fMRI acquired were used to train the model, and FCNs of 13 patients with only DSC perfusion MRI acquired were used to test the model. The AUC (area under the receiver operating characteristic curve) was used to evaluate the model’s performance. The similarity and mean-square-difference between average FCNs extracted from rs-fMRI and pseudo-rs-fMRI were 0.6769 and 0.0263, respectively. Classifier trained using 24 FCNs of pseudo-rs-fMRI has an AUC of 0.750 in identifying cognitively impaired patients in the testing cohort. Combining FCNs of both rs-fMRI and pseudo-rs-fMRI to train the classifier resulted in a higher AUC of 0.833 in the testing cohort. To summary, DSC perfusion MRI-derived pseudo-rs-fMRI can be used to predict cognitive impairment in patients with gliomas. External validation would be required.

NIMG-88. EVALUATION OF DIFFUSION AND PERFUSION MRI FEATURES FOR DIFFERENTIATING RECURRENT BRAIN METASTASES AND RADIATION NECROSIS

Abstract BACKGROUND Brain metastases (BM) are a frequent and serious complication of cancer. Differentiating between BM and radiation-induced necrosis (RN) after radiotherapy remains challenging. Diffusion-weighted imaging (DWI) derived apparent diffusion coefficient (ADC) maps and perfusion-weighted imaging (PWI) derived relative cerebral blood volume (rCBV) have the potential to distinguish between BM and RN. Despite the potential of these imaging modalities, previous studies have been limited by the absence of histopathological confirmation. In this study, we utilized a patient cohort that underwent stereotactic biopsy as part of their Laser Interstitial Thermal Therapy (LITT) following suspicious radiographic progression. This allowed us to evaluate the efficacy of ADC and rCBV imaging features with histopathological validation. METHODS In this study, 29 patients underwent MRI scans (3 with 1.5T, 26 with 3T) prior to LITT. Pathology confirmed 11 patients with BM and 18 with RN. Regions of interest (ROIs) in the contrast-enhanced lesion and T2 hyperintensity lesion were identified using post-contrast T1-weighted images and fluid-attenuated inversion recovery (FLAIR) images. Mean values and histogram-based features (standard deviation, 10%, 90%) of lesion volume, ADC, and rCBV within tumor ROIs were compared between the BM and RN using the Wilcoxon rank-sum test. RESULTS Our findings indicated that the mean values of ADC in the enhancing and non-enhancing lesion ROIs did not significantly differ between BM and RN patients. However, in the contrast-enhanced lesion regions, we observed a significant difference in the standard deviation of rCBV (p<0.05), and the 90th percentile value of rCBV also suggested potential differences between BM and RN (p=0.069). In the T2 hyperintensity lesion regions, lesion volume (p<0.05) and the mean of rCBV (p<0.05) show significant differences between BM and RN. CONCLUSION This study demonstrates the potential of using rCBV to aid in the clinical diagnosis of BM. Additionally, our findings indicate that T2 hyperintensity regions, beyond just contrast-enhancing lesions, may provide valuable information for differential diagnosis.

NIMG-84. BELZUTIFAN REDUCTION OF CEREBRAL BLOOD FLOW IN VHL-ASSOCIATED HEMANGIOBLASTOMA PREDICTS RESPONSE TO TREATMENT

Abstract Hemangioblastoma (HMB) is a vascular-origin tumor occurring primarily in the cerebellum. Treatment typically involves surgical resection of the solid part of the tumor or stereotactic radiosurgery. An emerging treatment for hemangioblastoma is belzutifan (BZF), a hypoxia-inducible factor 2a (HIF2a) inhibitor. A recent trial found BZF to control hemangioblastoma in patients with von Hippel Lindau (vHL) syndrome. Perfusion MRI techniques including arterial spin labelling (ASL) and can be used to determine relative cerebral blood flow (rCBF). No prior studies have investigated rCBF in hemangioblastoma with relation to belzutifan, and the mechanism of action of belzutifan on hemangioblastoma is not well understood. Here, we aim to measure the response in rCBF in patients with vHL-associated hemangioblastoma treated with belzutifan. This retrospective cohort study constituted a group of seven patients with vHL-associated hemangioblastoma treated with Belzutifan at a daily oral dose of 120mg. Perfusion MRI with ASL sequences were acquired as part of the tumor imaging protocol. We quantified rCBF of the tumors prior to treatment, following intiation of BZF, and at most recent follow-up. Statistics were performed using R studio. The long axis diameter, volume of the solid tumor, rCBF mean, rCBF max, N mean, N max of lesions all decreased after Belzutifan treatment (p<0.001). While the long axis diameter of the cyst in cystic lesions did not show statistically significant change, the volume of cysts decreased significantly on Belzutifan (p=0.016). Spearman’s rank correlation analysis demonstrated association between change in rCBF mean, rCBF max, N mean and N max to % reduction in tumor volume. In addition, change in rCBF mean, change in rCBF max and change in N max all showed statistically significant association on multiple linear regression. Finally, early change in CBF and N predicted further volumetric response to treatment with belzutifan. We demonstrate that vHL-associated hemangioblastoma demonstrates decrease in rCBF in conjunction with and predictive of decreased volume following treatment with belzutifan.

NIMG-29. EARLY REDUCTION IN MRI DIFFUSION APPARENT DIFFUSION COEFFICIENT (ADC) STRONGLY PREDICTS LONG TERM RESPONSE TO ONC201 THERAPY IN PATIENTS WITH H3K27M-DMG

Abstract ONC201 is the first monotherapy to improve outcomes in H3K27M- diffuse midline glioma (DMG) beyond radiation. Despite impressive early efficacy in H3K27M-DMG, individual response to ONC201 is variable and no radiographic biomarkers predict long term response. Previous studies demonstrated baseline MRI diffusion apparent diffusion coefficient (ADC) is lower in DMG with H3K27M compared to wildtype but change after radiation therapy was not correlated with improved OS or PFS. We hypothesize ADC will enable stratification of patients more likely to respond to ONC201. Imaging and clinical data were abstracted from chart review of patients treated with ONC201 at University of Michigan. Two neuroradiologists performed centralized review for RAPNO measurements and mean ADC was assessed using ROI measured in consistent anatomic locations, with areas of cystic degeneration or necrosis excluded. Sixty-one patients were identified for review. Preliminary analysis was performed on twenty-three patients, with upfront ONC201 therapy, median age 14.8 years old (5-25yo), primary site includes pontine (n=15), thalamic (n=7). Baseline characteristics of age, ADC and size at diagnosis or follow-up RAPNO scored size were not statistically significant. Patients with longer than median survival (334 days) demonstrated increased ADC (+58.25x10-6mm2/s) from baseline to cycle 2 whereas patients with shorter than median survival demonstrated decreased ADC (-174.8x10-6mm2/s) (p = 0.0076). Further, patients with decreased ADC demonstrated mean OS of 302.8 days and patients with increased ADC had mean OS of 588.0 (p = 0.0054). In H3K27M-DMG patients treated with ONC201, increased ADC after two cycles of ONC201 was strongly predictive of longer overall survival. Our recent work demonstrated that ONC201 disrupts metabolic and epigenetic pathways to restore pathognomonic H3K27me3 reduction, which may underline greater change in ADC. Ongoing work will validate these findings in an independent external cohort and integrate histogram analysis, parametric assessments, MRI perfusion and liquid biopsy biomarkers (cf-tDNA and metabolomics).

NIMG-23. A NOVEL APPROACH TO PERFUSION MRI STUDIES IN BRAIN TUMOR PATIENTS USING ENDOGENOUS DEOXYHEMOGLOBIN AS A CONTRAST AGENT: A PROOF-OF-CONCEPT STUDY

Abstract BACKGROUND Assessment of resting perfusion in brain tumors is clinically relevant and relies on dynamic susceptibility contrast magnetic resonance imaging using gadolinium contrast. Preliminary studies have introduced the use of controlled hemoglobin desaturation by means of a transient hypoxic stimulus during echo-planar imaging(EPI) as a surrogate for gadolinium for resting perfusion assessment in healthy subjects. In this proof of concept study, we investigated whether this approach is feasible in brain tumors and warrant further validation. METHODS A computer controlled gas blender was used to induce transient and standardized hypoxic stimulus in isocapnic conditions during EPI acquisition in a heterogenous cohort of tumor patients. The induced blood-oxygen-level-dependent(BOLD) signal changes determined by transit of a bolus of deoxygenated blood in the brain vasculature were used as a surrogate of gadolinium to calculate cerebral blood volume(CBV), cerebral blood flow(CBF) and mean transit time(MTT) using a global arterial input functions obtained through the BOLD signal measured over the middle cerebral artery as previously described by Poublanc et al. Perfusion parameters were calculated in the whole-brain voxel-by-voxel and in automatically segmented region of interest(ROI) using SPM, AFNI, Verbena softwares and MATLAB in-house written scripts. RESULTS Nine patients were included. MTT, rCBV, rCBF were calculated voxel-per-voxel. Obtained maps were overlayed on the co-registered T1 MRI scans and compared to T1CE and FLAIR to identify perfusion patterns in tumor ROIs (contrast enhancement, edema, necrosis). The deoxy-hemoglobin BOLD MRI perfusion were compared to clinical DSC-MRI when available and showed high qualitative agreement. CONCLUSION Transient and precise hemoglobin desaturation by controlled hypoxic gas modulation is safe and repeatable in brain tumor patients. The induced BOLD signal change allows measurement of resting perfusion, which qualitatively closely mimic gadolinium perfusion in different brain tumors. Deoxyhemoglobin-based perfusion warrant further quantitative validation against gadolinium in a larger cohort of heterogenous tumor patients.

ANGI-07. A CASE OF HYPERBARIC OXYGEN USED AS A TREATMENT MODALITY FOR ANAPLASTIC ASTROCYTOMA

Abstract Although its precise mechanism is unclear, hyperbaric oxygen is thought to impede the growth of tumor cells by inhibiting tumor hypoxia, a known driver for angiogenesis. We present a case of a 32-year-old pilot who developed sudden onset aphasia and disorientation which led to hospitalization and imaging. He was diagnosed with anaplastic astrocytoma and underwent resection, radiation, and chemotherapy with temozolomide. Approximately one year later, MRI showed enlarging non-enhancing T2/FLAIR hyperintense mass in the right temporal lobe. He received 4 cycles of lomustine. Four months later, MRI showed slight increase in the size of ring enhancement around the treatment area. These findings were thought to be related to treatment-related changes. After 4 doses of bevacizumab every 2 weeks, there was improvement in surrounding vasogenic edema. However, after 7 doses, his MRI brain demonstrated increase in treatment-related changes with more vasogenic edema. He also had worsening left-sided weakness, unable to lift his left arm against gravity, dysarthria, and cognitive slowing. MRI perfusion supported treatment-related changes rather than tumor growth. He then started hyperbaric oxygen treatments and after 20 sessions of treatment, his vasogenic edema and his left-sided weakness improved. After 60 sessions of hyperbaric oxygen, he noticed further improvement in his strength and short-term memory. Four months after completion of his hyperbaric oxygen, he was found to have increasing size of ring-enhancing lesion and was restarted on hyperbaric oxygen treatments in addition to bevacizumab and low-dose temozolomide. He completed a total of 100 rounds of hyperbaric treatments. MRI showed improvement and stability. His left-sided weakness continued to improve. Hyperbaric oxygen alone or combined with other treatment modalities may be a promising therapy to improve quality of life. Further research will assist with mechanisms through which hyperbaric oxygen works and patient outcomes.

MR tomographic evaluation of the effectiveness of neoadjuvant chemotherapy for breast cancer based on pharmacokinetic numerical analysis of tumor uptake of paramagnetic contrast in intravenous contrast enhancement

Background. In clinical practice, MRI pathophysiological and pharmacokinetic models with calculations of contrast transport indicators are unacceptably little used.Aim of the study. To propose a pharmacokinetic technique for the quantitative assessment of primary tumors and metastases, the effectiveness of breast cancer chemotherapy (BC), from dynamic contrast enhancement MRI. Material and methods. 18 patients were included who underwent neoadjuvant chemotherapy (NACHT) in four cycles for breast cancer T1-3N0-1M0, followed by radical surgical removal of the tumor. According to the results of a three — year follow-up, patients with a relapse — free course (n = 11) formed group 1, and seven patients with detected metastatic lesions (3 in the liver, 2 in the lungs, 2 in the brain) — group 2. For the initial 120–180 s of MRI with contrast after the injection of a paramagnetic, the simplification is valid for concentrations in tumor and blood and for tranfer coefficient: d{СОПУХОЛЬ(t)} / dt = ККр-Оп * СКРОВЬ (t) , from which it is obvious: ККр-Оп = (СОПУХОЛЬ(Т)) / (∫CКРОВЬ(t) dt), which was used in all calculations of the contrast transfer constant. Gadobutrol contrast is 0.1M/10 kg of body weight, TR = 5.5–6 ms, TE = 2.5 ms. Results. If, after the first cycle of NACHT, the ККр-Оп of the primary breast cancer is < 0.22 ml/min/g of tissue, the probability of subsequent relapse-free course = 0.78. Similarly, a decrease in the KCr-Op Ккр-Оп of the sentinel lymph node after the first cycle of NAHT < 0.08 ml/min/g of tissue with a probability of 0.75 predicts a relapse-free course. Conclusion. The proposed method for calculating the ККр-Оп transfer coefficient allows obtaining additional diagnostic and prognostic information in patients with local and locally advanced forms of breast cancer.

Enhancing the diagnostic capacity of [18F]PSMA-1007 PET/MRI in primary prostate cancer staging with artificial intelligence and semi-quantitative DCE: an exploratory study

BackgroundTo investigate the ability of artificial intelligence (AI)-based and semi-quantitative dynamic contrast enhanced (DCE) multiparametric MRI (mpMRI), performed within [18F]-PSMA-1007 PET/MRI, in differentiating benign from malignant prostate tissues in patients with primary prostate cancer (PC).ResultsA total of seven patients underwent whole-body [18F]-PSMA-1007 PET/MRI examinations including a pelvic mpMRI protocol with T2w, diffusion weighted imaging (DWI) and DCE image series. Conventional analysis included visual reading of PET/MRI images and Prostate Imaging Reporting & Data System (PI-RADS) scoring of the prostate. On the prostate level, we performed manual segmentations for time-intensity curve parameter formation and semi-quantitative analysis based on DCE segmentation data of PC-suspicious lesions. Moreover, we applied a recently introduced deep learning (DL) pipeline previously trained on 1010 independent MRI examinations with systematic biopsy-enhanced histopathological targeted biopsy lesion ground truth in order to perform AI-based lesion detection, prostate segmentation and derivation of a deep learning PI-RADS score. DICE coefficients between manual and automatic DL-acquired segmentations were compared. On patient-based analysis, PET/MRI revealed PC-suspicious lesions in the prostate gland in 6/7 patients (Gleason Score-GS ≥ 7b) that were histologically confirmed. Four of these patients also showed lymph node metastases, while two of them had bone metastases. One patient with GS 6 showed no PC-suspicious lesions. Based on DCE segmentations, a distinction between PC-suspicious and normal appearing tissue was feasible with the parameters fitted maximum contrast ratio (FMCR) and wash-in-slope. DICE coefficients (manual vs. deep learning) were comparable with literature values at a mean of 0.44. Further, the DL pipeline could identify the intraprostatic PC-suspicious lesions in all six patients with clinically significant PC.ConclusionFirstly, semi-quantitative DCE analysis based on manual segmentations of time-intensity curves was able to distinguish benign from malignant tissues. Moreover, DL analysis of the MRI data could detect clinically significant PC in all cases, demonstrating the feasibility of AI-supported approaches in increasing diagnostic certainty of PSMA-radioligand PET/MRI.

Performance of high-resolution diffusion-weighted magnetic resonance imaging for detecting clinically occult early breast cancers: a multi-reader study.

To compare mammography, breast ultrasound (US), high-resolution diffusion-weighted magnetic resonance imaging (DW-MRI), dynamic contrast-enhanced breast MRI (DCE-MRI), and their combinations for detecting clinically occult early breast cancers (EBCs), including ductal carcinoma in situ (DCIS). Three hundred and three consecutive women with screening imaging-detected early breast cancers (60 pure DCIS, 36 DCIS with microinvasion, and 207 invasive carcinoma less than 20mm) who underwent breast MRI at 3T including DW-MRI (b-values of 0, 800 and 1200s/mm2; in-plane resolution, 1.1 × 1.1 mm2 or 1.3 × 1.3 mm2; section thickness, 3mm) were retrospectively reviewed. Three radiologists independently reviewed each examination. Statistical analysis included Chi-square test, McNemar test for comparison of cancer detection rates, and Fleiss' Kappa for interreader agreement. Mixed-effect logistic regression analysis was employed to evaluate factors associated with cancer detection on DW-MRI. The overall cancer detection rates were 54.8% on mammography, 71.0% on breast US, 81.5% on DW-MRI, and 87.1% on DCE-MRI. On McNemar test, DW-MRI detected more cancers than mammography (adjusted p < 0.001), and its combination with mammography showed a similar cancer detection rate to DCE-MRI combined with mammography (adjusted p = 0.808). On multivariable analysis, histologic type, lesion size, ADC and CNR on DW-MRI were independent factors for cancer detection on DW-MRI. The interreader agreement for cancer detection was moderate to substantial (Fleiss' kappa: 0.52-0.65) across each modality. High-resolution DW-MRI plus mammography showed comparable cancer detection rate to DCE-MRI plus mammography for detecting clinically occult EBCs including DCIS.

Imaging blood-brain barrier dysfunction in drug-resistant epilepsy: A multi-center feasibility study.

Blood-brain barrier dysfunction (BBBD) has been linked to various neurological disorders, including epilepsy. This study aims to utilize dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to identify and compare brain regions with BBBD in patients with epilepsy (PWE) and healthy individuals. We scanned 50 drug-resistant epilepsy (DRE) patients and 58 control participants from four global specialized epilepsy centers using DCE-MRI. The presence and extent of BBBD were analyzed and compared between PWE and healthy controls. Both greater brain volume and higher number of brain regions with BBBD were significantly present in PWE compared to healthy controls (p < 10-7). No differences in total brain volume with BBBD were observed in patients diagnosed with either focal seizures or generalized epilepsy, despite variations in the affected regions. Overall brain volume with BBBD did not differ in PWE with MRI-visible lesions compared with non-lesional cases. BBBD was observed in brain regions suspected to be related to the onset of seizures in 82% of patients (n = 39) and was typically identified in, adjacent to, and/or in the same hemisphere as the suspected epileptogenic lesion (n = 10). These findings are consistent with pre-clinical studies that highlight the role of BBBD in the development of DRE and identify microvascular stabilization as a potential therapeutic strategy.

Image quality in three-dimensional (3D) contrast-enhanced dynamic magnetic resonance imaging of the abdomen using deep learning denoising technique: intraindividual comparison between T1-weighted sequences with compressed sensing and with a modified Fast 3D mode wheel.

To assess the image quality of a modified Fast three-dimensional (Fast 3D) mode wheel with sequential data filling (mFast 3D wheel) combined with a deep learning denoising technique (Advanced Intelligent Clear-IQ Engine [AiCE]) in contrast-enhanced (CE) 3D dynamic magnetic resonance (MR) imaging of the abdomen during a single breath hold (BH) by intra-individual comparison with compressed sensing (CS) with AiCE. Forty-two patients who underwent multiphasic CE dynamic MRI obtained with both mFast 3D wheel using AiCE and CS using AiCE in the same patient were retrospectively included. The conspicuity, artifacts, image quality, signal intensity ratio (SIR), signal-to-noise ratio (SNR), contrast ratio (CR), and contrast enhancement ratio (CER) of the organs were compared between these 2 sequences. Conspicuity, artifacts, and overall image quality were significantly better in the mFast 3D wheel using AiCE than in the CS with AiCE (all p < 0.001). The SNR of the liver in CS with AiCE was significantly better than that in the mFast 3D wheel using AiCE (p < 0.01). There were no significant differences in the SIR, CR, and CER between the two sequences. A mFast 3D wheel using AiCE as a deep learning denoising technique improved the conspicuity of abdominal organs and intrahepatic structures and the overall image quality with sufficient contrast enhancement effects, making it feasible for BH 3D CE dynamic MR imaging of the abdomen.

Dynamic Contrast-Enhanced and Diffusion-Weighted Imaging in Magnetic Resonance in the Assessment of Peritoneal Recurrence of Ovarian Cancer in Patients with or Without BRCA Mutation

Background: The aim of this study was to determine the differences in diffusion-weighted imaging (DWI) and dynamic contrast enhancement (DCE) parameters between patients with peritoneal high-grade serous ovarian cancer (HGSOC) recurrence with BRCA mutations (BRCAmut) or BRCA wild type (BRCAwt). Materials and Methods: We retrospectively analyzed the abdominal and pelvic magnetic resonance (MR) images of 43 patients suspected of having recurrent HGSOC, of whom 18 had BRCA1/2 gene mutations. Patients underwent MRI examination via a 1.5 T MRI scanner, and the analyzed parameters were as follows: apparent diffusion coefficient (ADC), time to peak (TTP) and perfusion maximum enhancement (Perf. Max. En.). Results: The mean ADC in patients with BRCAwt was lower than that in patients with BRCAmut: 788.7 (SD: 139.5) vs. 977.3 (SD: 103), p-value = 0.00002. The average TTP value for patients with BRCAwt was greater than that for patients with mutations: 256.3 (SD: 50) vs. 160.6 (SD: 35.5), p-value &lt; 0.01. The Perf. Max. En. value was lower in the BRCAwt group: 148.6 (SD: 12.3) vs. 233.6 (SD: 29.2), p-value &lt; 0.01. Conclusion: Our study revealed a statistically significant correlation between DWI and DCE parameters in examinations of peritoneal metastasis in patients with BRCA1/2 mutations. Adding DCE perfusion to the MRI protocol for ovarian cancer recurrence in patients with BRCAmut may be a valuable tool.

Can the second phase of contrast-enhanced MRA of the neck provide additional information in the acute stroke setting?

Double-concentration magnetic resonance imaging (MRI) contrast agents are frequently used in contrast-enhanced MR angiography (CE-MRA) of the head and neck. To avoid mistiming the peak concentration of intraluminal contrast (due to shorter duration of peak), a second acquisition is sometimes performed. To evaluate additional information from the second acquisition of CE-MRA and compare the collateral scoring to the hypoperfusion index obtained on MR perfusion, and to investigate presence of pseudo-occlusion using the second phase of CE-MRA. A retrospective study was conducted. CE-MRA of the brain/neck, dynamic susceptibility contrast (DSC) MR perfusion scan (in majority) and subsequent digital subtraction angiography (DSA) were evaluated in patients with previous acute internal carotid artery (ICA)/middle cerebral artery (MCA) occlusion. Evaluation of CE-MRA/MR perfusion and DSA was performed by three experienced neuroradiologists and one neurointerventionist, respectively. The site of ICA occlusion was seen to be distal to the site noted on early arterial phase (pseudo-occlusion of ICA) in 28.5% of patients. A significant negative correlation was seen between a higher HIR and collateral score. Evaluation of second phase CE-MRA can provide valuable information that may be otherwise lost if only the early arterial phase is evaluated.