Post-contrast T1 Research Articles

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-82. DEVELOPMENT AND VALIDATION OF AN MRI-BASED DEEP LEARNING MODEL TO DIFFERENTIATEIDH-WILDTYPE GLIOBLASTOMA AND TUMEFACTIVE MULTIPLE SCLEROSIS

Abstract Clinical management of IDH wildtype glioblastoma (GBM) and tumefactive multiple sclerosis (tMS) is drastically different. GBM requires maximal safe resection followed by chemoradiation, while tMS outcome is worsened by surgery and radiotherapy. Noninvasive methods are needed to help with accurate diagnosis of tumor and non-tumor etiologies. To develop an MRI-based classification model, tMS subjects diagnosed prior to January 1, 2020, were matched to tMS by age at diagnosis, sex, index MRI date, and 2D/3D acquisition. Inclusion criteria included one cm minimal lesion size and pre-operative post-contrast T1 and T2 images available for analysis. A 3D-DenseNet121 was used to develop a classification model using prespecified parameters: 650 epochs, batch size 16, learning rate 10-3, cross-entropy loss, and AdamW optimizer. The stopping rule was defined as three sequential differences in epoch cross-entropy loss <0.02. Models were developed using both T1gd and T2, as well as from only T1gd and only T2. Training included 220 subjects (110 GBM, 110 tMS). A 2-stage validation design was used, which included both retrospective and prospective cohorts. Stage 1 consisted of 272 retrospective GBM (diagnosed prior to January 1, 2020). Stage 2 consisted of 69 and 34 prospective (diagnosed after January 1, 2020) GBM and tMS, respectively. External validation on the 272 retrospective GBM demonstrated accuracy of 91%, 84%, and 78% for T1gd+T2, T1gd only, and T2 only, respectively. External validation on the 69 prospective GBM demonstrated an accuracy of 87%, 64%, and 67% for T1gd+T2, T1gd only, and T2 only, respectively. The 34 prospective tMS demonstrated accuracy of 76%, 76%, and 82% for T1gd+T2, T1gd only, and T2 only, respectively. This shows the feasibility of deep learning to aid in differential diagnosis of brain lesions. Future work entails the integration of germline variants into the classification model, including variants associated with the risk of glioma or MS.

INNV-26. FEASIBILITY EVALUATION OF TUMOR TREATING FIELDS (TTFIELDS) THERAPY FOR BRAINSTEM GLIOMAS

Abstract BACKGROUND Tumor Treating Fields (TTFields) therapy is a novel anti-mitotic therapy that is FDA-approved for use in patients with newly diagnosed and recurrent glioblastoma (GBM). However, TTFields therapy is currently only approved for supratentorial GBM, and the feasibility of TTFields therapy for treating infratentorial GBM remains unknown. TTFields values of average local minimum power density (LMiPD) >1.15 mW/cm3 and local minimum field intensity (LMiFI) >1.06 V/cm, were associated with improved OS and PFS based on a posthoc analysis of the EF-14 study. This is a dosimetric planning evaluation of the feasibility of TTFields therapy for brainstem gliomas. METHODS MRIs of patients with brainstem gliomas were used for this dosimetric evaluation, with planning conducted using MAXPOINT (Novocure, Switzerland). Gross tumor volume (GTV) for TTFields planning was defined as enhancing tumor on T1 post contrast MRI. Clinical target volume (CTV) was defined as GTV expanded by a 3 mm margin around sum total of resection cavity, necrotic core, and enhancing tumor. LMiPD and LMiFI to the GTV and CTV were evaluated. RESULTS A total of 5 patients with brainstem gliomas were included in this study. The median GTV volume was 8.2 cc (range: 3.8 – 13.5 cc), and median CTV volume was 18.6 cc (range: 9.1 – 23.4 cc). The median LMiPD for GTV and CTV were 1.9 (range: 1.1 – 2) and 1.9 (range: 1-2.1) mW/cm3, respectively. The median LMiFI for GTV and CTV were 1.3 (range: 1.1-1.6) and 1.2 (range: 1.1-1.6) V/cm, respectively. CONCLUSION LMiPD and LMiFI values for brainstem gliomas achieved levels that are consistent with those associated with improved OS and PFS in posthoc analyses in supratentorial GBM. This dosimetric planning study suggests feasibility and theoretical benefit of TTFields for brainstem gliomas. Further clinical evaluation is warranted to validate its efficacy.

Serial quantitative stress perfusion cardiac magnetic resonance in patients undergoing coronary artery bypass grafting; prediction of symptomatic benefit

Abstract Background Serial multiparametric cardiovascular magnetic resonance (CMR) in patients undergoing coronary artery bypass grafting (CABG) may provide mechanistic insight into dynamic and persistent abnormalities of the myocardium in patients with stable coronary artery disease (CAD). Objectives To assess for dynamic CMR markers of myocardial hypoperfusion and cardiac remodelling in patients undergoing CABG. Methods Patients with CAD awaiting elective CABG were recruited into an observational cohort study. Baseline evaluation included bloods, Seattle Angina Questionnaire-7, and adenosine stress perfusion CMR. Automated fully quantitative stress and rest myocardial blood flow was calculated, alongside assessment of the visual ischaemic burden. Native and post-contrast septal T1 indices were also measured. Repeat evaluation at 6-12 months post CABG was performed. Results Of 43 patients who underwent serial evaluation with CMR (mean age 62.1±9.3, median LVEF 68% [IQR: 62-73%]), there was improvement in the median visual ischaemic burden (18% [IQR: 11-21] vs 42% [IQR: 27-51], P<0.001), mean global stress myocardial blood flow (1.5±0.5 ml/min/g vs 1.3±0.5 ml/min/g, P=0.002) and median global myocardial perfusion reserve (2.4 [IQR: 1.7-2.8] vs 1.7 [IQR: 1.4-2.2], P=0.002) following CABG. Greater improvement in the SAQ-7 summary score was associated with a larger visual ischaemic burden at baseline (ρ=0.44, P=0.004) and a greater decrease in the visual ischaemic burden following CABG (ρ=-0.38, P=0.02). Quantitative MBF metrics did not associate with baseline or change in SAQ-7 summary score. Mean LV extracellular matrix volume decreased following CABG (16.6±3.6ml/m2 vs 18.2±4.6ml/m2, P=0.009). Conclusion Multiparametric CMR identifies dynamic changes in markers of myocardial perfusion and interstitial fibrosis in patients following CABG. Visual assessment of inducible myocardial hypoperfusion may identify patients who will derive the most symptomatic benefit from CABG. The results, however, suggest an important degree of residual inducible ischaemia and an unclear clinical role for CMR-derived MBF calculations.Serial CMR perfusion dataAssociation of SAQ with perfusion

Free-breathing 3D cardiac extracellular volume (ECV) mapping using a linear tangent space alignment (LTSA) model.

To develop a new method for free-breathing 3D extracellular volume (ECV) mapping of the whole heart at 3 T. A free-breathing 3D cardiac ECV mapping method was developed at 3 T. T1 mapping was performed before and after contrast agent injection using a free-breathing electrocardiogram-gated inversion recovery sequence with spoiled gradient echo readout. A linear tangent space alignment model-based method was used to reconstruct high-frame-rate dynamic images from (k,t)-space data sparsely sampled along a random stack-of-stars trajectory. Joint T1 and transmit B1 estimation were performed voxel-by-voxel for pre- and post-contrast T1 mapping. To account for the time-varying T1 after contrast agent injection, a linearly time-varying T1 model was introduced for post-contrast T1 mapping. ECV maps were generated by aligning pre- and post-contrast T1 maps through affine transformation. The feasibility of the proposed method was demonstrated using in vivo studies with six healthy volunteers at 3 T. We obtained 3D ECV maps at a spatial resolution of 1.9 × 1.9 × 4.5 mm3 and a FOV of 308 × 308 × 144 mm3, with a scan time of 10.1 ± 1.4 and 10.6 ± 1.6 min before and after contrast agent injection, respectively. The ECV maps and the pre- and post-contrast T1 maps obtained by the proposed method were in good agreement with the 2D MOLLI method both qualitatively and quantitatively. The proposed method allows for free-breathing 3D ECV mapping of the whole heart within a practically feasible imaging time. The estimated ECV values from the proposed method were comparable to those from the existing method.

There is poor agreement between the subjective and quantitative adjudication of aneurysm wall enhancement.

The determination of Aneurysm wall enhancement (AWE) by human readers on visual inspection alone is subjective and prone to error. A three-dimensional (3D) method for quantifying the aneurysm wall's signal intensity (SI) enables objective determination of AWE. Inter-reader agreement and agreement between subjective and objective determination of AWE were assessed in this study. Patients with saccular intracranial aneurysms (IAs) were imaged with high-resolution MRI. Subjective assessment: Two internal adjudicators visually determined AWE if the degree of enhancement was equal to or higher than the pituitary stalk. An experienced internal neuroradiologist resolved disagreements. This internal adjudication was compared with an external adjudication to assess inter-rater agreement among centers. Objective assessment: The distribution of SI across the aneurysm wall after normalizing the SI to the corpus callosum was determined with an in-house code. The normalized mean SI on post-contrast T1 MRI was defined as 3D-circumferential AWE (3D-CAWE). If the 3D-CAWE value was higher than one, an IA was defined as objectively "enhancing." Inter-rater agreement was analyzed with kappa coefficients. Inter-technique agreement between subjective and objective assessment was performed using kappa statistics. Univariate regressions were performed to identify which morphological characteristics influenced subjective adjudication of enhancement. A total of 113 IAs were analyzed. The agreement of the internal assessment was moderate (k = 0.63), 49.5% of IAs (56) were classified as "enhancing" and 50.5% (57) as "non-enhancing" after consensus. Inter-rater agreement between internal and external adjudication was weak (k = 0.52) for the presence of AWE. There was no agreement between the subjective assessment of AWE and objective 3D-CAWE (k = 0.16, p 0.02). Subjective assessment was less likely to reliably adjudicate enhancement when assessing multiple aneurysms (OR 0.4, 95% CI 0.16 -0.97, p 0.04) and IAs larger than > 7 mm (OR 0.22, 95% CI 0.09 -0.55, p 0.002) despite being objectively "non-enhancing". Subjective adjudication of AWE has poor inter-rater agreement, and no agreement with an objective 3D method of determining AWE. It is also less likely than objective quantification to identify enhancement in aneurysms larger than 7 mm or when multiple aneurysms are present. Objective 3D quantification, such as the technique used in this study, should therefore be considered when assessing AWE, especially in patients with multiple aneurysms and aneurysms larger than 7 mm in size. 3D, three-dimensional; 3D-CAWE, three-dimensional circumferential aneurysm wall enhancement; AWE, aneurysm wall enhancement; Gd, gadolinium; HR-MRI, high resolution MRI; HR 3D T1 VWI, high-resolution 3D T1 weighted black blood vessel wall imaging; IA, intracranial aneurysm; SI, signal intensity.

Dynamics of Daily Glioblastoma Evolution During Chemoradiation Therapy on the 0.35T Magnetic Resonance Imaging-Linear Accelerator

Glioblastoma changes during chemoradiation therapy are inferred from magnetic resonance imaging (MRI) before and after treatment but are rarely investigated due to logistics of frequent MRI. Using a combination MRI-linear accelerator (MRI-linac), we evaluated changes during daily chemoradiation therapy. Patients with glioblastoma were prospectively imaged daily during chemoradiation therapy on 0.35T MRI-linac and at 3 timepoints with and without contrast on standalone high-field MRI. Tumor or edema (lesion) and resection cavity dynamics throughout treatment were analyzed and compared with standalone T1 postcontrast (T1+C) and T2 volumes. Of 36 patients included in this analysis, 8 had cavity only, 12 had lesion only, and 16 had both cavity and lesion. Of these, 64% had lesion growth and 46% had cavity shrinkage during treatment on MRI-linac scans. The average MRI-linac migration distance was 1.3 cm (range, 0-4.1 cm) for lesion and 0.6 cm (range, 0.1-2.1 cm) for cavity. Standalone versus MRI-linac volumes correlated strongly with R2 values: 0.991 (T2 vs MRI-linac cavity), 0.972 (T1+C vs MRI-linac cavity), and 0.973 (T2 vs MRI-linac lesion). There was a moderate correlation between T1+C and MRI-linac lesion (R2 = 0.609), despite noncontrast MRI-linac inability to separate contrast enhancement from surrounding nonenhancing tumor and edema. From pretreatment to posttreatment in patients with all available scans (n = 35), T1+C and MRI-linac lesions changed together-shrank (n = 6), grew (n = 12), or unchanged (n = 8)-in 26 (74%) patients. Another 9 patients (26%) had growth on MRI-linac, although the T1+C component shrank. In no patient did T1+C lesion grow while MRI-linac lesion shrank. Anatomic changes are seen in patients with glioblastoma imaged daily on MRI-linac throughout the chemoradiation therapy course. As surgical resection cavities shrink, margins may be reduced to save normal brain. Patients with unresected or growing lesions may require margin expansions to cover changes. Limited volume glioblastoma boost trials could consider triggered gadolinium contrast administration for evaluation of adaptive radiation therapy when lesion growth is seen on noncontrast MRI-linac.

Systemic inflammatory markers and volume of enhancing tissue on post-contrast T1w MRI images in differentiating true tumor progression from pseudoprogression in high-grade glioma

BackgroundHigh-grade glioma (HGG) patients post-radiotherapy often face challenges distinguishing true tumor progression (TTP) from pseudoprogression (PsP). This study evaluates the effectiveness of systemic inflammatory markers and volume of enhancing tissue on post-contrast T1 weighted (T1WCE) MRI images for this differentiation within the first six months after treatment. Material and MethodsWe conducted a retrospective analysis on a cohort of HGG patients from 2015 to 2021, categorized per WHO 2016 and 2021 criteria. We analyzed treatment responses using modified RANO criteria and conducted volumetry on T1WCE and T2W/FLAIR images.Blood parameters assessed included neutrophil/lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI). We employed Chi-square, Fisher’s exact test, and Mann-Whitney U test for statistical analyses, using log-transformed predictors due to multicollinearity. A Cox regression analysis assessed the impact of PsP- and TTP-related factors on overall survival (OS). ResultsThe cohort consisted of 39 patients, where 16 exhibited PsP and 23 showed TTP. Univariate analysis revealed significantly higher NLR and SII in the TTP group [NLR: 4.1 vs 7.3, p = 0.002; SII 546.5 vs 890.5p = 0.009]. T1WCE volume distinctly differentiated PsP from TTP [2.2 vs 11.7, p < 0.001]. In multivariate regression, significant predictors included NLR and T1WCE volume in the “NLR Model,” and T1WCE volume and SII in the “SII Model.” The study also found a significantly lower OS rate in TTP patients compared to those with PsP [HR 3.97, CI 1.59 to 9.93, p = 0.003]. ConclusionElevated both, SII and NLR, and increased T1WCE volume were effective in differentiating TTP from PsP in HGG patients post-radiotherapy. These results suggest the potential utility of incorporating these markers into clinical practice, though further research is necessary to confirm these findings in larger patient cohorts.

Volumetric Changes in the Choroid Plexus Associated with Spontaneous Intracranial Hypotension in Patients with Spinal CSF Leak.

The choroid plexus contains specialized ependymal cells responsible for CSF production. Recent studies have demonstrated volumetric and perfusion changes in the choroid plexus with age and neurodegenerative disorders, however, volumetric changes in the choroid plexus in low pressure states is not known. The purpose of this study is to evaluate volumetric differences in choroid plexus size in patients with spontaneous intracranial hypotension (SIH) resultant from spinal CSF leaks compared with healthy controls. This was a retrospective, institutional review board-approved study. Patients with MRI evidence of SIH and a spinal CSF leak diagnosed on myelography and subsequently confirmed at surgery were included in this study. All patients included in this study including age-matched healthy controls had a brain MRI performed on a either a 1.5 or 3T scanner with acquisition of 3D T1 postcontrast (eg, BRAVO, MPRAGE, etc). In all patients, the trigonum ventriculi volume, in the atria of the lateral ventricles, was contoured by using Visage-7 segmentation tools on the volumetric postcontrast T1 sequence. A basic 2-tailed t test was used to compare choroid plexus volumes between the 2 groups. Thirty-four patients were included with 17 patients with SIH with spinal CSF leak and 17 healthy control patients who were age- and sex-matched. The mean age of patients was 45 years, standard deviation 14 years. The mean volume of the choroid plexus for patients with SIH with spinal CSF leak was 1.2 cm3 (standard deviation = 0.26) compared with 0.63 cm3 (standard deviation = 0.31) in the control group (P < .0001). Results of this study demonstrate a higher choroid plexus volume in patients with SIH with spinal CSF leak compared with age- and sex-matched healthy controls. This likely reflects compensatory mechanisms to counteract intracranial hypotension by increasing CSF production as well as increased vascularity of the choroid plexus through expansion of the intracranial blood pool.

Automatic pipeline for segmentation of LV myocardium on quantitative MR T1 maps using deep learning model and computation of radial T1 and ECV values.

Native T1 mapping is a non-invasive technique used for early detection of diffused myocardial abnormalities, and it provides baseline tissue characterization. Post-contrast T1 mapping enhances tissue differentiation, enables extracellular volume (ECV) calculation, and improves myocardial viability assessment. Accurate and precise segmenting of the left ventricular (LV) myocardium on T1 maps is crucial for assessing myocardial tissue characteristics and diagnosing cardiovascular diseases (CVD). This study presents a deep learning (DL)-based pipeline for automatically segmenting LV myocardium on T1 maps and automatic computation of radial T1 and ECV values. The study employs a multicentric dataset consisting of retrospective multiparametric MRI data of 332 subjects to develop and assess the performance of the proposed method. The study compared DL architectures U-Net and Deep Res U-Net for LV myocardium segmentation, which achieved a dice similarity coefficient of 0.84 ±0.43 and 0.85 ±0.03, respectively. The dice similarity coefficients computed for radial sub-segmentation of the LV myocardium on basal, mid-cavity, and apical slices were 0.77 ±0.21, 0.81 ±0.17, and 0.61 ±0.14, respectively. The t-test performed between ground truth vs. predicted values of native T1, post-contrast T1, and ECV showed no statistically significant difference (p> 0.05) for any of the radial sub-segments. The proposed DL method leverages the use of quantitative T1 maps for automatic LV myocardium segmentation and accurately computing radial T1 and ECV values, highlighting its potential for assisting radiologists in objective cardiac assessment and, hence, in CVD diagnostics.

Comparison of radiomics-based machine-learning classifiers for the pretreatment prediction of pathologic complete response to neoadjuvant therapy in breast cancer.

Machine learning classifiers are increasingly used to create predictive models for pathological complete response (pCR) in breast cancer after neoadjuvant therapy (NAT). Few studies have compared the effectiveness of different ML classifiers. This study evaluated radiomics models based on pre- and post-contrast first-phase T1 weighted images (T1WI) in predicting breast cancer pCR after NAT and compared the performance of ML classifiers. This retrospective study enrolled 281 patients undergoing NAT from the Duke-Breast-Cancer-MRI dataset. Radiomic features were extracted from pre- and post-contrast first-phase T1WI images. The Synthetic Minority Oversampling Technique (SMOTE) was applied, then the dataset was randomly divided into training and validation groups (7:3). The radiomics model was built using selected optimal features. Support vector machine (SVM), random forest (RF), decision tree (DT), k-nearest neighbor (KNN), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM) were classifiers. Receiver operating characteristic curves were used to assess predictive performance. LightGBM performed best in predicting pCR [area under the curve (AUC): 0.823, 95% confidence interval (CI) [0.743-0.902], accuracy 74.0%, sensitivity 85.0%, specificity 67.2%]. During subgroup analysis, RF was most effective in pCR prediction in luminal breast cancers (AUC: 0.914, 95% CI [0.847-0.981], accuracy 87.0%, sensitivity 85.2%, specificity 88.1%). In triple-negative breast cancers, LightGBM performed best (AUC: 0.836, 95% CI [0.708-0.965], accuracy 78.6%, sensitivity 68.2%, specificity 90.0%). The LightGBM-based radiomics model performed best in predicting pCR in patients with breast cancer. RF and LightGBM showed promising results for luminal and triple-negative breast cancers, respectively.

Predictors of lung cancer subtypes and lymph node status in non-small-cell lung cancer: intravoxel incoherent motion parameters and extracellular volume fraction

ObjectiveTo determine the performance of intravoxel incoherent motion (IVIM) parameters and the extracellular volume fraction (ECV) in distinguishing between different subtypes of lung cancer and predicting lymph node metastasis (LNM) status in patients with non-small-cell lung cancer (NSCLC).MethodsOne hundred sixteen patients with lung cancer were prospectively recruited. IVIM, native, and postcontrast T1 mapping examinations were performed, and the T1 values were measured to calculate the ECV. The differences in IVIM parameters and ECV were compared between NSCLC and small-cell lung cancer (SCLC), adenocarcinoma (Adeno-Ca) and squamous cell carcinoma (SCC), and NSCLC without and with LNM. The assessment of each parameter’s diagnostic performance was based on the area under the receiver operating characteristic curve (AUC).ResultsThe apparent diffusion coefficient (ADC), true diffusion coefficient (D), and ECV values in SCLC were considerably lower compared with NSCLC (all p < 0.001, AUC > 0.887). The D value in SCC was substantially lower compared with Adeno-Ca (p < 0.001, AUC = 0.735). The perfusion fraction (f) and ECV values in LNM patients were markedly higher compared with those without LNM patients (p < 0.01, < 0.001, AUC > 0.708).ConclusionIVIM parameters and ECV can serve as non-invasive biomarkers for assisting in the pathological classification and LNM status assessment of lung cancer patients.Critical relevance statementIVIM parameters and ECV demonstrated remarkable potential in distinguishing pulmonary carcinoma subtypes and predicting LNM status in NSCLC.Key PointsLung cancer is prevalent and differentiating subtype and invasiveness determine the treatment course.True diffusion coefficient and ECV showed promise for subtyping and determining lymph node status.These parameters could serve as non-invasive biomarkers to help determine personalized treatment strategies.Graphical

Retrospective Study of Multimodality Imaging Features of Chondroblastoma

PurposeTo evaluate the multimodality imaging features of chondroblastoma.Materials and MethodsRetrospective analysis of imaging features of 52 cases of histopathologically proven chondroblastoma from 2010 to 2022 was performed. Radiographs were evaluated for lesion site, location, morphology, margins, matrix mineralization, cortical breach, periosteal reaction, eccentricity, and subarticular extension. Appearance on T1, T2 weighted and post-contrast T1 was evaluated on MRI, with analysis of peritumoral edema and joint effusion.ResultsMean patient age was 18 years (10–57 years) with male preponderance (M = 39; F = 13). 75% (n = 39) cases involved an unfused skeleton and 25% (n = 13) affected a mature skeleton. Appendicular skeleton was involved in 88.5% (n = 46) cases and axial skeleton was involved in 11.5% (n = 6) cases with all cases involving epiphysis/epiphyseal equivalent. Radiographically, all cases were well-defined geographic osteolytic lesions with a narrow zone of transition, thin sclerotic rim and lobulated [56% (n = 29)] or smooth [44% (n = 23)] margins. Matrix calcification appreciable in 62% (n = 32) cases was ‘fluffy/smudgy’. Chondroblastoma appeared isointense (83%, n = 43) on T1 MRI with characteristically low signal and hyperintense foci within (67%, n = 35) on T2-weighted images and post-contrast enhancement [heterogeneous lobular (88%, n = 46) or septal pattern (12%, n = 6)] with all barring three lesions showing perilesional edema. None of the cases of chondroblastoma in our study developed metastasis till last follow-up (mean: 71 months).ConclusionChondroblastoma has distinctive imaging appearance and is often unlike majority other cartilaginous benign lesions due to characteristic low T2 signal on MRI and associated exuberant perilesional edema.

Abbreviated Breast MRI Protocols in the Screening of High-Risk Females

Abstract Background Standard MRI breast more often than not, have lengthy protocols that make them much more expensive and time-consuming. And in spite its great potential for early detection of breast cancer in high-risk females, its wide application remains difficult, therefore the use of abbreviated MRI protocols in breast cancer screening is introduced. Results This study was done on high-risk women with a lifetime risk of over 20%. The majority of the examinations were performed on women with previous history of breast cancer (63.3%), while 36.7% had moderate to high family history. An abbreviated protocol was created form the sequences obtained from the full diagnostic protocol, which consisted of a pre-contrast T1, post-contrast T1, subtraction and MIP images. On MRI examination using the conventional protocol, 36% of the women in our study were diagnosed with breast mass lesions, of which 20% were malignant masses. Benign findings, whether mass or non-mass lesions constitutes of a total of 50.1%, and about 26.7% were normal. All the malignant lesions were identified on the abbreviated protocol by the designated reader after review of the clinical history. So, the cancer detection rate in our study using the abbreviated MRI protocols revealed a Kappa agreement test of 1.000, i.e., perfect agreement with the conventional protocols for the participant females. Conclusion The use of abbreviated MRI breast is feasible without compromising the cancer detection rate compared to a full protocol. It also achieved a significant reduction in scanning time, interpretation time, and total cost of the study, proving its efficacy and making it a more accessible first line of screening high-risk females.

Left ventricular structural integrity on tetralogy of Fallot patients: approach using longitudinal relaxation time mapping.

Tetralogy of Fallot (TOF) is a congenital heart disease, and patients undergo surgical repair early in their lives. The evaluation of TOF patients is continuous through their adulthood. The use of cardiac magnetic resonance imaging (CMR) is vital for the evaluation of TOF patients. We aim to correlate advanced MRI sequences [parametric longitudinal relaxation time (T1), extracellular volume (ECV) mapping] with cardiac functionality to provide biomarkers for the evaluation of these patients. A complete CMR examination with the same imaging protocol was conducted in a total of 11 TOF patients and a control group of 25 healthy individuals. A Modified Look-Locker Inversion recovery (MOLLI) sequence was included to acquire the global T1 myocardial relaxation times of the left ventricular (LV) pre and post-contrast administration. Appropriate software (Circle cmr42) was used for the CMR analysis and the calculation of native, post-contrast T1, and ECV maps. A regression analysis was conducted for the correlation between global LV T1 values and right ventricular (RV) functional indices. Statistically significant results were obtained for RV cardiac index [RV_CI= -32.765 + 0.029 × T1 native; ], RV end diastolic volume [RV_EDV/BSA = -1023.872 + 0.902 × T1 native; ], and RV end systolic volume [RV_ESV/BSA = -536.704 + 0.472 × T1 native; ]. We further support the diagnostic importance of T1 mapping as a structural imaging tool in CMR. In addition to the well-known affected RV function in TOF patients, the LV structure is also impaired as there is a strong correlation between LV T1 mapping and RV function, evoking that the heart operates as an entity.

Myocardial Transit Time Mapping by CMR: A Novel Indicator of Microcirculatory Dysfunction in Cardiac Amyloidosis.

Cardiac amyloidosis (CA) is characterized by the deposition of amyloid fibrils within the myocardium, resulting in a restrictive physiology. Although microvascular dysfunction is a common feature, it is difficult to assess. This study aimed to explore myocardial transit time (MyoTT) by cardiovascular magnetic resonance (CMR) as a potential novel parameter of microcirculatory dysfunction in CA. This prospective study enrolled 20 CA patients and 20 control subjects. CMR acquisition included cine imaging, pre- and post-contrast T1 mapping, and MyoTT assessment, which was calculated from the time delay in contrast agent arrival between the aortic root and coronary sinus (CS). Compared to the control group, patients with CA exhibited significantly reduced left ventricular (LV) ejection fraction and myocardial strain, an increase in LV global peak wall thickness (LVGPWT), extracellular volume fraction (ECV), and prolonged MyoTT (14.4 ± 3.8s vs. 7.7 ± 1.5s, p < 0.001). Moreover, patients at Mayo stage III had a significantly longer MyoTT compared to those at stage I/II. MyoTT showed a positive correlation with the ECV, LVGPWT, and LV global longitudinal strain (LV-GLS) (p < 0.05). The area under the curve (AUC) for MyoTT was 0.962, demonstrating diagnostic performance comparable to that of the ECV (AUC 0.995) and LV-GLS (AUC 0.950) in identifying CA. MyoTT is significantly prolonged in patients with CA, correlating with fibrosis markers, remodeling, and dysfunction. As a novel parameter of coronary microvascular dysfunction (CMD), MyoTT has the potential to be an integral biomarker in multiparametric CMR assessment of CA.

IMG-21. HOW CAN WE BEST UTILISE HISTORICAL IMAGING DATASETS FOR RESEARCH IN PAEDIATRIC NEURO-ONCOLOGY? A REVIEW OF HISTORICAL PRE-OPERATIVE IMAGING PERFORMED FOR 92 PAEDIATRIC BRAIN TUMOUR PATIENTS WITH COMPARISON TO 2021 SIOPE GUIDELINES

Abstract BACKGROUND Utilisation of historical imaging is important for studying long-term outcomes in paediatric brain tumours often pooling data across multiple centres retrospectively over many years. Disparities in MRI sequence parameters, imaging planes, fields of view and resolution limit quantitative radiomic analysis and segmentation algorithms. We review historical imaging datasets, analysing the MRI scans performed assessing suitability for modern research techniques. METHODS Retrospective review of presenting MRI scans was performed in 92 paediatric brain tumour patients between 2006-2020. Whether imaging was performed internally at our paediatric neurosciences centre or externally at their referring hospitals was recorded. Image sequences, planes and slice thickness were compared with 2021 SIOPE guidelines for paediatric brain tumour imaging. T2 signal intensities for tumour, white and grey matter were compared for scans completed in different centres. Statistical testing was performed with T-Test and Paired T-Test. RESULTS 75% of patients had all SIOPE essential sequences and 60.9% were in the recommended planes. Only 1 patient had the desired slice thickness in all sequences recommended for 1.5T scanners. 38.5% had T1 and 27.8% had post-contrast T1 in the ≤1mm slice thickness recommended for 3T scanners. Comparison between 62 internal and 30 external scans revealed statistically significant differences in T2 signal intensities for regions of interest (ROI) within tumour, white and grey matter (p&amp;lt;0.01). Comparison of matched ROI for 12 patients imaged internally and externally demonstrated statistically significant differences in T2 signal intensities (p&amp;lt;0.05). Differences persisted despite normalisation of T2 signal intensity as ratios between tumour and the weighted mean of white and grey matter (p&amp;lt;0.01). CONCLUSIONS This study highlights the challenges of non-standardisation of imaging resolution and acquisition parameters in historical imaging. One approach to utilise these datasets is to use qualitative classifications where human experts label imaging features and encode data for future statistical or machine learning analysis.

IMG-27. ASSESSMENT OF VARIABILITY OF PEDIATRIC BRAIN TUMOR IMAGING PROTOCOLS ACROSS INSTITUTIONS: ARE WE FOLLOWING RECOMMENDATIONS?

Abstract BACKGROUND Evaluating pediatric brain tumors requires imaging children with tailored MRI protocols. Considerable variation in pediatric brain tumor imaging protocols exist across institutions, which can cause inaccuracies in staging. Although recently consensus guidelines for pediatric brain tumor imaging protocols have been established, adherence to these guidelines across institutions is unknown. Institutions may perceive guidelines as applicable for research purposes rather than routine clinical practice. We aim to explore variability in pediatric brain tumor imaging protocols across institutions and determine the factors influencing guideline divergence. METHODS AND METHODOLOGY Faculty at institutions routinely imaging pediatric patients with brain tumors were invited to share brain tumor MRI protocols and complete a structured survey. The survey included multiple choice and open-ended queries concerning practice type, the presence of an institutional imaging protocol for pediatric brain tumors and if the protocol was based on specific consensus recommendations. We assessed if protocols included the 7 minimum recommended MRI sequences by the Children’s Oncology Group (COG) guidelines, including slice thickness and gap. RESULTS Twenty emails were sent and responses were received from 12 institutions (the data collection is still ongoing). 2 institutions did not have dedicated protocols for pediatric brain tumors. On average, institutions had 5.7 out of the 7 minimum COG-recommended sequences. All 10 institutions included 3D T1 IR-GRE/TSE, DWI or DTI, and SWI sequences in their protocols. 9 (90%) included post-contrast 3D T1 IR-GRE/TSE, 7 (70%) included T2 TSE/FSE, 7 (70%) included either 3D T2 FLAIR or T2 FLAIR TSE/FSE, and 4 (40%) included T1/TSE/FSE. Across all sequences in all protocols, adherence to recommended imaging parameters was 87% for plane, 71% for slice thickness, and 85% for gap. CONCLUSION Significant variability in pediatric brain tumor imaging protocols exists across institutions Standardizing imaging protocols through collaboration is vital in ensuring uniformity in care.

MDB-94. RADIOMICS-BASED DECISION SUPPORT FOR PEDIATRIC MEDULLOBLASTOMA RISK STRATIFICATION ON MULTI-PARAMETRIC MRI

Abstract BACKGROUND Medulloblastoma (MB) is the most common pediatric brain malignancy. Accurate risk stratification is crucial for prescribing appropriate therapy. However, current risk stratification into standard or high-risk groups is limited in scope and does not accurately address the unique biological behavior of each specific tumor, with approximately 30% of children diagnosed with MB suffering from treatment failure. We developed a radiomic tool to more accurately risk stratify children with MB. METHODS We collected 1.5T/3T MRI (Siemens, Philips, or GE scanners) and clinical data from 80 patients with MB treated at Children’s Healthcare of Atlanta. Radiomic features that quantify textural heterogeneity including first and second order statistics, Haralick’s features from Gray Level Co-occurrence Matrices, and CoLIAge were extracted from tumor volumes segmented by a board-certified radiologist from multi-parametric MRI data including Apparent Diffusion Coefficient (ADC), T2, and post-contrast T1 sequences. Continuous survival models were built using the Cox proportional hazard method with 70% of the data for progression free survival (PFS) and overall survival (OS) using the 5 most predictive features obtained by univariate analysis after removing correlated features within the training data. RESULTS We developed three models with T1, T2, and ADC separately to evaluate predictive power of radiomic signatures. Three models for predicting MB OS delivered Harrel’s concordance indices (C-index) of 0.72 and 0.61 (T1); 0.70 and 0.65 (T2); and 0.80 and 0.76 (ADC) for training and test, respectively. C-indices for PFS were 0.70 and 0.69 (T1); 0.73 and 0.67 (T2); and 0.63 and 0.61 (ADC). CONCLUSIONS Our preliminary results show the feasibility and efficacy of our approach for predicting MB OS and PFS. Future studies will build an integrated model combining T1,T2, ADC, and other clinical information for predicting MB OS and PFS using a large multi-center validation cohort.

Cardiovascular Magnetic Resonance Radiomics to Identify Components of the Extracellular Matrix in Dilated Cardiomyopathy.

Current cardiovascular magnetic resonance sequences cannot discriminate between different myocardial extracellular space (ECSs), including collagen, noncollagen, and inflammation. We sought to investigate whether cardiovascular magnetic resonance radiomics analysis can distinguish between noncollagen and inflammation from collagen in dilated cardiomyopathy. We identified data from 132 patients with dilated cardiomyopathy scheduled for an invasive septal biopsy who underwent cardiovascular magnetic resonance at 3 T. Cardiovascular magnetic resonance imaging protocol included native and postcontrast T1 mapping and late gadolinium enhancement (LGE). Radiomic features were computed from the midseptal myocardium, near the biopsy region, on native T1, extracellular volume (ECV) map, and LGE images. Principal component analysis was used to reduce the number of radiomic features to 5 principal radiomics. Moreover, a correlation analysis was conducted to identify radiomic features exhibiting a strong correlation (r>0.9) with the 5 principal radiomics. Biopsy samples were used to quantify ECS, myocardial fibrosis, and inflammation. Four histopathological phenotypes were identified: low collagen (n=20), noncollagenous ECS expansion (n=49), mild to moderate collagenous ECS expansion (n=42), and severe collagenous ECS expansion (n=21). Noncollagenous expansion was associated with the highest risk of myocardial inflammation (65%). Although native T1 and ECV provided high diagnostic performance in differentiating severe fibrosis (C statistic, 0.90 and 0.90, respectively), their performance in differentiating between noncollagen and mild to moderate collagenous expansion decreased (C statistic: 0.59 and 0.55, respectively). Integration of ECV principal radiomics provided better discrimination and reclassification between noncollagen and mild to moderate collagen (C statistic, 0.79; net reclassification index, 0.83 [95% CI, 0.45-1.22]; P<0.001). There was a similar trend in the addition of native T1 principal radiomics (C statistic, 0.75; net reclassification index, 0.93 [95% CI, 0.56-1.29]; P<0.001) and LGE principal radiomics (C statistic, 0.74; net reclassification index, 0.59 [95% CI, 0.19-0.98]; P=0.004). Five radiomic features per sequence were identified with correlation analysis. They showed a similar improvement in performance for differentiating between noncollagen and mild to moderate collagen (native T1, ECV, LGE C statistic, 0.75, 0.77, and 0.71, respectively). These improvements remained significant when confined to a single radiomic feature (native T1, ECV, LGE C statistic, 0.71, 0.70, and 0.64, respectively). Radiomic features extracted from native T1, ECV, and LGE provide incremental information that improves our capability to discriminate noncollagenous expansion from mild to moderate collagen and could be useful for detecting subtle chronic inflammation in patients with dilated cardiomyopathy.