Project description:Quantitative correlations between T2 and ADC values were explored on cancerous breast lesions using spatiotemporally encoded (SPEN) MRI. To this end, T2 maps of patients were measured at more than one b-value, and ADC maps at several echo time values were recorded. SPEN delivered quality, artifact-free, TE-weighted DW images, from which T2-ADC correlations could be obtained despite the signal losses brought about by diffusion and relaxation. Data confirmed known aspects of breast cancer lesions, including their reduced ADC values vs. healthy tissue. Data also revealed an anticorrelation between the T2 and ADC values, when comparing regions with healthy and diseased tissues. This is contrary to expectations based on simple water restriction considerations. It is also contrary to what has been observed in a majority of porous materials and tissues. Differences between the healthy tissue of the lesion-affected breast and healthy tissue in the contralateral breast were also noticed. The potential significance of these trends is discussed, as is the potential of combining T2- and ADC-weightings to achieve an enhanced endogenous MRI contrast about the location of breast cancer lesions.
Project description:Recent advances in molecular subtyping of Pancreatic Ductal Adenocarcinoma (PDAC) support individualization of therapeutic strategies in this most aggressive disease. With the emergence of various novel therapeutic strategies and neoadjuvant approaches in this quickly deteriorating disease, robust approaches for fast evaluation of therapy response are urgently needed. To this aim, we designed a preclinical imaging-guided therapy trial where genetically engineered mice harboring endogenous aggressive PDAC were treated with the MEK targeting drug refametinib, which induces rapid and profound tumor regression in this model system. Multi-parametric non-invasive imaging was used for therapy response monitoring. A significant increase in the Diffusion-Weighted Magnetic Resonance Imaging derived Apparent Diffusion Coefficient (ADC) was noted already 24 hours after treatment onset. Histopathological analyses showed increased apoptosis and matrix remodeling at this time point. Our findings suggest the ADC parameter as an early predictor of therapy response in PDAC.
Project description:ObjectivesTo develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria.MethodsThis was a multicentric, retrospective analysis of 11 independently conducted institutional review board-approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant.ResultsA total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10-3 mm2/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p < .001). The following ADC-B categories were identified: ADC-B0-ADC cannot be assessed; ADC-B1-no contrast-enhancing lesion; ADC-B2-ADC ≥ 1.9 (cumulative malignancy rate < 0.1%); ADC-B3-ADC 1.5 to < 1.9 (0.1-1.7%); ADC-B4-ADC 1.0 to < 1.5 (10-24.5%); and ADC-B5-ADC < 1.0 (> 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94-0.97) for invasive versus non-invasive breast carcinomas was reached.ConclusionsThe breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI.Clinical relevance statementThe ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes.Key points• The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.
Project description:The objective of this study is to present a mathematical model which can describe the spatiotemporal progression of cerebral ischaemia and predict magnetic resonance observables including the apparent diffusion coefficient (ADC) of water and transverse relaxation time T2 This is motivated by the sensitivity of the ADC to the location of cerebral ischaemia and T2 to its time-course, and that it has thus far proven challenging to relate observations of changes in these MR parameters to stroke timing, which is of considerable importance in making treatment choices in clinics. Our mathematical model, called the cytotoxic oedema/dissociation (CED) model, is based on the transit of water from the extra- to the intra-cellular environment (cytotoxic oedema) and concomitant degradation of supramacromolecular and macromolecular structures (such as microtubules and the cytoskeleton). It explains experimental observations of ADC and T2, as well as identifying the rate of spread of effects of ischaemia through a tissue as a dominant system parameter. The model brings the direct extraction of the timing of ischaemic stroke from quantitative MRI closer to reality, as well as providing insight on ischaemia pathology by imaging in general. We anticipate that this may improve patient access to thrombolytic treatment as a future application.
Project description:ObjectiveTo establish optimised diffusion weightings ('b-values') for acquisition of whole-body diffusion-weighted MRI (WB-DWI) for estimation of the apparent diffusion coefficient (ADC) in patients with metastatic melanoma (MM). Existing recommendations for WB-DWI have not been optimised for the tumour properties in MM; therefore, evaluation of acquisition parameters is essential before embarking on larger studies.MethodsRetrospective clinical data and phantom experiments were used. Clinical data comprised 125 lesions from 14 examinations in 11 patients with multifocal MM, imaged before and/or after treatment with immunotherapy at a single institution. ADC estimates from these data were applied to a model to estimate the optimum b-value. A large non-diffusing phantom was used to assess eddy current-induced geometric distortion.ResultsConsidering all tumour sites from pre- and post-treatment examinations together, metastases exhibited a large range of mean ADC values, [0.67-1.49] × 10-3 mm2/s, and the optimum high b-value (bhigh) for ADC estimation was 1100 (10th-90th percentile: 740-1790) s/mm2. At higher b-values, geometric distortion increased, and longer echo times were required, leading to reduced signal.ConclusionsTheoretical optimisation gave an optimum bhigh of 1100 (10th-90th percentile: 740-1790) s/mm2 for ADC estimation in MM, with the large range of optimum b-values reflecting the wide range of ADC values in these tumours. Geometric distortion and minimum echo time increase at higher b-values and are not included in the theoretical optimisation; bhigh in the range 750-1100 s/mm2 should be adopted to maintain acceptable image quality but performance should be evaluated for a specific scanner.Key points• Theoretical optimisation gave an optimum high b-value of 1100 (10th-90th percentile: 740-1790) s/mm2 for ADC estimation in metastatic melanoma. • Considering geometric distortion and minimum echo time (TE), a b-value in the range 750-1100 s/mm2 is recommended. • Sites should evaluate the performance of specific scanners to assess the effect of geometric distortion and minimum TE.
Project description:ObjectivesPrevious non-simultaneous PET/MR studies have shown heterogeneous results about the correlation between standardized uptake values (SUVs) and apparent diffusion coefficients (ADCs). The aim of this study was to investigate correlations in patients with primary and recurrent tumors using a simultaneous PET/MRI system which could lead to a better understanding of tumor biology and might play a role in early response assessment.MethodsWe included 31 patients with histologically confirmed primary (n = 14) or recurrent cervical cancer (n = 17) who underwent simultaneous whole-body 18F-FDG-PET/MRI comprising DWI. Image analysis was performed by a radiologist and a nuclear physician who identified tumor margins and quantified ADC and SUV. Pearson correlations were calculated to investigate the association between ADC and SUV.Results92 lesions were detected. We found a significant inverse correlation between SUVmax and ADCmin (r = -0.532, p = 0.05) in primary tumors as well as in primary metastases (r = -0.362, p = 0.05) and between SUVmean and ADCmin (r = -0.403, p = 0.03). In recurrent local tumors we found correlations for SUVmax and ADCmin (r = -0.747, p = 0.002) and SUVmean and ADCmin (r = -0.773, p = 0.001). Associations for recurrent metastases were not significant (p>0.05).ConclusionsOur study demonstrates the feasibility of fast and reliable measurement of SUV and ADC with simultaneous PET/MRI. In patients with cervical cancer we found significant inverse correlations for SUV and ADC which could play a major role for further tumor characterization and therapy decisions.