Diffusion-weighted imaging of the breast-a consensus and mission statement from the EUSOBI International Breast Diffusion-Weighted Imaging working group.
ABSTRACT: The European Society of Breast Radiology (EUSOBI) established an International Breast DWI working group. The working group consists of clinical breast MRI experts, MRI physicists, and representatives from large vendors of MRI equipment, invited based upon proven expertise in breast MRI and/or in particular breast DWI, representing 25 sites from 16 countries. The aims of the working group are (a) to promote the use of breast DWI into clinical practice by issuing consensus statements and initiate collaborative research where appropriate; (b) to define necessary standards and provide practical guidance for clinical application of breast DWI; (c) to develop a standardized and translatable multisite multivendor quality assurance protocol, especially for multisite research studies; (d) to find consensus on optimal methods for image processing/analysis, visualization, and interpretation; and (e) to work collaboratively with system vendors to improve breast DWI sequences. First consensus recommendations, presented in this paper, include acquisition parameters for standard breast DWI sequences including specifications of b values, fat saturation, spatial resolution, and repetition and echo times. To describe lesions in an objective way, levels of diffusion restriction/hindrance in the breast have been defined based on the published literature on breast DWI. The use of a small ROI placed on the darkest part of the lesion on the ADC map, avoiding necrotic, noisy or non-enhancing lesion voxels is currently recommended. The working group emphasizes the need for standardization and quality assurance before ADC thresholds are applied. The working group encourages further research in advanced diffusion techniques and tailored DWI strategies for specific indications. Key Points • The working group considers breast DWI an essential part of a multiparametric breast MRI protocol and encourages its use. • Basic requirements for routine clinical application of breast DWI are provided, including recommendations on b values, fat saturation, spatial resolution, and other sequence parameters. • Diffusion levels in breast lesions are defined based on meta-analysis data and methods to obtain a reliable ADC value are detailed.
Project description:BACKGROUND:The MRI Breast Imaging-Reporting and Data System (BI-RADS) lexicon recommends that a breast MRI protocol contain T2 -weighted and dynamic contrast-enhanced (DCE) MRI sequences. The addition of diffusion-weighted imaging (DWI) significantly improves diagnostic accuracy. This study aims to clarify which descriptors from DCE-MRI, DWI, and T2 -weighted imaging are most strongly associated with a breast cancer diagnosis. PURPOSE/HYPOTHESIS:To develop a multiparametric MRI (mpMRI) model for breast cancer diagnosis incorporating American College of Radiology (ACR) BI-RADS recommended descriptors for breast MRI with DCE, T2 -weighted imaging, and DWI with apparent diffusion coefficient (ADC) mapping. STUDY TYPE:Retrospective. SUBJECTS:In all, 188 patients (mean 51.6 years) with 210 breast tumors (136 malignant and 74 benign) who underwent mpMRI from December 2010 to September 2014. FIELD STRENGTH/SEQUENCE:IR inversion recovert DCE-MRI dynamic contrast-enhanced magnetic resonance imaging VIBE Volume-Interpolated-Breathhold-Examination FLASH turbo fast-low-angle-shot TWIST Time-resolved angiography with stochastic Trajectories. ASSESSMENT:Two radiologists in consensus and another radiologist independently evaluated the mpMRI data. Characteristics for mass (n?=?182) and nonmass (n?=?28) lesions were recorded on DCE and T2 -weighted imaging according to BI-RADS, as well as DWI descriptors. Two separate models were analyzed, using DCE-MRI BI-RADS descriptors, T2 -weighted imagines, and ADCmean as either a continuous or binary form using a previously published ADC cutoff value of ?1.25 × 10-3 mm2 /sec for differentiation between benign and malignant lesions. Histopathology was the standard of reference. STATISTICAL TESTS:?2 test, Fisher's exact test, Kruskal-Wallis test, Pearson correlation coefficient, multivariate logistic regression analysis, Hosmer-Lemeshow test of goodness-of-fit, receiver operating characteristics analysis. RESULTS:In Model 1, ADCmean (P?=?0.0031), mass margins with DCE (P?=?0.0016), and delayed enhancement with DCE (P?=?0.0016) were significantly and independently associated with breast cancer diagnosis; Model 2 identified ADCmean (P?=?0.0031), mass margins with DCE (P?=?0.0012), initial enhancement (P?=?0.0422), and delayed enhancement with DCE (P?=?0.0065) to be significantly independently associated with breast cancer diagnosis. T2 -weighted imaging variables were not included in the final models. DATA CONCLUSION: mpMRI with DCE-MRI and DWI with ADC mapping enables accurate breast cancer diagnosis. A model using quantitative and qualitative descriptors from DCE-MRI and DWI identifies breast cancer with a high diagnostic accuracy. T2 -weighted imaging does not significantly contribute to breast cancer diagnosis. LEVEL OF EVIDENCE:3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:864-874.
Project description:PURPOSE:To determine the test-retest repeatability of Apparent Diffusion Coefficient (ADC) measurements across institutions and MRI vendors, plus investigate the effect of post-processing methodology on measurement precision. METHODS:Thirty malignant lung lesions >2 cm in size (23 patients) were scanned on two occasions, using echo-planar-Diffusion-Weighted (DW)-MRI to derive whole-tumour ADC (b?=?100, 500 and 800smm-2). Scanning was performed at 4 institutions (3 MRI vendors). Whole-tumour volumes-of-interest were copied from first visit onto second visit images and from one post-processing platform to an open-source platform, to assess ADC repeatability and cross-platform reproducibility. RESULTS:Whole-tumour ADC values ranged from 0.66-1.94x10-3mm2s-1 (mean?=?1.14). Within-patient coefficient-of-variation (wCV) was 7.1% (95% CI 5.7-9.6%), limits-of-agreement (LoA) -18.0 to 21.9%. Lesions >3 cm had improved repeatability: wCV 3.9% (95% CI 2.9-5.9%); and LoA -10.2 to 11.4%. Variability for lesions <3 cm was 2.46 times higher. ADC reproducibility across different post-processing platforms was excellent: Pearson's R2?=?0.99; CoV 2.8% (95% CI 2.3-3.4%); and LoA -7.4 to 8.0%. CONCLUSION:A free-breathing DW-MRI protocol for imaging malignant lung tumours achieved satisfactory within-patient repeatability and was robust to changes in post-processing software, justifying its use in multi-centre trials. For response evaluation in individual patients, a change in ADC >21.9% will reflect treatment-related change. KEY POINTS:• In lung cancer, free-breathing DWI-MRI produces acceptable images with evaluable ADC measurement. • ADC repeatability coefficient-of-variation is 7.1% for lung tumours >2 cm. • ADC repeatability coefficient-of-variation is 3.9% for lung tumours >3 cm. • ADC measurement precision is unaffected by the post-processing software used. • In multicentre trials, 22% increase in ADC indicates positive treatment response.
Project description:OBJECTIVE:To determine the added value of qualitative analysis as an adjunct to quantitative analysis for the discrimination of benign and malignant lesions in patients with breast cancer using diffusion-weighted imaging (DWI) with readout-segmented echo-planar imaging (rs-EPI). METHODS:A total of 99 patients with 144 lesions were reviewed from our prospectively collected database. DWI data were obtained using rs-EPI acquired at 3.0 T. The diagnostic performances of DWI in the qualitative, quantitative, and combination analyses were compared with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Additionally, the effect of lesion size on the diagnostic performance of the DWI combination analysis was evaluated. RESULTS:The strongest indicators of malignancy on DWI were a heterogeneous pattern (P = 0.005) and an apparent diffusion coefficient (ADC) value <1.0 × 10-3 mm2/sec (P = 0.002). The area under the curve (AUC) values for the qualitative analysis, quantitative analysis, and combination analysis on DWI were 0.732 (95% CI, 0.651-0.803), 0.780 (95% CI, 0.703-0.846), and 0.826 (95% CI, 0.754-0.885), respectively (P<0.0001). The AUC for the combination analysis on DWI was superior to that for DCE-MRI alone (0.651, P = 0.003) but inferior to that for DCE-MRI plus the ADC value (0.883, P = 0.03). For the DWI combination analysis, the sensitivity was significantly lower in the size ?1 cm group than in the size >1 cm group (80% vs. 95.6%, P = 0.034). CONCLUSIONS:Qualitative analysis of tumor morphology was diagnostically applicable on DWI using rs-EPI. This qualitative analysis adds value to quantitative analyses for lesion characterization in patients with breast cancer.
Project description:Diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) MRI have high sensitivity and specificity for Creutzfeldt-Jakob disease (CJD). No studies, however, have demonstrated how MRI can distinguish CJD from nonprion causes of rapidly progressive dementia (npRPD). We sought to determine the diagnostic accuracy of MRI for CJD compared to a cohort of npRPD subjects.Two neuroradiologists blinded to diagnosis assessed DWI and FLAIR images in 90 patients with npRPD (n = 29) or prion disease (sporadic CJD [sCJD], n = 48, or genetic prion disease [familial CJD, n = 6, and Gerstmann-Sträussler-Scheinker, n = 7]). Thirty-one gray matter regions per hemisphere were assessed for abnormal hyperintensities. The likelihood of CJD was assessed using our previously published criteria.Gray matter hyperintensities (DWI > FLAIR) were found in all sCJD cases, with certain regions preferentially involved, but never only in limbic regions, and rarely in the precentral gyrus. In all sCJD cases with basal ganglia or thalamic DWI hyperintensities, there was associated restricted diffusion (apparent diffusion coefficient [ADC] map). This restricted diffusion, however, was not seen in any npRPD cases, in whom isolated limbic hyperintensities (FLAIR > DWI) were common. One reader's sensitivity and specificity for sCJD was 94% and 100%, respectively, the other's was 92% and 72%. After consensus review, the readers' combined MRI sensitivity and specificity for sCJD was 96% and 93%, respectively. Familial CJD had overlapping MRI features with sCJD.The pattern of FLAIR/DWI hyperintensity and restricted diffusion can differentiate sCJD from other RPDs with a high sensitivity and specificity. MRI with DWI and ADC should be included in sCJD diagnostic criteria. New sCJD MRI criteria are proposed.
Project description:BACKGROUND:Several methods for tumor delineation are used in literature on breast diffusion weighted imaging (DWI) to measure the apparent diffusion coefficient (ADC). However, in the process of reaching consensus on breast DWI scanning protocol, image analysis and interpretation, still no standardized optimal breast tumor tissue selection (BTTS) method exists. Therefore, the purpose of this study is to assess the impact of BTTS methods on ADC in the discrimination of benign from malignant breast lesions in DWI in terms of sensitivity, specificity and area under the curve (AUC). METHODS AND FINDINGS:In this systematic review and meta-analysis, adhering to the PRISMA statement, 61 studies, with 65 study subsets, in females with benign or malignant primary breast lesions (6291 lesions) were assessed. Studies on DWI, quantified by ADC, scanned on 1.5 and 3.0 Tesla and using b-values 0/50 and ? 800 s/mm2 were included. PubMed and EMBASE were searched for studies up to 23-10-2019 (n = 2897). Data were pooled based on four BTTS methods (by definition of measured region of interest, ROI): BTTS1: whole breast tumor tissue selection, BTTS2: subtracted whole breast tumor tissue selection, BTTS3: circular breast tumor tissue selection and BTTS4: lowest diffusion breast tumor tissue selection. BTTS methods 2 and 3 excluded necrotic, cystic and hemorrhagic areas. Pooled sensitivity, specificity and AUC of the BTTS methods were calculated. Heterogeneity was explored using the inconsistency index (I2) and considering covariables: field strength, lowest b-value, image of BTTS selection, pre-or post-contrast DWI, slice thickness and ADC threshold. Pooled sensitivity, specificity and AUC were: 0.82 (0.72-0.89), 0.79 (0.65-0.89), 0.88 (0.85-0.90) for BTTS1; 0.91 (0.89-0.93), 0.84 (0.80-0.87), 0.94 (0.91-0.96) for BTTS2; 0.89 (0.86-0.92), 0.90 (0.85-0.93), 0.95 (0.93-0.96) for BTTS3 and 0.90 (0.86-0.93), 0.84 (0.81-0.87), 0.86 (0.82-0.88) for BTTS4, respectively. Significant heterogeneity was found between studies (I2 = 95). CONCLUSIONS:None of the breast tissue selection (BTTS) methodologies outperformed in differentiating benign from malignant breast lesions. The high heterogeneity of ADC data acquisition demands further standardization, such as DWI acquisition parameters and tumor tissue selection to substantially increase the reliability of DWI of the breast.
Project description:Radiomics deals with the high throughput extraction of quantitative textural information from radiological images that not visually perceivable by radiologists. However, the biological correlation between radiomic features and different tissues of interest has not been established. To that end, we present the radiomic feature mapping framework to generate radiomic MRI texture image representations called the radiomic feature maps (RFM) and correlate the RFMs with quantitative texture values, breast tissue biology using quantitative MRI and classify benign from malignant tumors. We tested our radiomic feature mapping framework on a retrospective cohort of 124 patients (26 benign and 98 malignant) who underwent multiparametric breast MR imaging at 3?T. The MRI parameters used were T1-weighted imaging, T2-weighted imaging, dynamic contrast enhanced MRI (DCE-MRI) and diffusion weighted imaging (DWI). The RFMs were computed by convolving MRI images with statistical filters based on first order statistics and gray level co-occurrence matrix features. Malignant lesions demonstrated significantly higher entropy on both post contrast DCE-MRI (Benign-DCE entropy: 5.72?±?0.12, Malignant-DCE entropy: 6.29?±?0.06, p?=?0.0002) and apparent diffusion coefficient (ADC) maps as compared to benign lesions (Benign-ADC entropy: 5.65?±?0.15, Malignant ADC entropy: 6.20?±?0.07, p?=?0.002). There was no significant difference between glandular tissue entropy values in the two groups. Furthermore, the RFMs from DCE-MRI and DWI demonstrated significantly different RFM curves for benign and malignant lesions indicating their correlation to tumor vascular and cellular heterogeneity respectively. There were significant differences in the quantitative MRI metrics of ADC and perfusion. The multiview IsoSVM model classified benign and malignant breast tumors with sensitivity and specificity of 93 and 85%, respectively, with an AUC of 0.91.
Project description:OBJECTIVES:Standardization is an important milestone in the validation of DWI-based parameters as imaging biomarkers for renal disease. Here, we propose technical recommendations on three variants of renal DWI, monoexponential DWI, IVIM and DTI, as well as associated MRI biomarkers (ADC, D, D*, f, FA and MD) to aid ongoing international efforts on methodological harmonization. MATERIALS AND METHODS:Reported DWI biomarkers from 194 prior renal DWI studies were extracted and Pearson correlations between diffusion biomarkers and protocol parameters were computed. Based on the literature review, surveys were designed for the consensus building. Survey data were collected via Delphi consensus process on renal DWI preparation, acquisition, analysis, and reporting. Consensus was defined as ??75% agreement. RESULTS:Correlations were observed between reported diffusion biomarkers and protocol parameters. Out of 87 survey questions, 57 achieved consensus resolution, while many of the remaining questions were resolved by preference (65-74% agreement). Summary of the literature and survey data as well as recommendations for the preparation, acquisition, processing and reporting of renal DWI were provided. DISCUSSION:The consensus-based technical recommendations for renal DWI aim to facilitate inter-site harmonization and increase clinical impact of the technique on a larger scale by setting a framework for acquisition protocols for future renal DWI studies. We anticipate an iterative process with continuous updating of the recommendations according to progress in the field.
Project description:OBJECTIVE:To correlate the tumor-stromal ratio (TSR) of invasive breast cancer and MRI findings. METHODS:This study was approved by our institutional review board. 126 consecutive patients with surgically proven invasive breast cancer were included. All patients underwent MRI exams including short-tau inversion-recovery (STIR) T 2 weighted imaging, diffusion-weighted imaging (DWI) and post-contrast dynamic imaging. The mean signal intensity (SI) and apparent diffusion coefficient (ADC) value of each lesion were measured. To objectively evaluate the STIR images, the ratio of the SI of the lesion to the muscle (L/M ratio) was also measured. Percentages of MRI kinetic parameters obtained from dynamic images were also measured. The TSR was defined as the percentage of the stromal component, and categorized into high-stroma (> 50%) and low-stroma (< 50%) groups. Intergroup differences in the SI, L/M ratio, ADC value and percentages of kinetic parameters were examined. RESULTS:The SI and L/M ratio of the high-stroma group were significantly lower than those of the low-stromal group (208.64 vs 331.86 for SI, 5.69 vs 9.31 for L/M ratio) (p < 0.001). The high-stroma group had significantly lower percentages of a washout pattern (25% vs 34.7 %) (p = 0.012) and significantly higher percentages of a persistent pattern (36.92% vs 28.26 %) (p = 0.044). There were no significant correlations between the TSR and ADC value. CONCLUSION:STIR and dynamic sequence of breast MRI reflects the stromal component of invasive breast cancer. ADVANCES IN KNOWLEDGE:This is the first study to correlate TSR and MRI findings. STIR and post-contrast dynamic study correlated with the stromal component of breast cancer.
Project description:Solid papillary carcinoma (SPC) is a rare variant of breast papillary carcinoma with unique pathological morphology and biological behavior. There is only one case report on T1-MRI of SPC. In this study, we report our findings on this new category of papillary carcinoma to fill the gap in MRI characterization of SPC.This retrospective study included four pathology-confirmed in situ SPC patients. Conventional MRI, diffusion weighted imaging (DWI), and magnetic resonance spectroscopy (MRS) were performed with a 1.5 T whole-body MR scanner before surgical operation. The following characteristics of each lesion were recorded: signal intensity on T2WI/STIR and T1FSPGR, morphology, maximum lesion size, and time intensity curve (TIC) on dynamic contrast enhancement MRI (DCE-MRI), apparent diffusion coefficient (ADC) value from DWI, and Cho peak from MRS.Signal intensities of all lesions were heterogenous on T2WI/STIR and T1FSPGR. Mass enhancements were observed for all lesions with either oval or irregular shapes on DCE-MRI. The maximum lesion size ranged from 0.8 cm to 3.2 cm. All lesion margins were circumscribed, and internal enhancements were homogeneous or heterogeneous from DCE-MRI. TIC appeared with a rapid increase in initial contrast phases of all lesions. All lesions on DWI (b = 1000s/mm2) were slightly hyperintense with an ADC value range of 1.3 × 10-3 mm2/s to 1.9 × 10-3 mm2/s. Cho peak was absent at 3.2 ppm for all lesions.MRI characteristics of SPC include heterogeneous signal intensity within the lesion on T2WI/STIR and T1FSPGR, mass enhancement with circumscribed margins, either oval or irregular shapes, and a rapid initial enhancement of TIC on DCE-MRI. ADC values and the absence of Cho peak may provide valuable information to distinguish SPC from other invasive breast carcinomas.
Project description:Background:Imaging diagnosis of medulloblastoma recurrence relies heavily on identifying new contrast-enhancing lesions on surveillance imaging, with diffusion-weighted imaging (DWI) being used primarily for detection of complications. We propose that DWI is more sensitive in detecting distal and leptomeningeal recurrent medulloblastoma than T1-weighted postgadolinium imaging. Methods:We identified 53 pediatric patients with medulloblastoma, 21 of whom developed definitive disease recurrence within the brain. MRI at diagnosis of recurrence and 6 months prior was evaluated for new lesions with reduced diffusion on DWI, contrast enhancement, size, and recurrence location. Results:All recurrent medulloblastoma lesions demonstrated reduced diffusion. Apparent diffusion coefficient (ADC) measurements were statistically significantly lower (P = .00001) in recurrent lesions (mean=0.658, SD=0.072) as compared to contralateral normal region of interest (mean=0.923, SD=0.146). Sixteen patients (76.2%) with disease recurrence demonstrated contrast enhancement within the recurrent lesions. All 5 patients with nonenhancing recurrence demonstrated reduced diffusion, with a mean ADC of 0.695 ± 0.101 (normal=0.893 ± 0.100, P = .0027). While group 3 and group 4 molecular subtypes demonstrated distal recurrence more frequently, nonenhancing metastatic disease was found in all molecular subtypes. Conclusion:Recurrent medulloblastoma lesions do not uniformly demonstrate contrast enhancement on MRI, but all demonstrate reduced diffusion. Our findings support that DWI is more sensitive than contrast enhancement for detection of medulloblastoma recurrence, particularly in cases of leptomeningeal nonenhancing disease and distal nonenhancing focal disease. As such, recurrent medulloblastoma can present as a reduced diffusion lesion in a patient with normal postgadolinium contrast MRI.