Your browser doesn't support javascript.
loading
: 20 | 50 | 100
1 - 9 de 9
1.
J Breast Imaging ; 3(1): 44-56, 2021.
Article En | MEDLINE | ID: mdl-33543122

OBJECTIVE: The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance. METHODS: The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping. RESULTS: Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p <0.03), though not significant after multiplicity correction. The AUC for differentiating benign and malignant lesions increased after excluding non-evaluable lesions, from 0.61 (95% CI: 0.50-0.71) to 0.75 (95% CI: 0.65-0.84). CONCLUSION: Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility.

2.
Radiology ; 298(1): 60-70, 2021 01.
Article En | MEDLINE | ID: mdl-33201788

Background The Eastern Cooperative Oncology Group and American College of Radiology Imaging Network Cancer Research Group A6702 multicenter trial helped confirm the potential of diffusion-weighted MRI for improving differential diagnosis of suspicious breast abnormalities and reducing unnecessary biopsies. A prespecified secondary objective was to explore the relative value of different approaches for quantitative assessment of lesions at diffusion-weighted MRI. Purpose To determine whether alternate calculations of apparent diffusion coefficient (ADC) can help further improve diagnostic performance versus mean ADC values alone for analysis of suspicious breast lesions at MRI. Materials and Methods This prospective trial (ClinicalTrials.gov identifier: NCT02022579) enrolled consecutive women (from March 2014 to April 2015) with a Breast Imaging Reporting and Data System category of 3, 4, or 5 at breast MRI. All study participants underwent standardized diffusion-weighted MRI (b = 0, 100, 600, and 800 sec/mm2). Centralized ADC measures were performed, including manually drawn whole-lesion and hotspot regions of interest, histogram metrics, normalized ADC, and variable b-value combinations. Diagnostic performance was estimated by using the area under the receiver operating characteristic curve (AUC). Reduction in biopsy rate (maintaining 100% sensitivity) was estimated according to thresholds for each ADC metric. Results Among 107 enrolled women, 81 lesions with outcomes (28 malignant and 53 benign) in 67 women (median age, 49 years; interquartile range, 41-60 years) were analyzed. Among ADC metrics tested, none improved diagnostic performance versus standard mean ADC (AUC, 0.59-0.79 vs AUC, 0.75; P = .02-.84), and maximum ADC had worse performance (AUC, 0.52; P < .001). The 25th-percentile ADC metric provided the best performance (AUC, 0.79; 95% CI: 0.70, 0.88), and a threshold using median ADC provided the greatest reduction in biopsy rate of 23.9% (95% CI: 14.8, 32.9; 16 of 67 BI-RADS category 4 and 5 lesions). Nonzero minimum b value (100, 600, and 800 sec/mm2) did not improve the AUC (0.74; P = .28), and several combinations of two b values (0 and 600, 100 and 600, 0 and 800, and 100 and 800 sec/mm2; AUC, 0.73-0.76) provided results similar to those seen with calculations of four b values (AUC, 0.75; P = .17-.87). Conclusion Mean apparent diffusion coefficient calculated with a two-b-value acquisition is a simple and sufficient diffusion-weighted MRI metric to augment diagnostic performance of breast MRI compared with more complex approaches to apparent diffusion coefficient measurement. © RSNA, 2020 Online supplemental material is available for this article.


Breast Neoplasms/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Adult , Aged , Breast/diagnostic imaging , Diagnosis, Differential , Female , Humans , Middle Aged , Prospective Studies , Reproducibility of Results , Sensitivity and Specificity , Societies, Medical , Young Adult
3.
Clin Cancer Res ; 25(6): 1756-1765, 2019 03 15.
Article En | MEDLINE | ID: mdl-30647080

PURPOSE: Conventional breast MRI is highly sensitive for cancer detection but prompts some false positives. We performed a prospective, multicenter study to determine whether apparent diffusion coefficients (ADCs) from diffusion-weighted imaging (DWI) can decrease MRI false positives.Experimental Design: A total of 107 women with MRI-detected BI-RADS 3, 4, or 5 lesions were enrolled from March 2014 to April 2015. ADCs were measured both centrally and at participating sites. ROC analysis was employed to assess diagnostic performance of centrally measured ADCs and identify optimal ADC thresholds to reduce unnecessary biopsies. Lesion reference standard was based on either definitive biopsy result or at least 337 days of follow-up after the initial MRI procedure. RESULTS: Of 107 women enrolled, 67 patients (median age 49, range 24-75 years) with 81 lesions with confirmed reference standard (28 malignant, 53 benign) and evaluable DWI were analyzed. Sixty-seven of 81 lesions were BI-RADS 4 (n = 63) or 5 (n = 4) and recommended for biopsy. Malignancies exhibited lower mean in centrally measured ADCs (mm2/s) than benign lesions [1.21 × 10-3 vs.1.47 × 10-3; P < 0.0001; area under ROC curve = 0.75; 95% confidence interval (CI) 0.65-0.84]. In centralized analysis, application of an ADC threshold (1.53 × 10-3 mm2/s) lowered the biopsy rate by 20.9% (14/67; 95% CI, 11.2%-31.2%) without affecting sensitivity. Application of a more conservative threshold (1.68 × 10-3 mm2/s) to site-measured ADCs reduced the biopsy rate by 26.2% (16/61) but missed three cancers. CONCLUSIONS: DWI can reclassify a substantial fraction of suspicious breast MRI findings as benign and thereby decrease unnecessary biopsies. ADC thresholds identified in this trial should be validated in future phase III studies.


Breast Neoplasms/diagnosis , Breast/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Image Interpretation, Computer-Assisted , Adult , Aged , Biopsy/adverse effects , Breast/pathology , Breast Neoplasms/pathology , Diagnosis, Differential , False Positive Reactions , Female , Humans , Middle Aged , Prospective Studies , ROC Curve , Reference Values , Sensitivity and Specificity , Young Adult
4.
Arthritis Care Res (Hoboken) ; 71(11): 1430-1435, 2019 11.
Article En | MEDLINE | ID: mdl-30387916

OBJECTIVE: Chronic nonbacterial osteomyelitis (CNO) is an autoinflammatory bone disease. An inexpensive and rapid imaging tool, infrared thermal imaging, was evaluated for its utility to detect active bone lesions in extremities of children with CNO. METHODS: Children with suspected active CNO and healthy controls were enrolled. All subjects underwent infrared thermal imaging of the lower extremities. Patients in the CNO group also received a magnetic resonance imaging (MRI) examination. Hyperintensity within bone marrow on a fluid-sensitive T2-weighted MRI sequence was considered confirmatory for inflammation. Infrared thermal data were analyzed using custom software by dividing the leg below the knee into 3 equal segments longitudinally and adding the distal femur segment as an equal length above the knee. Median and 95th percentile temperatures were recorded for each leg segment. Temperature differences between inflamed and uninflamed segments in all subjects (both intersubject and intrasubject) were evaluated using a linear mixed-effects model. RESULTS: Thirty children in the suspected/known CNO group and 31 healthy children were enrolled. In the healthy control group, males had significantly higher temperature in their lower extremities than females (P < 0.05). There was no difference in temperature detected between inflamed leg segments of patients with CNO versus uninflamed leg segments of the healthy control group. However, within the CNO group, significantly higher temperatures were detected for inflamed versus uninflamed distal tibia/fibula segments (P < 0.01). CONCLUSION: Children with active CNO lesions in the distal tibia/fibula exhibited higher regional temperatures on average than healthy extremities. Larger studies are warranted to further evaluate the clinical utility of infrared thermal imaging for CNO detection.


Bone Diseases/diagnostic imaging , Infrared Rays , Magnetic Resonance Imaging/methods , Osteomyelitis/diagnostic imaging , Thermography/methods , Adolescent , Bone Diseases/etiology , Bone Diseases/pathology , Bones of Lower Extremity/diagnostic imaging , Bones of Lower Extremity/pathology , Case-Control Studies , Child , Child, Preschool , Female , Hot Temperature , Humans , Male , Osteomyelitis/complications , Osteomyelitis/pathology , Pilot Projects
5.
J Comput Assist Tomogr ; 43(1): 85-92, 2019.
Article En | MEDLINE | ID: mdl-30052617

OBJECTIVES: The aims of this study were to identify optimal quantitative breast magnetic resonance imaging background parenchymal enhancement (BPE) parameters associated with breast cancer risk and compare performance to qualitative assessments. METHODS: Using a matched case-control cohort of 46 high-risk women who underwent screening magnetic resonance imaging (23 who developed breast cancer matched to 23 who did not), fibroglandular tissue area, BPE area, and intensity metrics (mean, SD, quartiles, skewness, and kurtosis) were quantitatively measured at varying enhancement thresholds. Optimal thresholds for discriminating between cancer and control cohorts were identified for each metric and performance summarized using area under the receiver operating characteristic curve. RESULTS: Women who developed breast cancer exhibited greater BPE area (adjusted P = 0.004) and higher intensity statistics (adjusted P < 0.004, except skewness and kurtosis with P > 0.99) than did control subjects, with areas under the receiver operating characteristic curve ranging from 0.75 to 0.78 at optimized thresholds. CONCLUSIONS: Elevated quantitative BPE parameters, related to both area and intensity of enhancement, are associated with breast cancer development.


Breast Neoplasms/diagnostic imaging , Magnetic Resonance Imaging/methods , Adult , Aged , Breast/diagnostic imaging , Case-Control Studies , Cohort Studies , Evaluation Studies as Topic , Female , Humans , Middle Aged , Risk
6.
Clin Imaging ; 49: 37-43, 2018.
Article En | MEDLINE | ID: mdl-29120813

PURPOSE: To investigate the visibility of mammographically occult breast cancers on diffusion-weighted MRI (DWI) versus ultrasound. MATERIALS AND METHODS: Mammographically occult breast cancers (n=60) initially detected on contrast-enhanced MRI that underwent pre-biopsy targeted ultrasound were retrospectively evaluated for visibility on DWI and ultrasound. RESULTS: More cancers were visible on DWI than ultrasound (78% vs. 63%; p=0.049), with 32 (53%) visible on both and 7 (12%) not visible on either. Visibility differences were more significant in larger lesions (92% vs. 68%, p=0.006). CONCLUSION: DWI may detect more mammographically occult cancers than ultrasound, warranting further investigation as an alternative supplemental screening technique.


Breast Neoplasms/diagnosis , Breast/pathology , Magnetic Resonance Imaging/methods , Mammography , Ultrasonography/methods , Adult , Aged , Biopsy , Breast Neoplasms/pathology , Contrast Media , Diffusion Magnetic Resonance Imaging/methods , Female , Humans , Middle Aged , Neoplasms, Unknown Primary , Retrospective Studies , Young Adult
7.
Radiology ; 285(3): 788-797, 2017 12.
Article En | MEDLINE | ID: mdl-28914599

Purpose To investigate whether specific imaging features on breast magnetic resonance (MR) images are associated with ductal carcinoma in situ (DCIS) recurrence risk after definitive treatment. Materials and Methods Patients with DCIS who underwent preoperative dynamic contrast material-enhanced (DCE) MR imaging between 2004 and 2014 with ipsilateral recurrence more than 6 months after definitive surgical treatment were retrospectively identified. For each patient, a control subject with DCIS that did not recur was identified and matched on the basis of clinical, histopathologic, and treatment features known to affect recurrence risk. On DCE MR images, lesion characteristics (longest diameter, functional tumor volume [FTV], peak percentage enhancement [PE], peak signal enhancement ratio [SER], and washout fraction) and normal tissue features (background parenchymal enhancement [BPE] volume, mean BPE) were quantitatively measured. MR imaging features were compared between patients and control subjects by using the Wilcoxon signed-rank test, with adjustment for multiple comparisons. Results Of 415 subjects with DCIS who underwent preoperative MR imaging, 14 experienced recurrence and 11 had an identifiable matching control subject (final cohort, 11 patients and 11 control subjects). Median time to recurrence was 14 months, and median follow-up for control subjects was 102 months. When compared with matched control subjects, patients with DCIS recurrence exhibited significantly greater FTV (median, 9.3 cm3 vs 1.3 cm3, P = .01), lesion peak SER (median, 1.7 vs 1.2; P = .03), and mean BPE (median, 58.3% vs 41.1%; P = .02). Conclusion Quantitative lesion and normal breast tissue characteristics at preoperative MR imaging in women with newly diagnosed DCIS show promise for association with breast cancer recurrence after treatment. © RSNA, 2017.


Carcinoma, Intraductal, Noninfiltrating/diagnostic imaging , Carcinoma, Intraductal, Noninfiltrating/surgery , Magnetic Resonance Imaging/statistics & numerical data , Neoplasm Recurrence, Local/diagnostic imaging , Neoplasm Recurrence, Local/epidemiology , Adult , Aged , Aged, 80 and over , Breast Neoplasms , Carcinoma, Intraductal, Noninfiltrating/epidemiology , Female , Humans , Image Interpretation, Computer-Assisted/methods , Incidence , Middle Aged , Neoplasm Recurrence, Local/prevention & control , Preoperative Care , Prognosis , Reproducibility of Results , Retrospective Studies , Risk Factors , Sensitivity and Specificity , Washington/epidemiology
8.
J Magn Reson Imaging ; 45(2): 337-355, 2017 02.
Article En | MEDLINE | ID: mdl-27690173

Diffusion-weighted MRI (DWI) holds potential to improve the detection and biological characterization of breast cancer. DWI is increasingly being incorporated into breast MRI protocols to address some of the shortcomings of routine clinical breast MRI. Potential benefits include improved differentiation of benign and malignant breast lesions, assessment and prediction of therapeutic efficacy, and noncontrast detection of breast cancer. The breast presents a unique imaging environment with significant physiologic and inter-subject variations, as well as specific challenges to achieving reliable high quality diffusion-weighted MR images. Technical innovations are helping to overcome many of the image quality issues that have limited widespread use of DWI for breast imaging. Advanced modeling approaches to further characterize tissue perfusion, complexity, and glandular organization may expand knowledge and yield improved diagnostic tools. LEVEL OF EVIDENCE: 5 J. Magn. Reson. Imaging 2016 J. Magn. Reson. Imaging 2017;45:337-355.


Algorithms , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/pathology , Breast/diagnostic imaging , Breast/pathology , Diffusion Magnetic Resonance Imaging/methods , Image Interpretation, Computer-Assisted/methods , Diffusion Magnetic Resonance Imaging/trends , Evidence-Based Medicine , Female , Humans , Image Enhancement/methods , Reproducibility of Results , Sensitivity and Specificity , Signal Processing, Computer-Assisted
9.
J Comput Assist Tomogr ; 40(3): 428-35, 2016.
Article En | MEDLINE | ID: mdl-27192501

OBJECTIVE: To determine whether a semiautomated voxel selection technique improves interreader reproducibility for breast apparent diffusion coefficient (ADC) measurements. METHODS: Three readers retrospectively performed ADC measurements of 31 breast lesions (16 malignant, 15 benign) and contralateral normal tissue in 26 women both unassisted (manual method) and assisted by a semiautomated software tool that excludes voxels below a dynamically specified signal intensity threshold. Reproducibility between readers for each technique was assessed by Bland-Altman analysis and concordance correlation coefficients (CCCs). RESULTS: Differences between readers' measured ADCs of lesions were smaller with the semiautomated tool vs the manual method. Concordance correlation coefficients for each reader pair were greater with the semiautomated tool for lesions (mean CCC difference, 0.11; 95% confidence interval, 0.04-0.26). For normal tissue, reader agreement was lower than for lesions and did not differ based on software tools (mean CCC difference, 0.00; 95% confidence interval, -0.14 to 0.13). CONCLUSIONS: A semiautomated voxel selection tool can improve interreader reproducibility of breast lesion ADC measures.


Breast Neoplasms/diagnostic imaging , Diffusion Magnetic Resonance Imaging/standards , Image Enhancement/methods , Adult , Aged , Diagnosis, Differential , Female , Humans , Image Interpretation, Computer-Assisted , Imaging, Three-Dimensional , Machine Learning , Middle Aged , Observer Variation , Pattern Recognition, Automated , Reproducibility of Results , Sensitivity and Specificity , Tumor Burden
...