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Background: This multicenter and retrospective study investigated the additive value of tumor morphologic features derived from the functional tumor volume (FTV) tumor mask at pre-treatment (T0) and the early treatment time point (T1) in the prediction of pathologic outcomes for breast cancer patients undergoing neoadjuvant chemotherapy., Methods: A total of 910 patients enrolled in the multicenter I-SPY 2 trial were included. FTV and tumor morphologic features were calculated from the dynamic contrast-enhanced (DCE) MRI. A poor response was defined as a residual cancer burden (RCB) class III (RCB-III) at surgical excision. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive performance. The analysis was performed in the full cohort and in individual sub-cohorts stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status., Results: In the full cohort, the AUCs for the use of the FTV ratio and clinicopathologic data were 0.64 ± 0.03 (mean ± SD [standard deviation]). With morphologic features, the AUC increased significantly to 0.76 ± 0.04 ( p < 0.001). The ratio of the surface area to volume ratio between T0 and T1 was found to be the most contributing feature. All top contributing features were from T1. An improvement was also observed in the HR+/HER2- and triple-negative sub-cohorts. The AUC increased significantly from 0.56 ± 0.05 to 0.70 ± 0.06 ( p < 0.001) and from 0.65 ± 0.06 to 0.73 ± 0.06 ( p < 0.001), respectively, when adding morphologic features., Conclusion: Tumor morphologic features can improve the prediction of RCB-III compared to using FTV only at the early treatment time point.

The apparent diffusion coefficient (ADC) provides a quantitative measure of water mobility that can be used to probe alterations in tissue microstructure due to disease or treatment. Establishment of the accepted level of variance in ADC measurements for each clinical application is critical for its successful implementation. The Diffusion-Weighted Imaging Biomarker Committee of the Quantitative Imaging Biomarkers Alliance (QIBA) has recently advanced the ADC Profile from the consensus to clinically feasible stage for the brain, liver, prostate, and breast. This profile distills multiple studies on ADC repeatability and describes detailed procedures to achieve stated performance claims on an observed ADC change within acceptable confidence limits. In addition to reviewing the current ADC Profile claims, this report has used recent literature to develop proposed updates for establishing metrology benchmarks for mean lesion ADC change that account for measurement variance. Specifically, changes in mean ADC exceeding 8% for brain lesions, 27% for liver lesions, 27% for prostate lesions, and 15% for breast lesions are claimed to represent true changes with 95% confidence. This report also discusses the development of the ADC Profile, highlighting its various stages, and describes the workflow essential to achieving a standardized implementation of advanced quantitative diffusion-weighted MRI in the clinic. The presented QIBA ADC Profile guidelines should enable successful clinical application of ADC as a quantitative imaging biomarker and ensure reproducible ADC measurements that can be used to confidently evaluate longitudinal changes and treatment response for individual patients., (© RSNA, 2024 See also the editorial by Haider in this issue.)

This study tested the hypothesis that a change in the apparent diffusion coefficient (ADC) measured in diffusion-weighted MRI (DWI) is an independent imaging marker, and ADC performs better than functional tumor volume (FTV) for assessing treatment response in patients with locally advanced breast cancer receiving neoadjuvant immunotherapy. A total of 249 patients were randomized to standard neoadjuvant chemotherapy with pembrolizumab (pembro) or without pembrolizumab (control). DCE-MRI and DWI, performed prior to and 3 weeks after the start of treatment, were analyzed. Percent changes of tumor ADC metrics (mean, 5th to 95th percentiles of ADC histogram) and FTV were evaluated for the prediction of pathologic complete response (pCR) using a logistic regression model. The area under the ROC curve (AUC) estimated for the percent change in mean ADC was higher in the pembro cohort (0.73, 95% confidence interval [CI]: 0.52 to 0.93) than in the control cohort (0.63, 95% CI: 0.43 to 0.83). In the control cohort, the percent change of the 95th percentile ADC achieved the highest AUC, 0.69 (95% CI: 0.52 to 0.85). In the pembro cohort, the percent change of the 25th percentile ADC achieved the highest AUC, 0.75 (95% CI: 0.55 to 0.95). AUCs estimated for percent change of FTV were 0.61 (95% CI: 0.39 to 0.83) and 0.66 (95% CI: 0.47 to 0.85) for the pembro and control cohorts, respectively. Tumor ADC may perform better than FTV to predict pCR at an early treatment time-point during neoadjuvant immunotherapy.

This study evaluated the inter-reader agreement of tumor apparent diffusion coefficient (ADC) measurements performed on breast diffusion-weighted imaging (DWI) for assessing treatment response in a multi-center clinical trial of neoadjuvant chemotherapy (NAC) for breast cancer. DWIs from 103 breast cancer patients (mean age: 46 ± 11 years) acquired at baseline and after 3 weeks of treatment were evaluated independently by two readers. Three types of tumor regions of interests (ROIs) were delineated: multiple-slice restricted, single-slice restricted and single-slice tumor ROIs. Compared to tumor ROIs, restricted ROIs were limited to low ADC areas of enhancing tumor only. We found excellent agreement (intraclass correlation coefficient [ICC] ranged from 0.94 to 0.98) for mean ADC. Higher ICCs were observed in multiple-slice restricted ROIs (range: 0.97 to 0.98) than in other two ROI types (both in the range of 0.94 to 0.98). Among the three ROI types, the highest area under the receiver operating characteristic curves (AUCs) were observed for mean ADC of multiple-slice restricted ROIs (0.65, 95% confidence interval [CI]: 0.52-0.79 and 0.67, 95% CI: 0.53-0.81 for Reader 1 and Reader 2, respectively). In conclusion, mean ADC values of multiple-slice restricted ROI showed excellent agreement and similar predictive performance for pathologic complete response between the two readers.

The study aims to test the long-term stability of gradient characteristics for model-based correction of diffusion weighting (DW) bias in an apparent diffusion coefficient (ADC) for multisite imaging trials. Single spin echo (SSE) DWI of a long-tube ice-water phantom was acquired quarterly on six MR scanners over two years for individual diffusion gradient channels, along with B0 mapping, as a function of right-left (RL) and superior-inferior (SI) offsets from the isocenter. Additional double spin-echo (DSE) DWI was performed on two systems. The offset dependences of derived ADC were fit to 4th-order polynomials. Chronic shim gradients were measured from spatial derivatives of B0 maps along the tube direction. Gradient nonlinearity (GNL) was modeled using vendor-provided gradient field descriptions. Deviations were quantified by root-mean-square differences (RMSD), normalized to reference ice-water ADC, between the model and reference (RMSDREF), measurement and model (RMSDEXP), and temporal measurement variations (RMSDTMP). Average RMSDREF was 4.9 ± 3.2 (%RL) and -14.8 ± 3.8 (%SI), and threefold larger than RMSDEXP. RMSDTMP was close to measurement errors (~3%). GNL-induced bias across gradient systems varied up to 20%, while deviation from the model accounted at most for 6.5%, and temporal variation for less than 3% of ADC reproducibility error. Higher SSE RMSDEXP = 7.5-11% was reduced to 2.5-4.8% by DSE, consistent with the eddy current origin. Measured chronic shim gradients below 0.1 mT/m had a minor contribution to ADC bias. The demonstrated long-term stability of spatial ADC profiles and consistency with system GNL models justifies retrospective and prospective DW bias correction based on system gradient design models. Residual errors due to eddy currents and shim gradients should be corrected independent of GNL.

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.

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/mm 2 ). 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/mm 2 ) 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/mm 2 ; 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.

Background: Multi-b-valued/multi-shell diffusion provides potentially valuable metrics in breast MRI but suffers from low signal-to-noise ratio and has potentially long scan times., Purpose: To investigate the effects of model-based denoising with no loss of spatial resolution on multi-shell breast diffusion MRI; to determine the effects of downsampling on multi-shell diffusion; and to quantify these effects in multi-b-valued (three directions per b-value) acquisitions., Study Type: Prospective ("fully-sampled" multi-shell) and retrospective longitudinal (multi-b)., Subjects: One normal subject (multi-shell) and 10 breast cancer subjects imaging at four timepoints (multi-b)., Field Strength/sequence: 3T multi-shell acquisition and 1.5T multi-b acquisition., Assessment: The "fully-sampled" multi-shell acquisition was retrospectively downsampled to determine the bias and error from downsampling. Mean, axial/parallel, radial diffusivity, and fractional anisotropy (FA) were analyzed. Denoising was applied retrospectively to the multi-b-valued breast cancer subject dataset and assessed subjectively for image noise level and tumor conspicuity., Statistical Tests: Parametric paired t-test (P < 0.05 considered statistically significant) on mean and coefficient of variation of each metric-the apparent diffusion coefficient (ADC) from all b-values, fast ADC, slow ADC, and perfusion fraction. Paired and two-sample t-tests for each metric comparing normal and tumor tissue., Results: In the multi-shell data, denoising effectively suppressed FA (-45% to -78%), with small biases in mean diffusivity (-5% in normal, +23% in tumor, and -4% in vascular compartments). In the multi-b data, denoising resulted in small biases to the ADC metrics in tumor and normal contralateral tissue (by -3% to +11%), but greatly reduced the coefficient of variation for every metric (by -1% to -24%). Denoising improved differentiation of tumor and normal tissue regions in most metrics and timepoints; subjectively, image noise level and tumor conspicuity were improved in the fast ADC maps., Data Conclusion: Model-based denoising effectively suppressed erroneously high FA and improved the accuracy of diffusivity metrics., Evidence Level: 3 TECHNICAL EFFICACY STAGE: 1., (© 2020 International Society for Magnetic Resonance in Medicine.)

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., (© Society of Breast Imaging 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.

Historically, breast magnetic resonance imaging (MRI) was not considered an effective modality in the evaluation of ductal carcinoma in situ (DCIS). Over the past decade this has changed, with studies demonstrating that MRI is the most sensitive imaging tool for detection of all grades of DCIS. It has been suggested that not only is breast MRI the most sensitive imaging tool for detection but it may also detect the most clinically relevant DCIS lesions. The role and outcomes of MRI in the preoperative setting for patients with DCIS remains controversial; however, several studies have shown benefit in the preoperative evaluation of extent of disease as well as predicting an underlying invasive component. The most common presentation of DCIS on MRI is nonmass enhancement (NME) in a linear or segmental distribution pattern. Maximizing breast MRI spatial resolution is therefore beneficial, given the frequent presentation of DCIS as NME on MRI. Emerging MRI techniques, such as diffusion-weighted imaging (DWI), have shown promising potential to discriminate DCIS from benign and invasive lesions. Future opportunities including advanced imaging visual techniques, radiomics/radiogenomics, and machine learning / artificial intelligence may also be applicable to the detection and treatment of DCIS. Level of Evidence: 3 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2020;52:697-709., (© 2019 International Society for Magnetic Resonance in Medicine.)

We investigated the impact of magnetic resonance imaging (MRI) protocol adherence on the ability of functional tumor volume (FTV), a quantitative measure of tumor burden measured from dynamic contrast-enhanced MRI, to predict response to neoadjuvant chemotherapy. We retrospectively reviewed dynamic contrast-enhanced breast MRIs for 990 patients enrolled in the multicenter I-SPY 2 TRIAL. During neoadjuvant chemotherapy, each patient had 4 MRI visits (pretreatment [T0], early-treatment [T1], inter-regimen [T2], and presurgery [T3]). Protocol adherence was rated for 7 image quality factors at T0-T2. Image quality factors confirmed by DICOM header (acquisition duration, early phase timing, field of view, and spatial resolution) were adherent if the scan parameters followed the standardized imaging protocol, and changes from T0 for a single patient's visits were limited to defined ranges. Other image quality factors (contralateral image quality, patient motion, and contrast administration error) were considered adherent if imaging issues were absent or minimal. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of FTV change (percent change of FTV from T0 to T1 and T2) in predicting pathological complete response. FTV changes with adherent image quality in all factors had higher estimated AUC than those with non-adherent image quality, although the differences did not reach statistical significance (T1, 0.71 vs. 0.66; T2, 0.72 vs. 0.68). These data highlight the importance of MRI protocol adherence to predefined scan parameters and the impact of data quality on the predictive performance of FTV in the breast cancer neoadjuvant setting., Competing Interests: Conflict of Interest: None reported., (© 2020 The Authors. Published by Grapho Publications, LLC.)

This retrospective study examined magnetic resonance imaging (MRI)-derived tumor sphericity (SPH) as a quantitative measure of breast tumor morphology, and investigated the association between SPH and reader-assessed morphological pattern (MP). In addition, association of SPH with pathologic complete response was evaluated in patients enrolled in an adaptively randomized clinical trial designed to rapidly identify new agents for breast cancer. All patients underwent MRI examinations at multiple time points during the treatment. SPH values from pretreatment (T0) and early-treatment (T1) were investigated in this study. MP on T0 dynamic contrast-enhanced MRI was ranked from 1 to 5 in 220 patients. Mean SPH values decreased with the increased order of MP. SPH was higher in patients with pathologic complete response than in patients without (difference at T0: 0.04, 95% confidence interval [CI]: 0.02-0.05, P < .001; difference at T1: 0.03, 95% CI: 0.02-0.04, P < .001). The area under the receiver operating characteristic curve was estimated as 0.61 (95% CI, 0.57-0.65) at T0 and 0.58 (95% CI, 0.55-0.62) at T1. When the analysis was performed by cancer subtype defined by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status, highest area under the receiver operating characteristic curve were observed in HR-/HER2+: 0.67 (95% CI, 0.54-0.80) at T0, and 0.63 (95% CI, 0.51-0.76) at T1. Tumor SPH showed promise to quantify MRI MPs and as a biomarker for predicting treatment outcome at pre- or early-treatment time points., Competing Interests: Conflict of Interest: None reported., (© 2020 The Authors. Published by Grapho Publications, LLC.)

The presented analysis of multisite, multiplatform clinical oncology trial data sought to enhance quantitative utility of the apparent diffusion coefficient (ADC) metric, derived from diffusion-weighted magnetic resonance imaging, by reducing technical interplatform variability owing to systematic gradient nonlinearity (GNL). This study tested the feasibility and effectiveness of a retrospective GNL correction (GNC) implementation for quantitative quality control phantom data, as well as in a representative subset of 60 subjects from the ACRIN 6698 breast cancer therapy response trial who were scanned on 6 different gradient systems. The GNL ADC correction based on a previously developed formalism was applied to trace-DWI using system-specific gradient-channel fields derived from vendor-provided spherical harmonic tables. For quantitative DWI phantom images acquired in typical breast imaging positions, the GNC improved interplatform accuracy from a median of 6% down to 0.5% and reproducibility of 11% down to 2.5%. Across studied trial subjects, GNC increased low ADC (<1 µm 2 /ms) tumor volume by 16% and histogram percentiles by 5%-8%, uniformly shifting percentile-dependent ADC thresholds by ∼0.06 µm 2 /ms. This feasibility study lays the grounds for retrospective GNC implementation in multiplatform clinical imaging trials to improve accuracy and reproducibility of ADC metrics used for breast cancer treatment response prediction., (© 2020 The Authors. Published by Grapho Publications, LLC.)

Background: The change in apparent diffusion coefficient (ADC) measured from diffusion-weighted imaging (DWI) has been shown to be predictive of pathologic complete response (pCR) for patients with locally invasive breast cancer undergoing neoadjuvant chemotherapy., Purpose: To investigate the additive value of tumor ADC in a multicenter clinical trial setting., Study Type: Retrospective analysis of multicenter prospective data., Population: In all, 415 patients who enrolled in the I-SPY 2 TRIAL from 2010 to 2014 were included., Field Strength/sequence: 1.5T or 3T MRI system using a fat-suppressed single-shot echo planar imaging sequence with b-values of 0 and 800 s/mm2 for DWI, followed by a T1-weighted sequence for dynamic contrast-enhanced MRI (DCE-MRI) performed at pre-NAC (T0), after 3 weeks of NAC (T1), mid-NAC (T2), and post-NAC (T3)., Assessment: Functional tumor volume and tumor ADC were measured at each MRI exam; pCR measured at surgery was assessed as the binary outcome. Breast cancer subtype was defined by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status., Statistical Tests: A logistic regression model was used to evaluate associations between MRI predictors with pCR. The cross-validated area under the curve (AUC) was calculated to assess the predictive performance of the model with and without ADC., Results: In all, 354 patients (128 HR+/HER2-, 60 HR+/HER2+, 34 HR-/HER2+, 132 HR-/HER2-) were included in the analysis. In the full cohort, adding ADC predictors increased the AUC from 0.76 to 0.78 at mid-NAC and from 0.76 to 0.81 at post-NAC. In HR/HER2 subtypes, the AUC increased from 0.52 to 0.65 at pre-NAC for HR+/HER2-, from 0.67 to 0.73 at mid-NAC and from 0.72 to 0.76 at post-NAC for HR+/HER2+, from 0.71 to 0.81 at post-NAC for triple negatives., Data Conclusion: The addition of ADC to standard functional tumor volume MRI showed improvement in the prediction of treatment response in HR+ and triple-negative breast cancer., Level of Evidence: 2 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2019;50:1742-1753., (© 2019 International Society for Magnetic Resonance in Medicine.)

Level of Evidence: 5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019., (© 2019 International Society for Magnetic Resonance in Medicine.)

Purpose: To determine the in vitro accuracy, test-retest repeatability, and interplatform reproducibility of T 1 quantification protocols used for dynamic contrast-enhanced MRI at 1.5 and 3 T., Methods: A T 1 phantom with 14 samples was imaged at eight centers with a common inversion-recovery spin-echo (IR-SE) protocol and a variable flip angle (VFA) protocol using seven flip angles, as well as site-specific protocols (VFA with different flip angles, variable repetition time, proton density, and Look-Locker inversion recovery). Factors influencing the accuracy (deviation from reference NMR T 1 measurements) and repeatability were assessed using general linear mixed models. Interplatform reproducibility was assessed using coefficients of variation., Results: For the common IR-SE protocol, accuracy (median error across platforms = 1.4-5.5%) was influenced predominantly by T 1 sample (P < 10 -6 ), whereas test-retest repeatability (median error = 0.2-8.3%) was influenced by the scanner (P < 10 -6 ). For the common VFA protocol, accuracy (median error = 5.7-32.2%) was influenced by field strength (P = 0.006), whereas repeatability (median error = 0.7-25.8%) was influenced by the scanner (P < 0.0001). Interplatform reproducibility with the common VFA was lower at 3 T than 1.5 T (P = 0.004), and lower than that of the common IR-SE protocol (coefficient of variation 1.5T: VFA/IR-SE = 11.13%/8.21%, P = 0.028; 3 T: VFA/IR-SE = 22.87%/5.46%, P = 0.001). Among the site-specific protocols, Look-Locker inversion recovery and VFA (2-3 flip angles) protocols showed the best accuracy and repeatability (errors < 15%)., Conclusions: The VFA protocols with 2 to 3 flip angles optimized for different applications achieved acceptable balance of extensive spatial coverage, accuracy, and repeatability in T 1 quantification (errors < 15%). Further optimization in terms of flip-angle choice for each tissue application, and the use of B 1 correction, are needed to improve the robustness of VFA protocols for T 1 mapping. Magn Reson Med 79:2564-2575, 2018. © 2017 International Society for Magnetic Resonance in Medicine., (© 2017 International Society for Magnetic Resonance in Medicine.)

Previous research has shown that system-dependent gradient nonlinearity (GNL) introduces a significant spatial bias (nonuniformity) in apparent diffusion coefficient (ADC) maps. Here, the feasibility of centralized retrospective system-specific correction of GNL bias for quantitative diffusion-weighted imaging (DWI) in multisite clinical trials is demonstrated across diverse scanners independent of the scanned object. Using corrector maps generated from system characterization by ice-water phantom measurement completed in the previous project phase, GNL bias correction was performed for test ADC measurements from an independent DWI phantom (room temperature agar) at two offset locations in the bore. The precomputed three-dimensional GNL correctors were retrospectively applied to test DWI scans by the central analysis site. The correction was blinded to reference DWI of the agar phantom at magnet isocenter where the GNL bias is negligible. The performance was evaluated from changes in ADC region of interest histogram statistics before and after correction with respect to the unbiased reference ADC values provided by sites. Both absolute error and nonuniformity of the ADC map induced by GNL (median, 12%; range, -35% to +10%) were substantially reduced by correction (7-fold in median and 3-fold in range). The residual ADC nonuniformity errors were attributed to measurement noise and other non-GNL sources. Correction of systematic GNL bias resulted in a 2-fold decrease in technical variability across scanners (down to site temperature range). The described validation of GNL bias correction marks progress toward implementation of this technology in multicenter trials that utilize quantitative DWI.

In this study, the prognostic significance of tumor metrics derived from diffusion tensor imaging (DTI) was evaluated in patients with locally advanced breast cancer undergoing neoadjuvant therapy. DTI and contrast-enhanced magnetic resonance imaging were acquired at 1.5 T in 34 patients before treatment and after 3 cycles of taxane-based therapy (early treatment). Tumor fractional anisotropy (FA), principal eigenvalues (λ1, λ2, and λ3), and apparent diffusion coefficient (ADC) were estimated for tumor regions of interest drawn on DTI data. The association between DTI metrics and final tumor volume change was evaluated with Spearman rank correlation. DTI metrics were investigated as predictors of pathological complete response (pCR) by calculating the area under the receiver operating characteristic curve (AUC). Early changes in tumor FA and ADC significantly correlated with final tumor volume change post therapy (ρ = -0.38, P = .03 and ρ = -0.71, P < .001, respectively). Pretreatment tumor ADC was significantly lower in the pCR than in the non-pCR group ( P = .04). At early treatment, patients with pCR had significantly higher percent changes of tumor λ1, λ2, λ3, and ADC than those without pCR. The AUCs for early percent changes in tumor FA and ADC were 0.60 and 0.83, respectively. The early percent changes in tumor eigenvalues and ADC were the strongest DTI-derived predictors of pCR. Although early percent change in tumor FA had a weak association with pCR, the significant correlation with final tumor volume change suggests that this metric changes with therapy and may merit further evaluation.

Purpose: To assess the ability of a recent, anatomically designed breast phantom incorporating T1 and diffusion elements to serve as a quality control device for quantitative comparison of apparent diffusion coefficient (ADC) measurements calculated from diffusion-weighted MRI (DWI) within and across MRI systems., Materials and Methods: A bilateral breast phantom incorporating multiple T1 and diffusion tissue mimics and a geometric distortion array was imaged with DWI on 1.5 Tesla (T) and 3.0T scanners from two different manufacturers, using three different breast coils (three configurations total). Multiple measurements were acquired to assess the bias and variability of different diffusion weighted single-shot echo-planar imaging sequences on the scanner-coil systems., Results: The repeatability of ADC measurements was mixed: the standard deviation relative to baseline across scanner-coil-sequences ranged from low variability (0.47, 95% confidence interval [CI]: 0.22-1.00) to high variability (1.69, 95% CI: 0.17-17.26), depending on material, with the lowest and highest variability from the same scanner-coil-sequence. Assessment of image distortion showed that right/left measurements of the geometric distortion array were 1 to 16% larger on the left coil side compared with the right coil side independent of scanner-coil systems, diffusion weighting, and phase-encoding direction., Conclusion: This breast phantom can be used to measure scanner-coil-sequence bias and variability for DWI. When establishing a multisystem study, this breast phantom may be used to minimize protocol differences (e.g., due to available sequences or shimming technique), to correct for bias that cannot be minimized, and to weigh results from each system depending on respective variability. J. Magn. Reson. Imaging 2016. J. MAGN. RESON. IMAGING 2016;44:846-855., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: We present a breast phantom designed to enable quantitative assessment of measurements of T1 relaxation time, apparent diffusion coefficient (ADC), and other attributes of breast tissue, with long-term support from a national metrology institute., Materials and Methods: A breast phantom was created with two independent, interchangeable units for diffusion and T1 /T2 relaxation, each with flexible outer shells. The T1 unit was filled with corn syrup solution and grapeseed oil to mimic the relaxation behavior of fibroglandular and fatty tissues, respectively. The diffusion unit contains plastic tubes filled with aqueous solutions of polyvinylpyrrolidone (PVP) to modulate the ADC. The phantom was imaged at 1.5T and 3.0T using magnetic resonance imaging (MRI) scanners and common breast coils from multiple manufacturers to assess T1 and T2 relaxation time and ADC values., Results: The fibroglandular mimic exhibited target T1 values on 1.5T and 3.0T clinical systems (25-75 percentile range: 1289 to 1400 msec and 1533 to 1845 msec, respectively) across all bore temperatures. PVP solutions mimicked the range of ADC values from malignant tumors to normal breast tissue (40% PVP median: 633 × 10(-6) mm(2) /s to 0% PVP median: 2231 × 10(-6) mm(2) /s) at temperatures of 17-24°C. The interchangeable phantom units allowed both the diffusion and T1 /T2 units to be tested on the left and right sides of the coil to assess any variation., Conclusion: This phantom enables T1 and ADC measurements, fits in a variety of clinical breast coils, and can serve as a quality control tool to facilitate the standardization of quantitative measurements for breast MRI. J. Magn. Reson. Imaging 2016;44:610-619., (© 2016 International Society for Magnetic Resonance in Medicine.)

The purpose of this study is to evaluate the predictive performance of magnetic resonance imaging (MRI) markers in breast cancer patients by subtype. Sixty-four patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy were enrolled in this study. Each patient received a dynamic contrast-enhanced (DCE-MRI) at baseline, after 1 cycle of chemotherapy and before surgery. Functional tumor volume (FTV), the imaging marker measured by DCE-MRI, was computed at various thresholds of percent enhancement (PEt) and signal-enhancement ratio (SERt). Final FTV before surgery and percent changes of FTVs at the early and final treatment time points were used to predict patients' recurrence-free survival. The full cohort and each subtype defined by the status of hormone receptor and human epidermal growth factor receptor 2 (HR+/HER2-, HER2+, triple negative) were analyzed. Predictions were evaluated using the Cox proportional hazard model when PEt changed from 30% to 200% in steps of 10% and SERt changed from 0 to 2 in steps of 0.2. Predictions with high hazard ratios and low p-values were considered as strong. Different profiles of FTV as predictors for recurrence-free survival were observed in each breast cancer subtype and strong associations with survival were observed at different PEt/SERt combinations that resulted in different FTVs. Findings from this retrospective study suggest that the predictive performance of imaging markers based on FTV may be improved with enhancement thresholds being optimized separately for clinically-relevant subtypes defined by HR and HER2 receptor expression.

Purpose: To evaluate a gradient nonlinearity correction (GNC) program for quantitative apparent diffusion coefficient (ADC) measurements on phantom and human subject diffusion-weighted (DW) magnetic resonance imaging (MRI) scans in a multicenter breast cancer treatment response study, Materials and Methods: A GNC program using fifth-order spherical harmonics for gradient modeling was applied retrospectively to qualification phantom and human subject scans. Ice-water phantoms of known diffusion coefficient were scanned at five different study centers with different scanners and receiver coils. Human in vivo data consisted of baseline and early-treatment exams on 54 patients from four sites. ADC maps were generated with and without GNC. Regions of interest were defined to quantify absolute errors and changes with GNC over breast imaging positions., Results: Phantom ADC errors varied with region of interest (ROI) position and scanner configuration; the mean error by configuration ranged from 1.4% to 19.9%. GNC significantly reduced the overall mean error for all sites from 9.9% to 0.6% (P = 0.016). Spatial dependence of GNC was highest in the right-left (RL) and anterior-posterior (AP) directions. Human subject mean tumor ADC was reduced 0.2 to 12% by GNC at different sites. By regression, every 1-cm change in tumor ROI position between baseline and follow-up visits resulted in an estimated change of 2.4% in the ADC early-treatment response measurement., Conclusion: GNC is effective for removing large, system-dependent errors in quantitative breast DWI. GNC may be important in ensuring reproducibility in multicenter studies and in reducing errors in longitudinal treatment response measures arising from spatial variations in tumor position between visits., (© 2015 Wiley Periodicals, Inc.)

Purpose: To evaluate diffusion changes in the breast tumor-stromal boundary and adjacent tissue in response to neoadjuvant chemotherapy using high resolution diffusion-weighted imaging (HR-DWI)., Materials and Methods: Seven patients with invasive breast cancer were imaged with HR-DWI before and early during treatment. The mean apparent diffusion coefficient (ADC) was plotted in 1-mm increments around the tumor boundary. Early change in ADC was measured for tumor, tumor boundary, and stromal regions, and the relationship to treatment response was evaluated using Spearman's correlation., Results: Statistically significant correlations between treatment response and early changes in ADC were found for: (i) whole tumor (ρ = 0.93, 95% confidence interval [CI] = (0.58, 0.99), P = 0.003); (ii) tumor rim (ρ = 0.75, 95% CI = (-0.007, 0.96), P = 0.05); and (iii) boundary transition region (ρ = 0.86, 95% CI = (0.29, 0.98), P = 0.01). Early change in ADC of distal stroma had a marginally statistically significant positive correlation to treatment response (ρ = 0.71, 95% CI = (-0.084, 0.95), P = 0.07)., Conclusion: Proximity-dependent evaluation of HR-DWI data in the breast tumor-stromal boundary and adjacent tissue may provide information about response to therapy., (Copyright © 2013 Wiley Periodicals, Inc.)

Purpose: To evaluate the variability and repeatability of repeated magnetic resonance imaging (MRI) measurements in normal breast tissues between and within subjects., Methods: Eighteen normal premenopausal subjects underwent two contrast-enhanced MRI scans within 72 hours or during the same menstrual phase in two consecutive months. A subset of nine women also completed diffusion-weighted imaging (DWI). Fibroglandular tissue (FGT) density and FGT enhancement were measured on the contrast-enhanced MRI. Apparent diffusion coefficient (ADC) values were computed from DWI. Between- and within-subject coefficients of variation (bCV and wCV, respectively) were assessed. Repeatability of all measurements was assessed by the coefficient of repeatability (CR) and Bland-Altman plots., Results: The bCV of FGT density and FGT enhancement at visit 1 and visit 2 ranged from 47% to 63%. The wCV was 13% for FGT density, 22% for FGT enhancement, and 11% for ADC. The CRs of FGT density and FGT enhancement were 0.15 and 0.19, respectively, and for ADC, it was 6.1 x 10(-4) mm(2)/s., Conclusions: We present an estimate of the variability and repeatability of MR measurements in normal breasts. These estimates provide the basis for understanding the normal variation of healthy breast tissue in MRI and establishing thresholds for agreement between measurements.

Rationale and Objectives: The aim of this work was to compare a high-resolution diffusion-weighted imaging (HR-DWI) acquisition (voxel size = 4.8 mm(3)) to a standard diffusion-weighted imaging (STD-DWI) acquisition (voxel size = 29.3 mm(3)) for monitoring neoadjuvant therapy-induced changes in breast tumors., Materials and Methods: Nine women with locally advanced breast cancer were imaged with both HR-DWI and STD-DWI before and after 3 weeks (early treatment) of neoadjuvant taxane-based treatment. Tumor apparent diffusion coefficient (ADC) metrics (mean and histogram percentiles) from both DWI methods were calculated, and their relationship to tumor volume change after 12 weeks of treatment (posttreatment) measured by dynamic contrast enhanced magnetic resonance imaging was evaluated with a Spearman's rank correlation., Results: The HR-DWI pretreatment 15th percentile tumor ADC (P = .03) and early treatment 15th, 25th, and 50th percentile tumor ADCs (P = .008, .010, .04, respectively) were significantly lower than the corresponding STD-DWI percentile ADCs. The mean tumor HR-ADC was significantly lower than STD-ADC at the early treatment time point (P = .02), but not at the pretreatment time point (P = .07). A significant early treatment increase in tumor ADC was found with both methods (P < .05). Correlations between HR-DWI tumor ADC and posttreatment tumor volume change were higher than the STD-DWI correlations at both time points and the lower percentile ADCs had the strongest correlations., Conclusion: These initial results suggest that the HR-DWI technique has potential for improving characterization of low tumor ADC values over STD-DWI and that HR-DWI may be of value in evaluating tumor change with treatment., (Copyright © 2013 AUR. Published by Elsevier Inc. All rights reserved.)

Rationale and Objectives: The aim of this study was to evaluate differences in tumor depiction and measured tumor apparent diffusion coefficient (ADC) with the use of a high-resolution diffusion-weighted (DW) magnetic resonance imaging (MRI) sequence, compared to a standard DW MRI sequence, in patients with locally advanced breast cancer., Materials and Methods: Patients with locally advanced breast cancer were scanned with a reduced-field of view (rFOV) DW MRI sequence (high resolution) and a standard-field of view diffusion sequence (standard resolution), and differences between the two sequences were evaluated quantitatively (by calculating tumor ADC distribution parameters) and qualitatively (by radiologists' visual assessments of images)., Results: Although the mean tumor ADC for both sequences was similar, differences were found in other parameters, including the 12.5th percentile (P = .042) and minimum tumor ADC (P = .003). Qualitatively, visualization of tumor morphologic detail, heterogeneity, and conspicuity was improved with rFOV DW MRI, and image quality was higher., Conclusions: Differences in ADC distribution parameters and qualitative image features suggest that the sequences differ in their ability to capture tumor heterogeneity. These differences are not apparent when the mean is used to evaluate tumor ADC. In particular, differences found in lower ADC values are compatible with reduced partial voluming in rFOV DW MRI, suggesting that rFOV DW MRI may be valuable in imaging the lower ADCs expected to correspond to viable tumor in most invasive breast cancers., (Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.)

Measurement of individual organ tissue oxygen levels can provide information to help evaluate and optimize medical interventions in many areas including wound healing, resuscitation strategies, and cancer therapeutics. Echo planar (19) F MRI has previously focused on tumor oxygen measurement at low oxygen levels (pO(2)) <30 mmHg. It uses the linear relationship between spin-lattice relaxation rate (R(1)) of hexafluorobenzene (HFB) and pO(2). The feasibility of this technique for a wider range of pO(2) values and individual organ tissue pO(2) measurement was investigated in a rat model. Spin-lattice relaxation times (T(1) = 1/R(1)) of hexafluorobenzene were measured using (19) F saturation recovery echo planar imaging. Initial in vitro studies validated the linear relationship between R(1) and pO(2) from 0 to 760 mmHg oxygen partial pressure at 25, 37, and 41°C at 7 Tesla for hexafluorobenzene. In vivo experiments measured rat tissue oxygen (ptO2) levels of brain, kidney, liver, gut, muscle, and skin during inhalation of both 30 and 100% oxygen. All organ ptO(2) values significantly increased with hyperoxia (P < 0.001). This study demonstrates that (19) F MRI of hexafluorobenzene offers a feasible tool to measure regional ptO2 in vivo, and that hyperoxia significantly increases ptO2 of multiple organs in a rat model., (Copyright © 2011 Wiley Periodicals, Inc.)

Promising recent investigations have shown that breast malignancies exhibit restricted diffusion on diffusion-weighted imaging (DWI) and may be distinguished from normal tissue and benign lesions in the breast based on differences in apparent diffusion coefficient (ADC) values. In this study, we assessed the influence of intravoxel fat signal on breast diffusion measures by comparing ADC values obtained using a diffusion-weighted single shot fast spin-echo sequence with and without fat suppression. The influence of breast density on ADC measures was also evaluated. ADC values were calculated for both tumor and normal fibroglandular tissue in a group of 21 women with diagnosed breast cancer. There were systematic underestimations of ADC for both tumor and normal breast tissue due to intravoxel contribution from fat signal on non-fat-suppressed DWI. This ADC underestimation was more pronounced for normal tissue values (mean difference=40%) than for tumors (mean difference=27%, P<.001) and was worse in women with low breast tissue density vs. those with extremely dense breasts (P<.05 for both tumor and normal tissue). Tumor conspicuity measured by contrast-to-noise ratio was significantly higher on ADC maps created with fat suppression and was not significantly associated with breast density. In summary, robust fat suppression is important for accurate breast ADC measures and optimal lesion conspicuity on DWI., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Purpose: To evaluate whether quantitative MRI parameters are sensitive to the effects of the tyrosine kinase inhibitor gefitinib and can discriminate between two different treatment protocols., Materials and Methods: Untreated mice with BT474 breast tumor xenografts were characterized in a preliminary study. Subsequently, tumor volume, apparent diffusion coefficient (ADC), transendothelial permeability (K(ps)), and fractional plasma volume (fPV) were measured in three groups of mice receiving: 1) control vehicle for 10 days, or gefitinib as 2) a single daily dose for 10 days or 3) a 2-day pulsed dose., Results: Gefitinib treatment resulted in significant tumor growth inhibition (pulsed: 439 +/- 93; daily: 404 +/- 53; control: 891 +/- 174 mm(3), P < 0.050) and lower cell density (pulsed: 0.15 +/- 0.01, daily: 0.17 +/- 0.01, control: 0.24 +/- 0.01, P < 0.050) after 9 days. Tumor ADC increased in treated groups but decreased in controls (P > 0.050). Tumor K(ps) decreased with pulsed treatment but rebounded afterwards and increased with daily treatment (P > 0.050). Tumor fPV increased in both treated groups, decreasing afterwards with pulsed treatment (P > 0.050)., Conclusion: Quantitative MRI can provide a sensitive measure of gefitinib-induced tumor changes, potentially distinguish between treatment regimens, and may be useful for determining optimal treatment scheduling for enhancing chemotherapy delivery.

Purpose: To determine if inhibitors of the human growth factor receptor (HER) family can be used to enhance tumor vascular permeability and perfusion and optimize the efficacy of cytotoxic chemotherapeutics. Poor tumor vascular function limits the delivery and efficacy of cancer chemotherapeutics and HER family tyrosine kinases mediate tumor-endothelial signaling in both of these compartments., Materials and Methods: BT474 human breast cancer tumors were established in mice and the biologic effects of the HER tyrosine kinase inhibitor (TKI) gefitinib on tumor vascular function was determined by dynamic contrast-enhanced MRI (DCE-MRI), and on tumor vascular architecture and perfusion by immunofluorescence microscopy., Results: A brief dose of gefitinib enhances the antitumor activity of paclitaxel in vivo but not in cell culture, suggesting that its chemoenhancing activity involves the in vivo microenvironment. A brief high dose of gefitinib induces a decrease in endothelial transfer constant (Kps) and a concomitant increase in tumor fractional plasma volume (fPV). These changes are accompanied by a rapid reduction in tumor volume, likely due to decreased tumor edema, and modestly improved tumor vascular architecture and perfusion on microscopy., Conclusion: These data suggest that HER family TKIs have the potential to optimize the tumor microenvironment for delivery of cytotoxic chemotherapeutics., ((c) 2007 Wiley-Liss, Inc.)

The goal of this study was to investigate the relationship between an empirical contrast kinetic parameter, the signal enhancement ratio (SER), for three-timepoint, high spatial resolution contrast-enhanced (CE) MRI, and a commonly analyzed pharmacokinetic parameter, kep, using dynamic high temporal resolution CE-MRI. Computer simulation was performed to investigate: 1) the relationship between the SER and the contrast agent concentration ratio (CACR) of two postcontrast timepoints (tp1 and tp2); 2) the relationship between the CACR and the redistribution rate constant (kep) based on a two-compartment pharmacokinetic model; and 3) the sensitivity of the relationship between the SER and kep to native tissue T1 relaxation time, T10, and to errors in an assumed vascular input function. The relationship between SER and kep was verified experimentally using a mouse model of breast cancer. The results showed that a monotonic mathematical relationship between SER and kep could be established if the acquisition parameters and the two postinjection timepoints of SER, tp1, tp2, were appropriately chosen. The in vivo study demonstrated a close correlation between SER and kep on a pixel-by-pixel basis (Spearman rank correlation coefficient=0.87+/-0.03). The SER is easy to calculate and may have a unique role in breast tissue characterization., (Copyright (c) 2007 Wiley-Liss, Inc.)

Dynamic contrast-enhanced MRI (DCE-MRI) was used to noninvasively evaluate the effects of AG-03736, a novel inhibitor of vascular endothelial growth factor (VEGF) receptor tyrosine kinases, on tumor microvasculature in a breast cancer model. First, a dose response study was undertaken to determine the responsiveness of the BT474 human breast cancer xenograft to AG-013736. Then, DCE-MRI was used to study the effects of a 7-day treatment regimen on tumor growth and microvasculature. Two DCE-MRI protocols were evaluated: (1) a high molecular weight (MW) contrast agent (albumin-(GdDTPA)(30)) with pharmacokinetic analysis of the contrast uptake curve and (2) a low MW contrast agent (GdDTPA) with a clinically utilized empirical parametric analysis of the contrast uptake curve, the signal enhancement ratio (SER). AG-013736 significantly inhibited growth of breast tumors in vivo at all doses studied (10-100 mg/kg) and disrupted tumor microvasculature as assessed by DCE-MRI. Tumor endothelial transfer constant (K(ps)) measured with albumin-(GdDTPA)(30) decreased from 0.034+/-0.005 to 0.003+/-0.001 ml min(-1) 100 ml(-1) tissue (P<.0022) posttreatment. No treatment-related change in tumor fractional plasma volume (fPV) was detected. Similarly, in the group of mice studied with GdDTPA DCE-MRI, AG-013736-induced decreases in tumor SER measures were observed. Additionally, our data suggest that 3D MRI-based volume measurements are more sensitive than caliper measurements for detecting small changes in tumor volume. Histological staining revealed decreases in tumor cellularity and microvessel density with treatment. These data demonstrate that both high and low MW DCE-MRI protocols can detect AG-013736-induced changes in tumor microvasculature. Furthermore, the correlative relationship between microvasculature changes and tumor growth inhibition supports DCE-MRI methods as a biomarker of VEGF receptor target inhibition with potential clinical utility.

Purpose: To determine whether combining 3D fast imaging employing steady-state acquisition (FIESTA) and T1-weighted contrast-enhanced (CE) sequences could help characterize lesions in 32 women with benign, in situ, or invasive breast lesions. Since FIESTA provides both T1 and T2 information on the same three-dimensional (3D) matrix as high-resolution T1-weighted dynamic data, we aimed to verify whether invasive lesions could be separated from in situ and/or benign lesions using quantitative FIESTA measures of tissue intensity and homogeneity., Material and Methods: With the use of CE-MRI data, regions of interest (ROIs) were manually delineated in enhancing lesions and on surrounding normal tissue. These ROIs were then applied to 3D FIESTA data. Quantitative measures between lesion and normal tissue were compared among the lesion groups., Results: On FIESTA most invasive cancer lesions were hypointense compared to surrounding normal tissue (mean lesion intensity was 89% of normal tissue intensity), whereas most ductal and benign lesions appeared hyperintense compared to surrounding normal tissue (lesions at 100.9% and 121.9% of normal tissue intensity, respectively). Measures obtained from resampled T2-weighted data showed no significant differences between the invasive and benign lesion groups., Conclusion: We detected significant differences between invasive and noninvasive lesions by quantifying intensity differences between the lesions and surrounding normal tissue on FIESTA.

Purpose: To investigate the heterogeneity in the angiogenic response of a human breast cancer xenograft to a novel vascular endothelial growth factor (VEGF)-receptor tyrosine kinase inhibitor, AG-013736, using dynamic contrast-enhanced MR imaging (DCE-MRI)., Materials and Methods: Changes in pharmacokinetic parameters in a seven-day interval were compared between AG-treated and control groups, using Gd-DTPA and albumin-(Gd-DTPA)30. A voxel-by-voxel analysis was performed to produce parametric spatial pharmacokinetic parametric maps and histograms. Histogram segmentation was used to quantify the heterogeneity in tumor response to therapy, and compared with conventional descriptive measures of distribution in terms of their capacity to separate control from AG-treated tumors., Results: The albumin-(Gd-DTPA)30 endothelial transfer constant, Kps, showed changes with AG-013736 treatment and tumor growth. The changes were highly heterogeneous for individual segments of the histogram with different Kps values, and the overall patterns in which the frequency distribution changed differed significantly between the two groups. A change in the number of voxels with Kps ranging from 0.03 to 0.14 mL/min/(100 mL tissue) was the most sensitive variable for separating control from AG-treated tumors (P = 0.0008). Parametric maps of the kinetic parameters also showed spatial heterogeneity in tumor response to treatment. The Kps maps depicted rapid development of central necrosis as a result of AG-013736 treatment. Maps of v(p) demonstrated a marked increase at peripheral regions of necrotic areas. Similar trends were noted in the Gd-DTPA rate constant Ktrans distribution., Conclusion: This study demonstrates the value of histogram analysis of maps of pharmacokinetic parameters for assessing heterogeneity in tumor response to antiangiogenic therapy. Changes in the number of voxels within certain segments of the Kps histogram were the most sensitive variable for separating control from AG-treated tumors., ((c) 2005 Wiley-Liss, Inc.)

The ability to make localized temperature measurements in tissue during hyperthermia treatment of cancer is an essential factor in optimizing its efficacy. To this end we have developed and evaluated the complex tris(ethylenediamine) cobalt(III) trichloride as a temperature sensor by determining the temperature dependence of it 59Co nuclear magnetic resonance chemical shift. Encapsulating this complex within liposomes targets the agent to the reticuloendothelial system. Temperature changes of the order of 0.1 degrees C have been measured in vivo on rats, and the half-life of the complex within the body determined by plasma emission spectroscopy.

T1 and T2 were determined simultaneously in vivo at 4.7 T in implanted rat brain tumors. Three different tumor cell lines were implanted in the right caudate nucleus: the F98 glioma, the E367 neuroblastoma, and the RN6 schwannoma. Their T1 and T2 values (mean +/- standard deviation [msec]), respectively, were 1,312 +/- 107 and 89 +/- 3 (glioma), 1,284 +/- 86 and 87 +/- 7 (neuroblastoma), and 1,338 +/- 85 and 86 +/- 9 (schwannoma). The T1 values (msec) of normal brain and muscle were 1,090 +/- 59 and 1,139 +/- 77, respectively, and the T2 values (msec) were 76 +/- 3 and 36 +/- 2, respectively. After injection of the contrast agent manganese (III) tetraphenylporphine sulfonate (TPPS) the T1 of all three tumors decreased by 30% and the T2 by 10%, whereas no such change in relaxivity was noted in normal brain. As a result, strong contrast enhancement of the three tumor types was seen on T1-weighted images. The tumor was clearly delineated and correlated with findings at histologic examination. This tumor enhancement was followed up for 4 days with quantitative relaxation time measurements, and the strong, selective reduction in T1 for all three tumor types after Mn-TPPS injection was preserved over the entire observation period.

Two cases of stereotactically induced and spontaneously metastasizing neoplasms in the rat and the cat brain are reported. In the rat, a malignant Schwannoma derived from initially supratentorially implanted RN6 cells developed a second tumor in the posterior cranial fossa. In the cat, a highly malignant polymorphous anaplastic glioma induced by implantation of cloned rat glioma cells (F98) into the left internal capsule developed small tumor cell nests along the ependyma of the ipsilateral ventricle. In precontrast magnetic resonance imaging (MRI) of both cases, the primary tumor was detectable only by a very weak hypointensity and through a shift of the midline. No metastases were apparent. Application of the metallated paramagnetic porphyrin derivative manganese(III) tetraphenylporphine sulfonate (MnTPPS) resulted in a remarkable contrast enhancement between tumoral and normal tissue, which was evident not only in the primary tumor but also in the small metastases. These observations demonstrate for the first time that MnTPPS is an efficient MRI contrast agent for the detection of metastases from primary brain neoplasms and, in consequence, support the hypothesis of its selective binding to tumor cells.