MRI measurements of breast tumor volume predict response to neoadjuvant chemotherapy and recurrence-free survival

Tumor response and clinical outcome in metastatic gastrointestinal stromal tumors under sunitinib therapy: comparison of RECIST, Choi and volumetric criteria

PURPOSE

Purpose of the study was to compare radiological treatment response according to RECIST, Choi and volumetry in GIST-patients under 2nd-line-sunitinib-therapy and to correlate the results of treatment response assessment with disease-specific survival (DSS).

PATIENTS AND METHODS

20 patients (mean: 60.7 years; 12 male/8 female) with histologically proven GIST underwent baseline-CT of the abdomen under imatinib and follow-up-CTs 3 months and 1 year after change to sunitinib. 68 target lesions (50 hepatic, 18 extrahepatic) were investigated. Therapy response (partial response (PR), stable disease (SD), progressive disease (PD)) was evaluated according to RECIST, Choi and volumetric criteria. Response according to the different assessment systems was compared and correlated to the DSS of the patients utilizing Kaplan-Meier statistics.

RESULTS

The mean DSS (in months) of the response groups 3 months after therapy change was: RECIST: PR (0/20); SD (17/20): 30.4 (months); PD (3/20) 11.6. Choi: PR (10/20) 28.6; SD (8/20) 28.1; PD (2/20) 13.5. Volumetry: PR (4/20) 29.6; SD (11/20) 29.7; PD (5/20) 17.2. Response groups after 1 year of sunitinib showed the following mean DSS: RECIST: PR (3/20) 33.6; SD (9/20) 29.7; PD (8/20) 20.3. Choi: PR (10/20) 21.5; SD (4/20) 42.9; PD (6/20) 23.9. Volumetry: PR (6/20) 27.3; SD (5/20) 38.5; PD (9/20) 19.3.

CONCLUSION

One year after modification of therapy, only partial response according to RECIST indicated favorable survival in patients with GIST. The value of alternate response assessment strategies like Choi criteria for prediction of survival in molecular therapy still has to be demonstrated.

Combined MR, fluorescence and histology imaging strategy in a human breast tumor xenograft model

Applications of molecular imaging in cancer and other diseases frequently require the combination of in vivo imaging modalities, such as MR and optical imaging, with ex vivo optical, fluorescence, histology and immunohistochemical imaging to investigate and relate molecular and biological processes to imaging parameters within the same region of interest. We have developed a multimodal image reconstruction and fusion framework that accurately combines in vivo MRI and MRSI, ex vivo brightfield and fluorescence microscopic imaging and ex vivo histology imaging. Ex vivo brightfield microscopic imaging was used as an intermediate modality to facilitate the ultimate link between ex vivo histology and in vivo MRI/MRSI. Tissue sectioning necessary for optical and histology imaging required the generation of a three-dimensional reconstruction module for two-dimensional ex vivo optical and histology imaging data. We developed an external fiducial marker-based three-dimensional reconstruction method, which was able to fuse optical brightfield and fluorescence with histology imaging data. The registration of the three-dimensional tumor shape was pursued to combine in vivo MRI/MRSI and ex vivo optical brightfield and fluorescence imaging data. This registration strategy was applied to in vivo MRI/MRSI, ex vivo optical brightfield/fluorescence and histology imaging datasets obtained from human breast tumor models. Three-dimensional human breast tumor datasets were successfully reconstructed and fused with this platform.

Texture analysis in assessment and prediction of chemotherapy response in breast cancer

PURPOSE

To assess the efficacy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)-based textural analysis in predicting response to chemotherapy in a cohort of breast cancer patients.

MATERIALS AND METHODS

In all, 100 patients were scanned on a 3.0T HDx scanner immediately prior to neoadjuvant chemotherapy treatment. A software application to use texture features based on co-occurrence matrices was developed. Texture analysis was performed on precontrast and 1-5 minutes postcontrast data. Patients were categorized according to their chemotherapeutic response: partial responders corresponding to a decrease in tumor diameter over 50% (40) and nonresponders corresponding to a decrease of less than 50% (4). Data were also split based on factors that influence response: triple receptor negative phenotype (TNBC) (22) vs. non-TNBC (49); node negative (45) vs. node positive (46); and biopsy grade 1 or 2 (38) vs. biopsy grade 3 (55).

RESULTS

Parameters f2 (contrast), f4 (variance), f10 (difference in variance), f6 (sum average), f7 (sum variance), f8 (sum entropy), f15 (cluster shade), and f16 (cluster prominence) showed significant differences between responders and partial responders of chemotherapy. Differences were mainly seen at 1-3 minutes postcontrast administration. No significant differences were found precontrast administration. Node +ve, high grade, and TNBC are associated with poorer prognosis and appear to be more heterogeneous in appearance according to texture analysis.

CONCLUSION

This work highlights that textural differences between groups (based on response, nodal status, and triple negative groupings) are apparent and appear to be most evident 1-3 minutes postcontrast administration. The fact that significant differences for certain texture parameters and groupings are consistently observed is encouraging.

Current and emerging quantitative magnetic resonance imaging methods for assessing and predicting the response of breast cancer to neoadjuvant therapy

Reliable early assessment of breast cancer response to neoadjuvant therapy (NAT) would provide considerable benefit to patient care and ongoing research efforts, and demand for accurate and noninvasive early-response biomarkers is likely to increase. Response assessment techniques derived from quantitative magnetic resonance imaging (MRI) hold great potential for integration into treatment algorithms and clinical trials. Quantitative MRI techniques already available for assessing breast cancer response to neoadjuvant therapy include lesion size measurement, dynamic contrast-enhanced MRI, diffusion-weighted MRI, and proton magnetic resonance spectroscopy. Emerging yet promising techniques include magnetization transfer MRI, chemical exchange saturation transfer MRI, magnetic resonance elastography, and hyperpolarized MR. Translating and incorporating these techniques into the clinical setting will require close attention to statistical validation methods, standardization and reproducibility of technique, and scanning protocol design.

Microcirculatory fraction (MCF(I)) as a potential imaging marker for tumor heterogeneity in breast cancer

Cancer is a heterogeneous disease by nature. Current imaging studies usually ignore intratumor variability in imaging biomarkers. We postulate that quantifying tumor heterogeneity with imaging techniques can provide useful information about cancer biology and potentially serve as novel imaging biomarkers. In this retrospective study, we identify a potential imaging marker, the microcirculatory fraction (MCF(I)), that quantifies tumor heterogeneity in normoxic/hypoxic cellular composition. We demonstrate its application on a test population of 22 women with stage II/III HER-2 negative breast cancer receiving antiangiogenic-cytotoxic combination neoadjuvant chemotherapy. Early change in MCF(I) (ΔMCF(I)) is assessed with dynamic contrast enhanced magnetic resonance imaging at the end of Cycle 2 and associated with pathologic response. Its performance is compared with other established volumetric imaging biomarkers (initial tumor volume and volume change) by statistical and graphic methods. We demonstrate that a significant (P<.01) difference in ΔMCF(I) can be detected between good (median ΔMCF(I) 0.27) and poor (median ΔMCF(I) -0.12) responders, despite the limited population size. Differences in the volumetric biomarkers are not statistically significant. Receiver operating characteristic analysis also shows that ΔMCF(I) is a good predictor for pathologic response (AUC=0.86, 95% CI 0.69-1.00, P<.01), while predictions made with the established volumetric biomarkers are not significantly better than random guesses. We conclude that ΔMCF(I) has the potential of being a better predictive biomarker for therapeutic response assessment. Our findings support our postulation that quantifying tumor heterogeneity with imaging techniques can provide additional information that can serve as novel biomarkers.

MRI volume measurements compared with the RECIST 1.1 for evaluating the response to neoadjuvant chemotherapy for mass-type lesions

BACKGROUND

The purpose of this study was to compare the accuracy of volumetric (3D) measurements with that of unidimensional (1D) measurements by response evaluation criteria in solid tumors 1.1 (RECIST 1.1) in patients with breast cancer before and after neoadjuvant chemotherapy.

METHODS

The study included 48 patients with breast cancer who underwent neoadjuvant chemotherapy. Dynamic contrast-enhanced magnetic resonance imaging was performed before the first cycle of chemotherapy and after the completion of the planned chemotherapy. The longest diameter and volume of each target lesion were measured using a TeraRecon Aquarius workstation (San Mateo, CA). Response was assessed both by using the RECIST 1.1 and volumetric criteria. Histologic response was assessed using the Sataloff criteria. The agreements between the two measures and the histologic response were analyzed statistically.

RESULTS

In monitoring the response to neoadjuvant chemotherapy, the 1D and 3D measurements showed "good agreement" (κ = 0.610) for the treatment response categories and "moderate agreement" (κ = 0.565) for the responder/non-responder categories. Disagreement was observed in 9 out of 48 comparisons (18.75 %). The percent agreement of the 1D measurement of residual lesions (79.17 %) with the pathology was higher than that by volumetric measurement (70.83 %), but there was no statistically significant difference (p = 0.35). Both the 1D (rho = 0.67, p < 0.0001) and 3D measurements (rho = 0.52, p < 0.0001) showed a moderate degree of linear correlation with the pathologic diameter of residual lesions.

CONCLUSION

There was generally good agreement between the 1D and 3D measurements and moderate predictive value using either approach for predicting pathological response.

Diffuse Optical Monitoring of the Neoadjuvant Breast Cancer Therapy

Recent advances in the use of diffuse optical techniques for monitoring the hemodynamic, metabolic and physiological signatures of the neoadjuvant breast cancer therapy effectiveness is critically reviewed. An extensive discussion of the state-of-theart diffuse optical mammography is presented alongside a discussion of the current approaches to breast cancer therapies. Overall, the diffuse optics field is growing rapidly with a great deal of promise to fill an important niche in the current approaches to monitor, predict and personalize neoadjuvant breast cancer therapies.

Assessment of CAD-generated tumor volumes measured using MRI in breast cancers before and after neoadjuvant chemotherapy

OBJECTIVE

To evaluate inter-observer agreement and the predictive value of tumor size measurements using MRI for breast cancer under neoadjuvant chemotherapy (NAC) by comparing the measurements of the longest diameters (LD), total enhanced volumes (TEV) and washout volumes (WOV).

METHODS

Thirty-seven female breast cancer patients were prospectively enrolled from August 2008 to October 2010. Two of these patients had locally advanced disease. MRI examinations were acquired within 2 weeks before and after NAC. Interim scans were also conducted in 30 patients. Tumor resection was undertaken within 2 weeks after the cessation of NAC. MRI images were independently measured for LD, TEV and WOV by two experienced radiologists. Inter-observer agreement was evaluated using concordance correlation coefficients (CCCs). Tumor sizes after NAC were evaluated relative to their initial sizes for early prediction of a pathological complete response (pCR).

RESULTS

The CCCs were 0.93 (CI: 0.90-0.95) for LD, 0.98 (CI: 0.97-0.98) for TEV and 0.99 (CI: 0.991-0.996) for WOV. All measurements had high inter-observer agreement, but the CCCs were significantly increased in the aforementioned order (P<0.0001). WOV measured after the completion of chemotherapy had significant discriminating ability (P=0.0056) when evaluated using receiver operating characteristic analysis, and was found to be superior to LD (P=0.045). The average WOV size was significantly smaller in pCR cases than in non-pCR cases (P=0.016).

CONCLUSION

Computer-aided detection-generated tumor volumes had significantly higher inter-observer concordance than conventional LD measurements. WOV measurements had the highest concordance, and WOV could better predict pCR after NAC at smaller tumor sizes.

Evaluation of an automatic registration-based algorithm for direct measurement of volume change in tumors

PURPOSE

Assuming that early tumor volume change is a biomarker for response to therapy, accurate quantification of early volume changes could aid in adapting an individual patient's therapy and lead to shorter clinical trials. We investigated an image registration-based approach for tumor volume change quantification that may more reliably detect smaller changes that occur in shorter intervals than can be detected by existing algorithms.

METHODS AND MATERIALS

Variance and bias of the registration-based approach were evaluated using retrospective, in vivo, very-short-interval diffusion magnetic resonance imaging scans where true zero tumor volume change is unequivocally known and synthetic data, respectively. The interval scans were nonlinearly registered using two similarity measures: mutual information (MI) and normalized cross-correlation (NCC).

RESULTS

The 95% confidence interval of the percentage volume change error was (-8.93% to 10.49%) for MI-based and (-7.69%, 8.83%) for NCC-based registrations. Linear mixed-effects models demonstrated that error in measuring volume change increased with increase in tumor volume and decreased with the increase in the tumor's normalized mutual information, even when NCC was the similarity measure being optimized during registration. The 95% confidence interval of the relative volume change error for the synthetic examinations with known changes over ±80% of reference tumor volume was (-3.02% to 3.86%). Statistically significant bias was not demonstrated.

CONCLUSION

A low-noise, low-bias tumor volume change measurement algorithm using nonlinear registration is described. Errors in change measurement were a function of tumor volume and the normalized mutual information content of the tumor.

Diffuse optical spectroscopic imaging correlates with final pathological response in breast cancer neoadjuvant chemotherapy

Diffuse optical spectroscopic imaging (DOSI) non-invasively and quantitatively measures tissue haemoglobin, water and lipid. Pilot studies in small groups of patients demonstrate that DOSI may be useful for longitudinal monitoring and predicting breast cancer neoadjuvant chemotherapy pathological response. This study evaluates the performance of a bedside DOSI platform in 34 breast cancer patients followed for several months. DOSI optical endpoints obtained at multiple timepoints are compared with final pathological response. Thirty-six stage II/III breast cancers (34 patients) were measured in vivo with DOSI prior to, in the middle of and after the completion of pre-surgical neoadjuvant chemotherapy. Cancer therapies ranged from standard anthracyclines to targeted therapies. Changes in DOSI-measured parameters at each timepoint were compared against final surgical pathology. Absolute changes in the tumour-to-normal (T/N) ratio of tissue deoxyhaemoglobin concentration (ctHHb) and relative changes in the T/N ratio of a tissue optical index (TOI) were most sensitive and correlate to pathological response. Changes in ctHHb and TOI were significantly different between tumours that achieved pathological complete response (pCR) versus non-pCR. By therapy midpoint, mean TOI-T/N changes were 47±8 versus 20±5 per cent for pCR versus non-pCR subjects, respectively (Z=0.011). Changes in ctHHb and TOI scaled significantly with the degree of pathological response (non-, partial and complete). DOSI measurements of TOI separated pCR from non-pCR by therapy midpoint regardless of drug or dosing strategy. This approach is well suited to monitoring breast tumour response and may provide feedback for optimizing therapeutic outcomes and minimizing side-effects.

Magnetic resonance imaging of the breast for cancer diagnosis and staging

Gadolinium-enhanced breast magnetic resonance imaging (MRI) is optimally suited for the diagnosis and assessment of breast cancer. The complete breast MRI examination, which includes select nonenhanced sequences, yields abundant information about the nature and stage of disease. In this article, we will explore cancer diagnosis by examining the main imaging features of breast malignancy as well as the assessment of surrounding structures. We will then discuss current ideas in the use of breast MRI in breast cancer, including high-risk screening, evaluation of extent of disease, role in surgical planning, and the use of MRI in the patient receiving neoadjuvant chemotherapy. Breast MRI plays an important role in the assessment of patients with breast malignancy-a role that is yet to be fully defined and used. By understanding the strengths and weakness of this imaging method in cancer evaluation, we hope to highlight the appropriate uses of the technique.

Accuracy of perfusion MRI with high spatial but low temporal resolution to assess invasive breast cancer response to neoadjuvant chemotherapy: a retrospective study

Background

To illustrate that Breast-MRI performed in high spatial resolution and low temporal resolution (1 minute) allows the measurement of kinetic parameters that can assess the final pathologic response to neoadjuvant chemotherapy in breast cancer.

Methods

Breast-MRI was performed in 24 women before and after treatment. Eight series of 1.11 minute-duration were acquired with a sub-millimeter spatial resolution. Transfer constant (K^trans) and leakage space (V_e) were calculated using measured and theoretical Arterial Input Function (AIF). Changes in kinetic parameters after treatment obtained with both AIFs were compared with final pathologic response graded in non-responder (< 50% therapeutic effect), partial-responder (> 50% therapeutic effect) and complete responder. Accuracies to identify non-responders were compared with receiver operating characteristic curves.

Results

With measured-AIF, changes in kinetic parameters measured after treatment were in agreement with the final pathological response. Changes in V_e and K^trans were significantly different between non-(N = 11), partial-(N = 7), and complete (N = 6) responders, (P = 0.0092 and P = 0.0398 respectively). A decrease in V_e of more than -72% and more than -84% for K^trans resulted in 73% sensitivity for identifying non-responders (specificity 92% and 77% respectively). A decrease in V_e of more than -87% helped to identify complete responders (Sensitivity 89%, Specificity 83%). With theoretical-AIF, changes in kinetic parameters had lower accuracy.

Conclusion

There is a good agreement between pathological findings and changes in kinetic parameters obtained with breast-MRI in high spatial and low temporal resolution when measured-AIF is used. Further studies are necessary to confirm whether MRI contrast kinetic parameters can be used earlier as a response predictor to neoadjuvant chemotherapy.

MRI in breast cancer therapy monitoring

Breast MRI has several roles in the clinical management of breast cancer, including as a screening method for high-risk women, as a diagnostic tool used as an adjunct to mammography and ultrasound, and for the staging of disease extent prior to treatment. In addition to these uses, MRI is also employed to track small changes in tumor size and microenvironment. MRI has produced several early indicators of treatment response in clinical trials over the last 10  years, including initial lesion pattern, changes in lesion size, kinetic parameters, apparent diffusion coefficient and T(2) value; the related technique of (1) H MRS has also shown that choline concentration, T(2) value and water-to-fat ratio are response indicators. In addition to measuring anatomical changes in the lesion size, as performed in traditional radiology, MRI has the ability to track vascular and cellular changes using dynamic contrast-enhanced MRI and diffusion-weighted MRI, respectively. By adding (1) H MRS to MRI examinations, metabolic changes can also be determined. These functional imaging techniques allow studies to focus on early time points relative to neoadjuvant treatment. Early treatment response predictors may allow therapy to be tailored to individual patients and thus aid in the realization of the goal of personalized medicine.

Monitoring of neoadjuvant chemotherapy using multiparametric, ²³Na sodium MR, and multimodality (PET/CT/MRI) imaging in locally advanced breast cancer

We prospectively investigated using advanced magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) to identify radiological biomarkers for treatment response in patients receiving preoperative systemic therapy (PST) for locally advanced breast cancer. Patients with a stage II or III breast cancer receiving PST were selected and underwent positron emission tomography (PET), magnetic resonance imaging (MRI), and breast biopsies at baseline and after the first cycle of PST (days 7-8) during the full course of treatment. PET/CT was acquired after injection of 2-deoxy-2-[18F]-fluoro-D-glucose (¹⁸FDG, 0.22 mCi/kg) and quantified with standardized uptake value assessment (SUV). Diagnostic breast MRI and sodium (²³Na) was acquired at 1.5 T. Total tissue sodium concentration (TSC), response criteria in solid tumors (RECIST), and volumes were quantified. Treatment response was determined by pathological assessment at surgery. Immunohistochemistry values of the proliferative index (Ki-67) were performed on biopsy specimens. Six of nineteen eligible women (43 ± 11 years) who received PST underwent radiological imaging of ¹⁸FDG-PET/CT and MRI for at least two cycles of treatment. Five patients had a pathological partial response (pPR) and one had pathological non-response (pNR). TSC decreased 21% in responders with increases in the non-responder (P = 0.03). Greater reduction in SUV was observed in responders (38%) compared to the non-responder (22%; P = 0.03). MRI volumes decreased after cycle 1 by 42% (responders) and 35% (non-responder; P = 0.11). Proliferation index Ki-67 declined in responders in the first cycle (median = 47%, range = 29-20%), but increased (4%) in the non-responder. Significant decreases in TSC, SUV, and Ki-67 were observed in responders with increases in TSC and Ki-67 in non-responders. Our results demonstrate the feasibility of using multi-modality proton, ²³Na MRI, and PET/CT metrics as radiological biomarkers for monitoring response to PST in patients with operable breast cancer.

Size assessment of breast lesions by means of a computer-aided detection (CAD) system for magnetic resonance mammography

PURPOSE

The aim of this study was to investigate the efficacy of a dedicated software tool for automated volume measurement of breast lesions in contrast-enhanced (CE) magnetic resonance mammography (MRM).

MATERIAL AND METHODS

The size of 52 breast lesions with a known histopathological diagnosis (three benign, 49 malignant) was automatically evaluated using different techniques. The volume of all lesions was measured automatically (AVM) from CE 3D MRM examinations by means of a computer-aided detection (CAD) system and compared with the size estimates based on maximum diameter measurement (MDM) on MRM, ultrasonography (US), mammography and histopathology.

RESULTS

Compared with histopathology as the reference method, AVM understimated lesion size by 4% on average. This result was similar to MDM (3% understimation, not significantly different) but significantly better than US and mammographic lesion measurements (24% and 33% size underestimation, respectively).

CONCLUSIONS

AVM is as accurate as MDM but faster. Both methods are more accurate for size assessment of breast lesions compared with US and mammography.

Tumor angiogenesis change estimated by using diffuse optical spectroscopic tomography: demonstrated correlation in women undergoing neoadjuvant chemotherapy for invasive breast cancer?

PURPOSE

To investigate if changes in tumor angiogenesis associated with complete pathologic response (pCR) or partial pathologic response (pPR) to treatment can be demonstrated by using diffuse optical spectroscopic (DOS) tomography.

MATERIALS AND METHODS

All participants in this prospective, HIPAA-compliant, institutional review board-approved study provided written informed consent. Eleven women with invasive breast carcinoma were imaged with DOS tomography prior to, during, and at completion of neoadjuvant chemotherapeutic regimens. By using region of interest (ROI) analysis, the DOS measure of total tissue hemoglobin (Hb(T)) was temporally correlated with quantitative measures of existing (CD31-expressing) and tumor-induced (CD105-expressing) vessels, in pretreatment and posttreatment tissue specimens, to assess change.

RESULTS

Quantified angiogenesis alone in pretreatment core biopsy specimens did not predict treatment response, but mean vessel density (MVD) and mean vessel area (MVA) of CD105-expressing vessels were significantly decreased in women with pCR (n = 7) (P < .001 and P = .003, respectively). MVA of CD105-expressing vessels was also significantly reduced at comparison of pre- and posttreatment residual tumor for women with pPR (n = 4) (P = .033). A longitudinal analysis showed significant decreases (P = .001) in mean Hb(T) levels during neoadjuvant chemotherapy in breast abnormality ROIs for women with pCR but not women with pPR. For women with pCR, but not women with pPR, pretreatment MVD of CD105-expressing vessels correlated with pretreatment Hb(T) (P ≤ .001).

CONCLUSION

DOS tomographic examinations in women with breast cancer who are receiving neoadjuvant chemotherapy show a mean decrease in Hb(T) with time in patients with pCR only. Observed pretreatment and posttreatment correlates with quantified angiogenesis markers confirm the likely biologic origin for this DOS signature and support its potential to predict angiogenic tissue response early in the treatment cycle.

SUPPLEMENTAL MATERIAL

http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11100699/-/DC1.

Association between serial dynamic contrast-enhanced MRI and dynamic 18F-FDG PET measures in patients undergoing neoadjuvant chemotherapy for locally advanced breast cancer

PURPOSE

To investigate the relationship between changes in vascularity and metabolic activity measured by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and dynamic (18)F-FDG-positron emission tomography (PET) in breast tumors undergoing neoadjuvant chemotherapy.

MATERIALS AND METHODS

PET and MRI examinations were performed in 14 patients with locally advanced breast cancer (LABC) before and after chemotherapy. Dynamic (18)F-FDG PET measures included (18)F-FDG transport rate constant from blood to tissue (K(1)) and metabolism flux constant (Ki). DCE-MRI measures included initial peak enhancement (PE), signal enhancement ratio (SER), and tumor volume. Spearman rank-order correlations were assessed between changes in PET and MRI parameters, and measures were compared between patients with and without pathologic complete response (pCR) by Mann-Whitney U-test.

RESULTS

Changes in glucose delivery (PET K(1)) were closely correlated with changes in tumor vascularity as reflected by DCE-MRI SER (r = 0.83, P < 0.001). Metabolic changes in PET Ki showed moderate correlations with vascularity changes as reflected by SER (r = 0.71) and PE (r = 0.76), and correlated closely with MRI tumor volume (r = 0.79, P < 0.001). Decreases in K(1), Ki, SER, and PE were greater for patients with pCR compared to those with residual disease (P < 0.05).

CONCLUSION

Dynamic (18)F-FDG PET and DCE-MRI tumor measures of tumor metabolism, vascularity, and volume were well correlated for assessing LABC response to neoadjuvant chemotherapy and significantly discriminated pathologic complete responders. Further work is necessary to assess the value of combined PET and MRI for evaluating tumor pharmacodynamics in response to novel therapy.

Computer-aided evaluation of breast MRI for the residual tumor extent and response monitoring in breast cancer patients receiving neoadjuvant chemotherapy

Objective

To evaluate the accuracy of a computer-aided evaluation program (CAE) of breast MRI for the assessment of residual tumor extent and response monitoring in breast cancer patients receiving neoadjuvant chemotherapy.

Materials and Methods

Fifty-seven patients with breast cancers who underwent neoadjuvant chemotherapy before surgery and dynamic contrast enhanced MRI before and after chemotherapy were included as part of this study. For the assessment of residual tumor extent after completion of chemotherapy, the mean tumor diameters measured by radiologists and CAE were compared to those on histopathology using a paired student t-test. Moreover, the agreement between unidimensional (1D) measurement by radiologist and histopathological size or 1D measurement by CAE and histopathological size was assessed using the Bland-Altman method. For chemotherapy monitoring, we evaluated tumor response through the change in the 1D diameter by a radiologist and CAE and three-dimensional (3D) volumetric change by CAE based on Response Evaluation Criteria in Solid Tumors (RECIST). Agreement between the 1D response by the radiologist versus the 1D response by CAE as well as by the 3D response by CAE were evaluated using weighted kappa (k) statistics.

Results

For the assessment of residual tumor extent after chemotherapy, the mean tumor diameter measured by radiologists (2.0 ± 1.7 cm) was significantly smaller than the mean histological diameter (2.6 ± 2.3 cm) (p = 0.01), whereas, no significant difference was found between the CAE measurements (mean = 2.2 ± 2.0 cm) and histological diameter (p = 0.19). The mean difference between the 1D measurement by the radiologist and histopathology was 0.6 cm (95% confidence interval: -3.0, 4.3), whereas the difference between CAE and histopathology was 0.4 cm (95% confidence interval: -3.9, 4.7). For the monitoring of response to chemotherapy, the 1D measurement by the radiologist and CAE showed a fair agreement (k = 0.358), while the 1D measurement by the radiologist and 3D measurement by CAE showed poor agreement (k = 0.106).

Conclusion

CAE for breast MRI is sufficiently accurate for the assessment of residual tumor extent in breast cancer patients receiving neoadjuvant chemotherapy. However, for the assessment of response to chemotherapy, the assessment by the radiologist and CAE showed a fair to poor agreement.

Multiparametric magnetic resonance imaging, spectroscopy and multinuclear (²³Na) imaging monitoring of preoperative chemotherapy for locally advanced breast cancer

RATIONALE AND OBJECTIVES

The aim of this prospective study was to investigate using multiparametric and multinuclear magnetic resonance imaging during preoperative systemic therapy for locally advanced breast cancer.

MATERIALS AND METHODS

Women with operable stage 2 or 3 breast cancer who received preoperative systemic therapy were studied using dynamic contrast-enhanced magnetic resonance imaging, magnetic resonance spectroscopy, and ²³Na magnetic resonance. Quantitative metrics of choline peak signal-to-noise ratio, total tissue sodium concentration, tumor volumes, and Response Evaluation Criteria in Solid Tumors were determined and compared to final pathologic results using receiver-operating characteristic analysis. Hormonal markers were investigated. Statistical significance was set at P < .05.

RESULTS

Eighteen eligible women were studied. Fifteen responded to therapy, four (22%) with pathologic complete response and 11 (61%) with pathologic partial response. Three patients (17%) had no response. Among estrogen receptor-positive, HER2-positive, and triple-negative phenotypes, observed frequencies of pathologic complete response, pathologic partial response, and no response were 2, 5, and 0; 1, 4, and 0; and 1, 1, and 3, respectively. Responders (pathologic complete response and pathologic partial response) had the largest reductions in choline signal-to-noise ratio (35%, from 7.2 ± 2.3 to 4.6 ± 2; P < .01) compared to nonresponders (11%, from 8.4 ± 2.7 to 7.5 ± 3.6; P = .13) after the first cycle. Total tissue sodium concentration significantly decreased in responders (27%, from 66 ± 18 to 48.4 ± 8 mmol/L; P = .01), while there was little change in nonresponders (51.7 ± 7.6 to 56.5 ± 1.6 mmol/L; P = .50). Lesion volume decreased in responders (40%, from 78 ± 78 to 46 ± 51 mm³; P = .01) and nonresponders (21%, from 100 ± 104 to 79.2 ± 87 mm³; P = .23) after the first cycle. The largest reduction in Response Evaluation Criteria in Solid Tumors occurred after the first treatment in responders (18%, from 24.5 ± 20 to 20.2 ± 18 mm; P = .01), with a slight decrease in tumor diameter noted in nonresponders (17%, from 23 ± 19 to 19.2 ± 19.1 mm; P = .80).

CONCLUSIONS

Multiparametric and multinuclear imaging parameters were significantly reduced after the first cycle of preoperative systemic therapy in responders, specifically, choline signal-to-noise ratio and sodium. These new surrogate radiologic biomarkers maybe able to predict and provide a platform for potential adaptive therapy in patients.

Comparison of mammography, sonography, MRI and clinical examination in patients with locally advanced or inflammatory breast cancer who underwent neoadjuvant chemotherapy

OBJECTIVES

The purpose of this study was to determine the relative accuracies of mammography, sonography, MRI and clinical examination in predicting residual tumour size and pathological response after neoadjuvant chemotherapy for locally advanced or inflammatory breast cancer. Each prediction method was compared with the gold standard of surgical pathology.

METHODS

43 patients (age range, 25-62 years; mean age, 42.7 years) with locally advanced or inflammatory breast cancer who had been treated by neoadjuvant chemotherapy were enrolled prospectively. We compared the predicted residual tumour size and the predicted response on imaging and clinical examination with residual tumour size and response on pathology. Statistical analysis was performed using weighted kappa statistics and intraclass correlation coefficients (ICC).

RESULTS

The ICC values between predicted tumour size and pathologically determined tumour size were 0.65 for clinical examination, 0.69 for mammography, 0.78 for sonography and 0.97 for MRI. Agreement between the response predictions at mid-treatment and the responses measured by pathology had kappa values of 0.28 for clinical examination, 0.32 for mammography, 0.46 for sonography and 0.68 for MRI. Agreement between the final response predictions and the responses measured by pathology had kappa values of 0.43 for clinical examination, 0.44 for mammography, 0.50 for sonography and 0.82 for MRI.

CONCLUSION

Predictions of response and residual tumour size made on MRI were better correlated with the assessments of response and residual tumour size made upon pathology than were predictions made on the basis of clinical examination, mammography or sonography. Thus, the evaluation of predicted response using MRI could provide a relatively sensitive early assessment of chemotherapy efficacy.

Image guided near-infrared spectroscopy of breast tissue in vivo using boundary element method

We demonstrate quantitative functional imaging using image-guided near-infrared spectroscopy (IG-NIRS) implemented with the boundary element method (BEM) for reconstructing 3-D optical property estimates in breast tissue in vivo. A multimodality MRI-NIR system was used to collect measurements of light reflectance from breast tissue. The BEM was used to model light propagation in 3-D based only on surface discretization in order to reconstruct quantitative values of total hemoglobin (HbT), oxygen saturation, water, and scatter. The technique was validated in experimental measurements from heterogeneous breast-shaped phantoms with known values and applied to a total of seven subjects comprising six healthy individuals and one participant with cancer imaged at two time points during neoadjuvant chemotherapy. Using experimental measurements from a heterogeneous breast phantom, BEM for IG-NIRS produced accurate values for HbT in the inclusion with a <3% error. Healthy breast tissues showed higher HbT and water in fibroglandular tissue than in adipose tissue. In a subject with cancer, the tumor showed higher HbT compared to the background. HbT in the tumor was reduced by 9 μM during treatment. We conclude that 3-D MRI-NIRS with BEM provides quantitative and functional characterization of breast tissue in vivo through measurement of hemoglobin content. The method provides potentially complementary information to DCE-MRI for tumor characterization.

Breast MR imaging: current indications and advanced imaging techniques

Breast cancer is the most common solid tumor diagnosed in women. In the past decades, great strides have been made in breast cancer screening. While multiple screening trials have shown the benefits of screening mammography, there are limitations to x-ray mammography. Given these inherent limitations, efforts have been made to develop adjunctive imaging techniques, including screening ultrasonography, gamma-specific breast imaging, breast tomosynthesis, dedicated breast computed tomography, and breast magnetic resonance (MR) imaging. This article addresses the current indications and advanced imaging applications of breast MR imaging.

Role of breast MR imaging in neoadjuvant chemotherapy

Neoadjuvant chemotherapy is now widely used in the management of locally advanced breast cancer (LABC). Early initiation of systemic therapy can improve overall and disease-free survival for patients with LABC or inflammatory cancer. MR imaging with intravenous contrast and advanced MR imaging techniques provide new opportunities for assessing tumor morphologic changes, tumor vascularity, tumor cellularity, and tumor metabolic features. MR imaging is more reliable than the conventional methods in the assessment of tumor size and vascularity changes during and after chemotherapy. The addition of advanced imaging techniques to further characterize tumor cellularity and metabolic features appears promising. However, there is still no consensus on the role of MR imaging for assessing response to neoadjuvant chemotherapy or on a standardized MR imaging examination in patients receiving neoadjuvant chemotherapy.

Frequent optical imaging during breast cancer neoadjuvant chemotherapy reveals dynamic tumor physiology in an individual patient

RATIONALE AND OBJECTIVES

Imaging tumor response to neoadjuvant chemotherapy in vivo offers unique opportunities for patient care and clinical decision-making. Detailed imaging studies may allow oncologists to optimize therapeutic drug type and dose based on individual patient response. Most radiologic methods are used sparingly because of cost; thus, important functional information about tumor response dynamics may be missed. In addition, current clinical standards are based on determining tumor size changes; thus, standard anatomic imaging may be insensitive to early or frequent biochemical responses. Because optical methods provide functional imaging end points, our objective is to develop a low-barrier-to-access bedside approach that can be used for frequent, functional assessment of dynamic tumor physiology in individual patients.

MATERIALS AND METHODS

Diffuse Optical Spectroscopic Imaging (DOSI) is a noninvasive, bedside functional imaging technique that quantifies the concentration and molecular state of tissue hemoglobin, water, and lipid. Pilot clinical studies have shown that DOSI may be a useful tool for quantifying neoadjuvant chemotherapy response, typically by comparing the degree of change in tumor water and deoxy-hemoglobin concentration before and after therapy. Patient responses at 1 week and mid-therapy have been used to predict clinical outcome. In this report, we assess the potential value of frequent DOSI monitoring by performing measurements on 19 different days in a 51-year-old subject with infiltrating ductal carcinoma (initial tumor size 60 x 27 mm) who received neoadjuvant chemotherapy (anthracyclines and bevacizumab) over an 18-week period.

RESULTS

A composite index, the Tissue Optical Index (TOI), showed a significant ( approximately 50%) decrease over the nearly 18 weeks of chemotherapy. Tumor response was sensitive to the type of chemotherapy agent, and functional indices fluctuated in a manner consistent with dynamic tumor physiology. Final pathology revealed 4 mm of residual disease, which was detectible by DOSI at the conclusion of chemotherapy before surgery.

CONCLUSION

This case study suggests that DOSI may be a bedside-capable tool for frequent longitudinal monitoring of therapeutic functional response to neoadjuvant chemotherapy.

Molecular and Functional Imaging of Breast Cancer

Background

Significant efforts have been directed toward developing and enhancing imaging methods for the early detection, diagnosis, and characterization of small breast tumors. Molecular and functional imaging sets the stage for enhancement of current methodology.

Methods

Current imaging modalities are described based on the molecular characteristics of normal and malignant tissue. New molecular imaging methods that have the potential for clinical use are also discussed.

Results:

Dynamic contrast-enhanced magnetic resonance imaging is more sensitive than mammography in BRCA1 carriers. It is used in screening and in the early evaluation of neoadjuvant therapy. Positron emission mammography is 91% sensitive and 93% specific in detecting primary breast cancers. Sentinel node scintigraphy is a key component of axillary lymph node evaluation. Other imaging modalities being studied include Tc99m sestamibi, radiolabeled thymidine or uridine, estrogen receptor imaging, magnetic resonance spectroscopy, and diffusion magnetic resonance imaging.

Conclusions

Molecular and functional imaging of the breast will likely alter clinical practice in diagnosing and staging primary breast cancer and assessing response to therapy since it will provide earlier information regarding the underlying biology of individual breast cancers, tumor stage, potential treatment strategies, and biomarkers for early evaluation of treatment effects.

Diffusion-weighted magnetic resonance imaging for pretreatment prediction and monitoring of treatment response of patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy

BACKGROUND

For patients with locally advanced breast cancer (LABC) undergoing neoadjuvant chemotherapy (NACT), the European Guidelines for Breast Imaging recommends magnetic resonance imaging (MRI) to be performed before start of NACT, when half of the NACT has been administered and prior to surgery. This is the first study addressing the value of flow-insensitive apparent diffusion coefficients (ADCs) obtained from diffusion-weighted (DW) MRI at the recommended time points for pretreatment prediction and monitoring of treatment response.

MATERIALS AND METHODS

Twenty-five LABC patients were included in this prospective study. DW MRI was performed using single-shot spin-echo echo-planar imaging with b-values of 100, 250 and 800 s/mm(2) prior to NACT, after four cycles of NACT and at the conclusion of therapy using a 1.5 T MR scanner. ADC in the breast tumor was calculated from each assessment. The strength of correlation between pretreatment ADC, ADC changes and tumor volume changes were examined using Spearman's rho correlation test.

RESULTS

Mean pretreatment ADC was 1.11 + or - 0.21 x 10(-3) mm(2)/s. After 4 cycles of NACT, ADC was significantly increased (1.39 + or - 0.36 x 10(-3) mm(2)/s; p=0.018). There was no correlation between individual pretreatment breast tumor ADC and MR response measured after four cycles of NACT (p=0.816) or prior to surgery (p=0.620).

CONCLUSION

Pretreatment tumor ADC does not predict treatment response for patients with LABC undergoing NACT. Furthermore, ADC increase observed mid-way in the course of NACT does not correlate with tumor volume changes.

Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group

The use of breast magnetic resonance imaging (MRI) is rapidly increasing. EUSOMA organised a workshop in Milan on 20-21st October 2008 to evaluate the evidence currently available on clinical value and indications for breast MRI. Twenty-three experts from the disciplines involved in breast disease management - including epidemiologists, geneticists, oncologists, radiologists, radiation oncologists, and surgeons - discussed the evidence for the use of this technology in plenary and focused sessions. This paper presents the consensus reached by this working group. General recommendations, technical requirements, methodology, and interpretation were firstly considered. For the following ten indications, an overview of the evidence, a list of recommendations, and a number of research issues were defined: staging before treatment planning; screening of high-risk women; evaluation of response to neoadjuvant chemotherapy; patients with breast augmentation or reconstruction; occult primary breast cancer; breast cancer recurrence; nipple discharge; characterisation of equivocal findings at conventional imaging; inflammatory breast cancer; and male breast. The working group strongly suggests that all breast cancer specialists cooperate for an optimal clinical use of this emerging technology and for future research, focusing on patient outcome as primary end-point.

Neoadjuvant chemotherapy for early breast cancer

BACKGROUND

Neoadjuvant chemotherapy defines the preoperative administration of systemic therapy in order to downstage the primary tumor and affected lymph nodes to improve the surgical approach. Neoadjuvant chemotherapy is increasingly being used in the treatment of early operable breast cancer.

OBJECTIVE

We reviewed the available data of neoadjuvant chemotherapy with emphasis on tumor response assessment and prediction, and locoregional management.

METHODS

We searched the databases of MEDLINE and EMBASE using the search terms breast cancer, neoadjuvant or preoperative or primary or induction, and chemotherapy from 1950 to 1 March 2009.

RESULTS/CONCLUSION

Compared with adjuvant chemotherapy, neoadjuvant chemotherapy increases breast conservation with equal survival and locoregional control. Tumor response assessment during neoadjuvant chemotherapy allows identification of in vivo tumor sensitivity to different agents which will help determine predictive factors for improved selection criteria. Randomized trials assessing the timing of sentinel lymph node biopsy in initially lymph node positive patients are warranted. In the near future, intraoperative fluorescent imaging and targeting of cancer stem cells will become important avenues of research.

Diagnostic breast MR imaging: current status and future directions

Breast MRI has become an integral component in breast imaging. Indications have become clearer and better defined. Guidelines and recommendations are evolving and many are recognized and published. Future applications are exciting and may possibly improve our ability to diagnose breast cancer, improving the patient's treatment options and ultimately patient outcome.

Treatment response assessment of breast masses on dynamic contrast-enhanced magnetic resonance scans using fuzzy c-means clustering and level set segmentation

The goal of this study was to develop an automated method to segment breast masses on dynamic contrast-enhanced (DCE) magnetic resonance (MR) scans and to evaluate its potential for estimating tumor volume on pre- and postchemotherapy images and tumor change in response to treatment. A radiologist experienced in interpreting breast MR scans defined a cuboid volume of interest (VOI) enclosing the mass in the MR volume at one time point within the sequence of DCE-MR scans. The corresponding VOIs over the entire time sequence were then automatically extracted. A new 3D VOI representing the local pharmacokinetic activities in the VOI was generated from the 4D VOI sequence by summarizing the temporal intensity enhancement curve of each voxel with its standard deviation. The method then used the fuzzy c-means (FCM) clustering algorithm followed by morphological filtering for initial mass segmentation. The initial segmentation was refined by the 3D level set (LS) method. The velocity field of the LS method was formulated in terms of the mean curvature which guaranteed the smoothness of the surface, the Sobel edge information which attracted the zero LS to the desired mass margin, and the FCM membership function which improved segmentation accuracy. The method was evaluated on 50 DCE-MR scans of 25 patients who underwent neoadjuvant chemotherapy. Each patient had pre- and postchemotherapy DCE-MR scans on a 1.5 T magnet. The in-plane pixel size ranged from 0.546 to 0.703 mm and the slice thickness ranged from 2.5 to 4.5 mm. The flip angle was 15 degrees, repetition time ranged from 5.98 to 6.7 ms, and echo time ranged from 1.2 to 1.3 ms. Computer segmentation was applied to the coronal T1-weighted images. For comparison, the same radiologist who marked the VOI also manually segmented the mass on each slice. The performance of the automated method was quantified using an overlap measure, defined as the ratio of the intersection of the computer and the manual segmentation volumes to the manual segmentation volume. Pre- and postchemotherapy masses had overlap measures of 0.81 +/- 0.13 (mean +/- s.d.) and 0.71 +/- 0.22, respectively. The percentage volume reduction (PVR) estimated by computer and the radiologist were 55.5 +/- 43.0% (mean +/- s.d.) and 57.8 +/- 51.3%, respectively. Paired Student's t test indicated that the difference between the mean PVRs estimated by computer and the radiologist did not reach statistical significance (p = 0.641). The automated mass segmentation method may have the potential to assist physicians in monitoring volume change in breast masses in response to treatment.

Malignant lesion segmentation in contrast-enhanced breast MR images based on the marker-controlled watershed

Breast tumor volume measured on MRI has been used to assess response to neoadjuvant chemotherapy. However, accurate and reproducible delineation of breast lesions can be challenging, since the lesions may have complicated topological structures and heterogeneous intensity distributions. In this article, the authors present an advanced computerized method to semiautomatically segment tumor volumes on T1-weighted, contrast-enhanced breast MRI. The method starts with manual selection of a region of interest (ROI) that contains the lesion to be segmented in a single image, followed by automated separation of the lesion volume from its surrounding breast parenchyma by using a unique combination of the image processing techniques including Gaussian mixture modeling and a marker-controlled watershed transform. Explicitly, the Gaussian mixture modeling is applied to an intensity histogram of the pixels inside the ROI to distinguish the tumor class from other tissues. Based on the ROI and the intensity distribution of the tumor, internal and external markers are determined and the tumor contour is delineated using the marker-controlled watershed transform. To obtain the tumor volume, the segmented tumor in one slice is propagated to the adjacent slice to form an ROI in that slice. The marker-controlled watershed segmentation is then used again to obtain a tumor contour in the propagated slice. This procedure is terminated when there is no lesion in an adjacent slice. To reduce measurement variations possibly caused by the manual selection of the ROI, the segmentation result is refined based on an automatically determined ROI based on the segmented volume. The algorithm was applied to 13 patients with breast cancer, prospectively accrued prior to beginning neoadjuvant chemotherapy. Each patient had two MRI scans, a baseline MRI examination prior to commencing neoadjuvant chemotherapy and a 1 week follow-up after receiving the first dose of neoadjuvant chemotherapy. Blinded to the computer segmentation results, two experienced radiologists manually delineated all tumors independently. The computer results were then compared with the manually generated results using the volume overlap ratio, defined as the intersection of the computer- and radiologist-generated tumor volumes divided by the union of the two. The algorithm reached overall overlap ratios of 62.6% +/- 9.1% and 61.0% +/- 11.3% in comparison to the two manual segmentation results, respectively. The overall overlap ratio between the two radiologists' manual segmentations was 64.3% +/- 10.4%. Preliminary results suggest that the proposed algorithm is a promising method for assisting in tumor volume measurement in contrast-enhanced breast MRI.

The role of mean diffusivity (MD) as a predictive index of the response to chemotherapy in locally advanced breast cancer: a preliminary study

OBJECTIVE

To evaluate the role of mean diffusivity (MD) as a predictive index of the response to chemotherapy in locally advanced breast cancer.

METHODS

Twenty-one women referred to our institution with a diagnosis of locally advanced breast cancer underwent magnetic resonance imaging (MRI) studies at 1.5 T before beginning and after completing combined neoadjuvant chemotherapy. The examination protocol included an EPI sequence sensitised to diffusion (b-value 1,000 s/mm(2)) and three-dimensional (3D) coronal T1 sequences before and after intravenous contrast medium. Tumours were delineated by using dynamic MR acquisition before and after chemotherapy. The percentage of tumour volume reduction (PVR) and pre-(MD(pre)) and post-therapy (MD(post)) MD values were computed for each lesion.

RESULTS

PVR >or= 65% was observed in 17/21 patients (responders). MD(pre) of responders (0.99 +/- 0.27 10(-3) mm(2)/s) was significantly (p = 0.025) lower than MD(pre) of non-responders (1.46 +/- 0.33 10(-3) mm(2)/s). Moreover, in patients as a whole PVR significantly correlated (p = 0.01, r = -0.54) with MD(pre). MD(post) (1.26 +/- 0.39 10(-3) mm(2)/s) of responders was significantly(p = 0.024) higher than MD(pre) (0.99 +/- 0.27 mm(2) 10(-3) mm(2)/s), whereas non-responders MD(post) (1.00 +/- 0.14 10(-3) mm(2)/s)did not increase compared with MD(pre) (1.46 +/- 0.33 10(-3) mm(2)/s).

CONCLUSIONS

This preliminary study seems to indicate that low values of pre-chemotherapy MD may identify, before starting treatment, the patients with higher probability of response in terms of percentage of volume reduction of the lesion. MD may represent a complementary parameter useful to correctly select patients for neoadjuvant chemotherapy.

Spatial registration of temporally separated whole breast 3D ultrasound images

The purpose of this study was to evaluate the potential for use of image volume based registration (IVBaR) to aid in measurement of changes in the tumor during chemotherapy of breast cancer. Successful IVBaR could aid in the detection of such changes in response to neoadjuvant chemotherapy and potentially be useful for routine breast cancer screening and diagnosis. IVBaR was employed in a new method of automated estimation of tumor volume in studies following the radiologist identification of the tumor region in the prechemotherapy scan. The authors have also introduced a new semiautomated method for validation of registration based on Doppler ultrasound (U.S.) signals that are independent of the grayscale signals used for registration. This Institutional Review Board approved study was conducted on 10 patients undergoing chemotherapy and 14 patients with a suspicious/unknown mass scheduled to undergo biopsy. Reasonably reproducible mammographic positioning and nearly whole breast U.S. imaging were achieved. The image volume was registered offline with a mutual information cost function and global interpolation based on a thin-plate spline using MIAMI FUSE software developed at the University of Michigan. The success and accuracy of registration of the three dimensional (3D) U.S. image volume were measured by means of mean registration error (MRE). IVBaR was successful with MRE of 4.3 +/- 1.7 mm in 9 out of 10 reproducibility automated breast ultrasound (ABU) studies and in 12 out of 17 ABU image pairs collected before, during, or after 115 +/- 14 days of chemotherapy. Semiautomated tumor volume estimation was performed on registered image volumes giving 86 +/- 8% mean accuracy compared to the radiologist hand-segmented tumor volume on seven cases. Doppler studies yielded fractional volume of color pixels in the region surrounding the lesion and its change with changing breast compression. The Doppler study of patients with detectable blood flow included five patients with suspicious masses and three undergoing chemotherapy. Spatial alignment of the 3D blood vessel data from the Doppler studies provided independent measures for the validation of registration. In 15 Doppler image volume pairs scanned with differing breast compression, the mean centerline separation value was 1.5 +/- 0.6 mm, while MRE based on a few identifiable structural points common to the two grayscale image volumes was 1.1 +/- 0.6 mm. Another measure, the overlap ratio of blood vessels, was shown to increase from 0.32 to 0.59 (+84%) with IVBaR for pairs at various compression levels. These results show that successful registration of ABU scans may be accomplished for comparison and integration of information.

Effect of the enhancement threshold on the computer-aided detection of breast cancer using MRI

RATIONALE AND OBJECTIVES

To evaluate the effect that variations in the enhancement threshold have on the diagnostic accuracy of two computer-aided detection (CAD) systems for magnetic resonance based breast cancer screening.

MATERIALS AND METHODS

Informed consent was obtained from all patients participating in cancer screening and this study was approved by the participating institution's review board. This retrospective study was nested in a prospective, single-institution, high-risk, breast screening study involving dynamic contrast-enhanced magnetic resonance imaging. Only those screening examinations (n = 223) for which a histopathological diagnosis was available were included. Two CAD methods were performed: the signal enhancement ratio (SER) and support vector machines (SVMs). Statistical analysis was performed by tracking changes in each CAD test's diagnostic accuracy (eg, receiver-operating characteristic [ROC] curve area, maximum possible sensitivity) with changes in the enhancement threshold.

RESULTS

The enhancement threshold plays a significant role in affecting a CAD test's potential sensitivity, ROC curve area, and number of assumed true and false-positive predictions per cancerous examination. A high threshold can also limit the CAD-based detection of the full size of a lesion.

CONCLUSIONS

Enhancement thresholds can limit a CAD test's ability to diagnose a lesion's full size and as such should not be raised above 60%. The clinically used SER method exhibits a high rate of false positives at low enhancement thresholds and as such the threshold should not be set lower than 50%. The SVM method yielded better results in our study than the SER method at clinically realistic enhancement thresholds.

Predicting survival and early clinical response to primary chemotherapy for patients with locally advanced breast cancer using DCE-MRI

PURPOSE

To evaluate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) as a tool for early prediction of response to neoadjuvant chemotherapy (NAC) and 5-year survival in patients with locally advanced breast cancer.

MATERIALS AND METHODS

DCE-MRI was performed in patients scheduled for NAC (n = 24) before and after the first treatment cycle. Clinical response was evaluated after completed NAC. Relative signal intensity (RSI) and area under the curve (AUC) were calculated from the DCE-curves and compared to clinical treatment response. Kohonen and probabilistic neural network (KNN and PNN) analysis were used to predict 5-year survival.

RESULTS

RSI and AUC were reduced after only one cycle of NAC in patients with clinical treatment response (P = 0.02 and P = 0.08). The mean and 10th percentile RSI values before NAC were significantly lower in patients surviving more than 5 years compared to nonsurvivors (P = 0.05 and 0.02). This relationship was confirmed using KNN, which demonstrated that patients who remained alive clustered in separate regions from those that died. Calibration of contrast enhancement curves by PNN for patient survival at 5 years yielded sensitivity and specificity for training and testing ranging from 80%-92%.

CONCLUSION

DCE-MRI in locally advanced breast cancer has the potential to predict 5-year survival in a small patient cohort. In addition, changes in tumor vascularization after one cycle of NAC can be assessed.

Evaluation of breast tumor response to neoadjuvant chemotherapy with tomographic diffuse optical spectroscopy: case studies of tumor region-of-interest changes

PURPOSE

To evaluate two methods of summarizing tomographic diffuse optical spectroscopic (DOS) data through region-of-interest (ROI) analysis to differentiate complete from incomplete responses in patients with locally advanced breast cancer undergoing neoadjuvant treatment and to estimate the standard deviations of these methods for power analysis of larger study designs in the future.

MATERIALS AND METHODS

Subjects participating in the HIPAA-compliant imaging study, approved by the institutional review board, provided written informed consent and were compensated for their examination participation. Seven of 16 cases in women with complete study data were analyzed by using both fixed- and variable-size (full-width-at-half-maximum) ROI measures of the DOS total hemoglobin concentration (Hb(T)), blood oxygen saturation, water fraction, optical scattering amplitude, and scattering power in the ipsilateral and contralateral breasts. Postsurgical histopathologic analysis was used to categorize patients as having a complete or incomplete treatment response.

RESULTS

Average normalized change in Hb(T) was the only DOS parameter to show significant differences (P < or = .05) in the pathologic complete response (pCR) and pathologic incomplete response (pIR) outcomes in seven patients. Mean values of the changes for fixed-size ROIs were -64.2% +/- 50.8 (standard deviation) and 16.9% +/- 38.2 for the pCR and pIR groups, respectively, and those for variable-size ROIs were -96.7% +/- 91.8, and 14.1% +/- 26.7 for the pCR and pIR groups, respectively.

CONCLUSION

Tomographic DOS may provide findings predictive of therapeutic response, which could lead to superior individualized patient treatment.

SUPPLEMENTAL MATERIAL

http://radiology.rsnajnls.org/cgi/content/full/2522081202/DC1.

Are we HER-ting for innovation in neoadjuvant breast cancer trial design?

Through the use of surrogate markers of efficacy, neoadjuvant studies may facilitate the implementation of new treatments into clinical practice. However, disease-free survival is the current standard outcome endpoint for registration of a novel treatment. The coupling of smaller neoadjuvant 'proof of principle' studies with larger adjuvant registration trials offers the promise of speeding up the time to market of new therapies. Clever new designs, such as the 'biological window' and 'learn on the way', can provide valuable insight regarding mechanisms of action and resistance of these novel drugs by identifying patients who are most likely to respond to a novel therapy early in the drug development process. Using the ongoing neoadjuvant trials with HER2 (human epidermal growth factor receptor 2)-directed therapy as a paradigm, this article discusses recent innovations in study design and the challenges of conducting translational research in the neoadjuvant setting.

Longitudinal study of the assessment by MRI and diffusion-weighted imaging of tumor response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy

Measurements of tumor apparent diffusion coefficient (ADC), volume and diameter in assessing the response of patients with locally advanced breast cancer (LABC) (n = 56) undergoing neoadjuvant chemotherapy (NACT) at four time periods (before treatment and after three cycles of NACT) were carried out at 1.5 T using diffusion-weighted imaging (DWI) and MRI. Ten benign tumors and 15 controls were also investigated. The MR tumor response was compared with the clinical response. Mean ADC before treatment of malignant breast tissue was significantly lower than that of controls, disease-free contralateral tissue of the patients, and benign lesions, and gradually increased during the course of NACT. Analysis of the percentage change in ADC, volume and diameter after each cycle of NACT between clinical responders and non-responders showed that the change in ADC after the first cycle was statistically significant compared with volume and diameter, indicating its potential in assessing early response. After the third cycle, the sensitivity for differentiating responders from non-responders was 89% for volume and diameter and 68% for ADC, and the respective specificities were 50%, 70% and 100%. A sensitivity of 84% (specificity of 60% with an accuracy of 76%) was achieved when all three variables were taken together to predict the response. A cut-off value of ADC was also calculated using receiver operator characteristics analysis to discriminate between normal, benign and malignant breast tissue. Similarly, a cut-off value for ADC, volume and diameter was obtained after the second and third cycles of NACT to predict tumor response. The results show that ADC is more useful for predicting early tumor response to NACT than morphological variables, suggesting its potential in effective treatment management.