MRI in breast cancer therapy monitoring

Implications of Agile Values in Software Engineering for Agility in Breast Cancer Treatment: Protocol for a Comparative Study

BACKGROUND

Breast cancer treatment has been described as a dynamic and patient-centered approach that emphasizes adaptability and flexibility throughout the treatment process. Breast cancer is complex, with varying subtypes and stages, making it important to tailor treatment plans to each patient's unique circumstances. Breast cancer treatment delivery relies on a multidisciplinary team of health care professionals who collaborate to provide personalized care and quick adaptation to changing conditions to optimize outcomes while minimizing side effects and maintaining the patient's quality of life. However, agility in breast cancer treatment has not been defined according to common agile values and described in language comprehensible to breast cancer professionals. In the rapidly evolving landscape of breast cancer treatment, the incorporation of agile values from software engineering promises to enhance patient care.

OBJECTIVE

Our objective is to propose agile values for breast cancer treatment adopted and adapted from software engineering. We also aim to validate how these values conform to the concept of agility in the breast cancer context through referencing past work.

METHODS

We applied a structured research methodology to identify and validate 4 agile values for breast cancer treatment. In the elicitation phase, through 2 interviews, we identified 4 agile values and described them in language that resonates with breast cancer treatment professionals. The values were then validated by a domain expert and discussed in the context of supporting work from the literature. Final validation entailed a domain expert conducting a walkthrough of the 4 identified agile values to adjust them as per the reported literature.

RESULTS

Four agile values were identified for breast cancer treatment, and among them, we validated 3 that conformed to the concept of agility. The fourth value, documentation and the quality of documentation, is vital for breast cancer treatment planning and management. This does not conform to agility. However, its nonagility is vital for the agility of the other values. None of the identified agile values were validated as partially conforming to the concept of agility.

CONCLUSIONS

This work makes a novel contribution to knowledge in identifying the first set of agile values in breast cancer treatment through multidisciplinary research. Three of these values were evaluated as conforming to the concept of agility, and although 1 value did not meet the concept of agility, it enhanced the agility of the other values. It is anticipated that these 4 agile values can drive oncology practice, strategies, policies, protocols, and procedures to enhance delivery of care. Moreover, the identified values contribute to identifying quality assurance and control practices to assess the concept of agility in oncology practice and breast cancer treatment and adjust corresponding actions. We conclude that breast cancer treatment agile values are not limited to 4.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR1-10.2196/53124.

Assessment of Suspected Breast Lesions in Early-Stage Triple-Negative Breast Cancer during Follow-Up after Breast-Conserving Surgery Using Multiparametric MRI

Background

The local recurrence rate of triple-negative breast cancer (TNBC) can be as high as 12%.The standard treatment for early-stage TNBC is breast-conserving surgery (BCS), followed by postoperative radiotherapy with or without chemotherapy. However, detection of the local recurrence of the disease after radiotherapy is a major issue.

Objective

The aim of this study was at investigating the role of dynamic and functional magnetic resonance imaging (MRI) during follow-up after BCS and radiotherapy with/without chemotherapy to differentiate between locoregional recurrence and postoperative fibrosis. Patients and Methods. This prospective study was conducted at the oncology, radiology, and pathology departments, Tanta University. It involved 50 patients with early-stage TNBC who were treated with BCS, followed by radiotherapy with/without chemotherapy. The suspected lesions were evaluated during the follow-up period by sonomammography. All patients were subjected to MRI, including conventional sequences, diffusion-weighted imaging (DWI), and dynamic postcontrast study.

Results

Ten cases were confirmed as recurrent malignant lesions. After contrast administration, they all exhibited irregular T1 hypodense lesions of variable morphology with diffusion restriction and positive enhancement. Eight cases displayed a type III curve, while two showed a type II curve. Histopathological assessment was consistent with the MRI findings in all eight cases. The combination of the data produced by DWI-MRI and dynamic contrast-enhanced (DCE) MRI resulted in 100%sensitivity, 92.5% specificity, 90.9% positive predictive value, 100% negative predictive value, and 98% accuracy.

Conclusion

Combination of DWI-MRI and DCE-MRI could have high diagnostic value for evaluating postoperative changes in patients with TNBC after BCS, followed by radiotherapy with/without chemotherapy. Trial Registrations. No trial to be registered.

Predicting pathologic response to neoadjuvant chemotherapy in patients with locally advanced breast cancer using multiparametric MRI

Background

This study aims to observe and analyze the effect of diffusion weighted magnetic resonance imaging (MRI) on the patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy.

Methods

Fifty patients (mean age, 48.7 years) with stage II–III breast cancer who underwent neoadjuvant chemotherapy and preoperative MRI between 2016 and 2020 were retrospectively evaluated. The associations between preoperative breast MRI findings/clinicopathological features and outcomes of neoadjuvant chemotherapy were assessed.

Results

Clinical stage at baseline (OR: 0.104, 95% confidence interval (CI) 0.021–0.516, P = 0.006) and standard apparent diffusion coefficient (ADC) change (OR: 9.865, 95% CI 1.024–95.021, P = 0.048) were significant predictive factors of the effects of neoadjuvant chemotherapy. The percentage increase of standard ADC value in pathologic complete response (pCR) group was larger than that in non-pCR group at first time point (P < 0.05). A correlation was observed between the change in standard ADC values and tumor diameter at first follow-up (r: 0.438, P < 0.05).

Conclusions

Our findings support that change in standard ADC values and clinical stage at baseline can predict the effects of neoadjuvant chemotherapy for patients with breast cancer in early stage.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12880-021-00688-z.

The Role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Predicting Treatment Response for Cervical Cancer Treated with Concurrent Chemoradiotherapy

Purpose

To evaluate the role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting early treatment response.

Materials and Methods

Patients with locally advanced cervical cancer (LACC) treated with concurrent chemoradiotherapy (CCRT) were enrolled. Pelvic DCE-MRI scans were performed before RT (pre-RT), in the middle of RT (mid-RT), and at the end of RT (post-RT), separately. Parameters (ie, K^trans, K_ep, and V_e) were measured. Pre-, mid-, and post-RT K^trans were denoted as K^trans-preTx, K^trans-midTx, and K^trans-postTx, respectively. And the same denoting rule also went for K_ep and V_e. Difference for the same parameter such as K^trans measured between two consecutive time points was calculated as second K^trans value minus first K^trans value. The differences in K^trans between pre-RT and post-RT, between pre-RT and mid-RT, and between mid-RT and post-RT were denoted as ΔK^trans-post-preTx, ΔK^trans-mid-preTx, and ΔK^trans-post-midTx, respectively, and the same denoting rule was also applied to K_ep and V_e.

Results

A total of 57 patients were enrolled. After the treatment, 31 patients had complete response (CR group). The remaining 26 patients had partial response (NCR group). Significant differences were found in K^trans-postTx, K_ep-postTx, V_e-midTx, ΔK^trans-post-preTx, ΔK^trans-post-midTx, ΔK_ep-post-preTx, ΔK_ep-mid-preTx and ΔK_ep-post-midTx between the two groups. Receiver operating characteristic (ROC) analysis for their performances in predicting treatment response showed an area under curve (AUC) of 0.656-0.849, sensitivity of 61.3-93.5%, specificity of 46.1-73.1%, and maximal Youden Index of 36.5-66.6. Among those parameters, K_ep-postTx was the best, and its AUC, sensitivity, specificity, maximal Youden Index, and cutoff value were 0.849, 87.1%, 73.1%, 60.2, and 0.341, respectively. These combined parameters showed an AUC of 0.952, with sensitivity of 87.1%, specificity of 96.1%, and maximal Youden Index of 83.2.

Conclusion

DCE-MRI parameters can predict early treatment outcome. Among those parameters, K_ep-postTx is the best predictor. The combination of multi-parameters can increase the predictive potency.

Noninvasive assessment and therapeutic monitoring of drug-resistant colorectal cancer by MR molecular imaging of extradomain-B fibronectin

Antineoplastic resistance represents a multifaceted challenge for cancer therapy and diagnostics. Extensive molecular heterogeneity, even within neoplasms of the same type, can elicit distinct outcomes of administering therapeutic pressures, frequently leading to the development of drug-resistant populations. Improved success of oncotherapies merits the exploration of precise molecular imaging technologies that can detect not only anatomical but also molecular changes in tumors and their microenvironment, early on in the treatment regimen. To this end, we developed magnetic resonance molecular imaging (MRMI) strategies to target the extracellular matrix oncoprotein, extradomain-B fibronectin (EDB-FN), for non-invasive assessment and therapeutic monitoring of drug-resistant colorectal cancer (CRC). Methods: Two drug-resistant CRC lines generated from parent DLD-1 and RKO cells by long-term treatment with 5'-FU and 5'-FU plus CB-839 respectively, were characterized for functional and gene expression changes using 3D culture, transwell invasion, qRT-PCR, and western blot assays. Contrast-enhanced MRMI of EDB-FN was performed in athymic nu/nu mice bearing subcutaneous tumor xenografts with 40 µmol/kg dose of macrocyclic ZD2-targeted contrast agent MT218 [ZD2-N3-Gd (HP-DO3A)] on a 3T MRS 3000 scanner. Immunohistochemistry was conducted on patient specimens and xenografts using anti-EDB-FN antibody G4. Results: Analyses of TCGA and GTEx databases revealed poor prognosis of colon cancer patients with higher levels of EDB-FN. Similarly, immunohistochemical staining of patient specimens showed increased EDB-FN expression in primary colon adenocarcinoma and hepatic metastases, but none in normal adjacent tissues. Drug-resistant DLD1-DR and RKO-DR cells were also found to demonstrate enhanced invasive potential and significantly elevated EDB-FN expression over their parent counterparts. MRMI of EDB-FN with 40 µmol/kg dose of MT218 (60% lower than the clinical dose) resulted in robust signal enhancement in the drug-resistant CRC xenografts with 84-120% increase in their contrast-to-noise ratios (CNRs) over the non-resistant counterparts. The feasibility of non-invasive therapeutic monitoring using MRMI of EDB-FN was also evaluated in drug-resistant DLD1-DR tumors treated with a pan-AKT inhibitor MK2206-HCl. The treated drug-resistant tumors failed to respond to therapy, which was accurately detected by MRMI with MT218, demonstrating higher signal enhancement and increased CNRs in the 4-week follow-up scans over the pre-treatment scans. Conclusions: EDB-FN is a promising molecular marker for assessing drug resistance. MRMI of EDB-FN with MT218 at a significantly reduced dose can facilitate effective non-invasive assessment and treatment response monitoring of drug-resistant CRC, highlighting its translational potential for active surveillance and management of CRC and other malignancies.

Diffuse optical spectroscopic imaging reveals distinct early breast tumor hemodynamic responses to metronomic and maximum tolerated dose regimens

Background

Breast cancer patients with early-stage disease are increasingly administered neoadjuvant chemotherapy (NAC) to downstage their tumors prior to surgery. In this setting, approximately 31% of patients fail to respond to therapy. This demonstrates the need for techniques capable of providing personalized feedback about treatment response at the earliest stages of therapy to identify patients likely to benefit from changing treatment. Diffuse optical spectroscopic imaging (DOSI) has emerged as a promising functional imaging technique for NAC monitoring. DOSI uses non-ionizing near-infrared light to provide non-invasive measures of absolute concentrations of tissue chromophores such as oxyhemoglobin. In 2011, we reported a new DOSI prognostic marker, oxyhemoglobin flare: a transient increase in oxyhemoglobin capable of discriminating NAC responders within the first day of treatment. In this follow-up study, DOSI was used to confirm the presence of the flare as well as to investigate whether DOSI markers of NAC response are regimen dependent.

Methods

This dual-center study examined 54 breast tumors receiving NAC measured with DOSI before therapy and the first week following chemotherapy administration. Patients were treated with either a standard of care maximum tolerated dose (MTD) regimen or an investigational metronomic (MET) regimen. Changes in tumor chromophores were tracked throughout the first week and compared to pathologic response and treatment regimen at specific days utilizing generalized estimating equations (GEE).

Results

Within patients receiving MTD therapy, the oxyhemoglobin flare was confirmed as a prognostic DOSI marker for response appearing as soon as day 1 with post hoc GEE analysis demonstrating a difference of 48.77% between responders and non-responders (p < 0.0001). Flare was not observed in patients receiving MET therapy. Within all responding patients, the specific treatment was a significant predictor of day 1 changes in oxyhemoglobin, showing a difference of 39.45% (p = 0.0010) between patients receiving MTD and MET regimens.

Conclusions

DOSI optical biomarkers are differentially sensitive to MTD and MET regimens at early timepoints suggesting the specific treatment regimen should be considered in future DOSI studies. Additionally, DOSI may help to identify regimen-specific responses in a more personalized manner, potentially providing critical feedback necessary to implement adaptive changes to the treatment strategy.

Preoperative indication for systemic therapy extended to patients with early-stage breast cancer using multiparametric 7-tesla breast MRI

Purpose

To establish a preoperative decision model for accurate indication of systemic therapy in early-stage breast cancer using multiparametric MRI at 7-tesla field strength.

Materials and methods

Patients eligible for breast-conserving therapy were consecutively included. Patients underwent conventional diagnostic workup and one preoperative multiparametric 7-tesla breast MRI. The postoperative (gold standard) indication for systemic therapy was established from resected tumor and lymph-node tissue, based on 10-year risk-estimates of breast cancer mortality and relapse using Adjuvant! Online. Preoperative indication was estimated using similar guidelines, but from conventional diagnostic workup. Agreement was established between preoperative and postoperative indication, and MRI-characteristics used to improve agreement. MRI-characteristics included phospomonoester/phosphodiester (PME/PDE) ratio on 31-phosphorus spectroscopy (³¹P-MRS), apparent diffusion coefficients on diffusion-weighted imaging, and tumor size on dynamic contrast-enhanced (DCE)-MRI. A decision model was built to estimate the postoperative indication from preoperatively available data.

Results

We included 46 women (age: 43-74yrs) with 48 invasive carcinomas. Postoperatively, 20 patients (43%) had positive, and 26 patients (57%) negative indication for systemic therapy. Using conventional workup, positive preoperative indication agreed excellently with positive postoperative indication (N = 8/8; 100%). Negative preoperative indication was correct in only 26/38 (68%) patients. However, ³¹P-MRS score (p = 0.030) and tumor size (p = 0.002) were associated with the postoperative indication. The decision model shows that negative indication is correct in 21/22 (96%) patients when exempting tumors larger than 2.0cm on DCE-MRI or with PME>PDE ratios at ³¹P-MRS.

Conclusions

Preoperatively, positive indication for systemic therapy is highly accurate. Negative indication is highly accurate (96%) for tumors sized ≤2,0cm on DCE-MRI and with PME≤PDE ratios on ³¹P-MRS.

Role of quantitative magnetic resonance imaging parameters in the evaluation of treatment response in malignant tumors

OBJECTIVE

To elaborate the role of quantitative magnetic resonance imaging (MRI) parameters in the evaluation of treatment response in malignant tumors.

DATA SOURCES

Data cited in this review were obtained mainly from PubMed in English from 1999 to 2014, with keywords "dynamic contrast-enhanced (DCE)-MRI," "diffusion-weighted imaging (DWI)," "microcirculation," "apparent diffusion coefficient (ADC)," "treatment response" and "oncology."

STUDY SELECTION

Articles regarding principles of DCE-MRI, principles of DWI, clinical applications as well as opportunity and aspiration were identified, retrieved and reviewed.

RESULTS

A significant correlation between ADC values and treatment response was reported in most DWI studies. Most quantitative DCE-MRI studies showed a significant correlation between K trans values and treatment response. However, in different tumors and studies, both high and low pretreatment ADC or K trans values were found to be associated with response rate. Both DCE-MRI and DWI demonstrated changes in their parameters hours to days after treatment, showing a decrease in K trans or an increase in ADC associated with response in most cases.

CONCLUSIONS

Combinations of quantitative MRI play an important role in the evaluation of treatment response of malignant tumors and hold promise for use as a cancer treatment response biomarker. However, validation is hampered by the lack of reproducibility and standardization. MRI acquisition protocols and quantitative image analysis approaches should be properly addressed prior to further testing the clinical use of quantitative MRI parameters in the assessment of treatments.

Breast DCE-MRI Kinetic Heterogeneity Tumor Markers: Preliminary Associations With Neoadjuvant Chemotherapy Response

The ability to predict response to neoadjuvant chemotherapy for women diagnosed with breast cancer, either before or early on in treatment, is critical to judicious patient selection and tailoring the treatment regimen. In this paper, we investigate the role of contrast agent kinetic heterogeneity features derived from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting treatment response. We propose a set of kinetic statistic descriptors and present preliminary results showing the discriminatory capacity of the proposed descriptors for predicting complete and non-complete responders as assessed from pre-treatment imaging exams. The study population consisted of 15 participants: 8 complete responders and 7 non-complete responders. Using the proposed kinetic features, we trained a leave-one-out logistic regression classifier that performs with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.84 under the ROC. We compare the predictive value of our features against commonly used MRI features including kinetics of the characteristic kinetic curve (CKC), maximum peak enhancement (MPE), hotspot signal enhancement ratio (SER), and longest tumor diameter that give lower AUCs of 0.71, 0.66, 0.64, and 0.54, respectively. Our proposed kinetic statistics thus outperform the conventional kinetic descriptors as well as the classifier using a combination of all the conventional descriptors (i.e., CKC, MPE, SER, and longest diameter), which gives an AUC of 0.74. These findings suggest that heterogeneity-based DCE-MRI kinetic statistics could serve as potential imaging biomarkers for tumor characterization and could be used to improve candidate patient selection even before the start of the neoadjuvant treatment.

The Impact of Flip Angle and TR on the Enhancement Ratio of Dynamic Gadobutrol-enhanced MR Imaging: In Vivo VX2 Tumor Model and Computer Simulation

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used to diagnose cancer and monitor therapy. The maximum enhancement ratio (ERmax) obtained from the curve of signal intensity over time could be a biomarker to distinguish cancer from normal tissue or benign tumors. We evaluated the impact of flip angle (FA) and repetition time (TR) on the ERmax values of dynamic gadobutrol-enhanced MR imaging, obtaining T1-weighted (T1W) MR imaging of VX2 tumors using 2-dimensional fast spoiled gradient echo (2D FSPGR) with various FAs (30°, 60° and 90°) at 1.5 tesla before and after injection of 0.1 mmol/kg gadobutrol. In vivo study indicated significant differences between ERmax values and area under the ER-time curve (AUC100) of VX2 tumors and muscle tissue, with the highest ERmax and AUC100 at FA 90°. Computer simulation also demonstrated the ER as a strictly increasing monotonic function in the closed interval [0°, 90°] for a given TR when using T1W FSPGR, and the highest ER value always occurred at FA 90°. The FA for the highest ER differed from that for the highest signal-to-noise or contrast-to-noise ratio. For long TR, the ER value increases gradually. However, for short TR, the ER value increases rapidly and plateaus so that the ER value changes little beyond a certain FA value. Therefore, we suggest use of a higher FA, near 90°, to obtain a higher ERmax for long TR in 2D SPGR or FSPGR and a smaller FA, much less than 90°, to reach an appropriate ERmax for short TR in 3D SPGR or FSPGR. This information could be helpful in setting the optimal parameters for DCE-MRI.

Flexible, 31-Channel breast coil for enhanced parallel imaging performance at 3T

PURPOSE

To design, build, and characterize the performance of a novel 3T, 31-channel breast coil.

METHODS

A flexible breast coil, accommodating all breast sizes while preserving close to unity filling factors in all configurations, was designed and built. Its performance was compared to the performance of the current state-of-the-art, 16 channel breast coil (Sentinelle coil, Hologic, Bedford, MA, USA), in phantoms and in vivo.

RESULTS

Better axilla coverage and lower inter-coil coupling (12% versus 26%, as characterized by the average off-diagonal elements of the noise correlation matrix) was exhibited by our 31-channel coil compared with the 16-channel coil. Breast area signal-to-noise ratio increases of 68% (phantom) and 28% ± 31% (in vivo) were observed when the 31-channel coil was used. For the 31-channel/16-channel arrays, respectively, two-dimensional acceleration factors of left/right × superior/inferior = 4.3 × 2.4 resulted in average g-factors of 1.10/1.68 (in vitro) and 1.28/2.75 (in vivo); acceleration factors of left/right × anterior/posterior = 3.0 × 2.8 resulted in average g-factors of 1.06/1.54 (in vitro) and 1.05/1.12 (in vivo).

CONCLUSION

A high performance breast coil was built; its capabilities were demonstrated in phantom and normal volunteer imaging experiments.

Deformable registration for quantifying longitudinal tumor changes during neoadjuvant chemotherapy

PURPOSE

To evaluate DRAMMS, an attribute-based deformable registration algorithm, compared to other intensity-based algorithms, for longitudinal breast MRI registration, and to show its applicability in quantifying tumor changes over the course of neoadjuvant chemotherapy.

METHODS

Breast magnetic resonance images from 14 women undergoing neoadjuvant chemotherapy were analyzed. The accuracy of DRAMMS versus five intensity-based deformable registration methods was evaluated based on 2,380 landmarks independently annotated by two experts, for the entire image volume, different image subregions, and patient subgroups. The registration method with the smallest landmark error was used to quantify tumor changes, by calculating the Jacobian determinant maps of the registration deformation.

RESULTS

DRAMMS had the smallest landmark errors (6.05 ± 4.86 mm), followed by the intensity-based methods CC-FFD (8.07 ± 3.86 mm), NMI-FFD (8.21 ± 3.81 mm), SSD-FFD (9.46 ± 4.55 mm), Demons (10.76 ± 6.01 mm), and Diffeomorphic Demons (10.82 ± 6.11 mm). Results show that registration accuracy also depends on tumor versus normal tissue regions and different patient subgroups.

CONCLUSIONS

The DRAMMS deformable registration method, driven by attribute-matching and mutual-saliency, can register longitudinal breast magnetic resonance images with a higher accuracy than several intensity-matching methods included in this article. As such, it could be valuable for more accurately quantifying heterogeneous tumor changes as a marker of response to treatment.

MRI of breast tumor initiating cells using the extra domain-B of fibronectin targeting nanoparticles

The identification of breast tumor initiating cells (BTICs) is important for the diagnosis and therapy of breast cancers. This study was undertaken to evaluate whether the extra domain-B of fibronectin (EDB-FN) could be used as a new biomarker for BTICs and whether EDB-FN targeting superparamagnetic iron oxide nanoparticles (SPIONs) could be used as a magnetic resonance imaging (MRI) contrast agent for BTIC imaging in vitro and in vivo. BTICs (NDY-1) exhibited high EDB-FN expression, whereas non-BTICs (MCF-7, BT-474, SUM-225, MDA-MB-231) did not exhibit EDB-FN expression. Furthermore, Cy3.3-labeled EDB-FN specific peptides (APTEDB) showed preferential binding to the targeted NDY-1 cells. To construct an EDB-FN targeted imaging probe, APTEDB was covalently attached to a thermally cross-linked SPION (TCL-SPION) to yield APTEDB-TCL-SPION. In the in vitro MRI of cell phantoms, selective binding of APTEDB-TCL-SPION to NDY-1 cells was evident, but little binding was observed in MCF-7 cells. After the intravenous injection of APTEDB-TCL-SPION into the NDY-1 mouse tumor xenograft model, a significant decrease in the signal within the tumor was observed in the T2*-weighted images; however, there was only a marginal change in the signal of non-targeting SPIONs such as APTscramble-TCL-SPION or TCL-SPION. Taken together, we report for the first time that EDB-FN was abundantly expressed in BTICs and may therefore be useful as a new biomarker for identifying BTICs. Our study also suggests that APTEDB-TCL-SPION could be used as an MRI contrast agent for BTIC imaging.

Identification of intrinsic imaging phenotypes for breast cancer tumors: preliminary associations with gene expression profiles

PURPOSE

To present a method for identifying intrinsic imaging phenotypes in breast cancer tumors and to investigate their association with prognostic gene expression profiles.

MATERIALS AND METHODS

The authors retrospectively analyzed dynamic contrast material-enhanced (DCE) magnetic resonance (MR) images of the breast in 56 women (mean age, 55.6 years; age range, 37-74 years) diagnosed with estrogen receptor-positive breast cancer between 2005 and 2010. The study was approved by the institutional review board and compliant with HIPAA. The requirement to obtain informed consent was waived. Primary tumors were assayed with a validated gene expression assay that provides a score for the likelihood of recurrence. A multiparametric imaging phenotype vector was extracted for each tumor by using quantitative morphologic, kinetic, and spatial heterogeneity features. Multivariate linear regression was performed to test associations between DCE MR imaging features and recurrence likelihood. To identify intrinsic imaging phenotypes, hierarchical clustering was performed on the extracted feature vectors. Multivariate logistic regression was used to classify tumors at high versus low or medium risk of recurrence. To determine the additional value of intrinsic phenotypes, the phenotype category was tested as an additional variable. Receiver operating characteristic analysis and the area under the receiver operating characteristic curve (Az) were used to assess classification performance.

RESULTS

There was a moderate correlation (r = 0.71, R(2) = 0.50, P < .001) between DCE MR imaging features and the recurrence score. DCE MR imaging features were predictive of recurrence risk as determined by the surrogate assay, with an Az of 0.77 (P < .01). Four dominant imaging phenotypes were detected, with two including only low- and medium-risk tumors. When the phenotype category was used as an additional variable, the Az increased to 0.82 (P < .01).

CONCLUSION

Intrinsic imaging phenotypes exist for breast cancer tumors and correlate with recurrence likelihood as determined with gene expression profiling. These imaging biomarkers could ultimately help guide treatment decisions.

Meta-analysis of agreement between MRI and pathologic breast tumour size after neoadjuvant chemotherapy

BACKGROUND

Magnetic resonance imaging (MRI) has been proposed to guide breast cancer surgery by measuring residual tumour after neoadjuvant chemotherapy. This study-level meta-analysis examines MRI's agreement with pathology, compares MRI with alternative tests and investigates consistency between different measures of agreement.

METHODS

A systematic literature search was undertaken. Mean differences (MDs) in tumour size between MRI or comparator tests and pathology were pooled by assuming a fixed effect. Limits of agreement (LOA) were estimated from a pooled variance by assuming equal variance of the differences across studies.

RESULTS

Data were extracted from 19 studies (958 patients). The pooled MD between MRI and pathology from six studies was 0.1 cm (95% LOA: -4.2 to 4.4 cm). Similar overestimation for MRI (MD: 0.1 cm) and ultrasound (US) (MD: 0.1 cm) was observed, with comparable LOA (two studies). Overestimation was lower for MRI (MD: 0.1 cm) than mammography (MD: 0.4 cm; two studies). Overestimation by MRI (MD: 0.1 cm) was smaller than underestimation by clinical examination (MD: -0.3 cm). The LOA for mammography and clinical examination were wider than that for MRI. Percentage agreement between MRI and pathology was greater than that of comparator tests (six studies). The range of Pearson's/Spearman's correlations was wide (0.21-0.92; 16 studies). Inconsistencies between MDs, percentage agreement and correlations were common.

CONCLUSION

Magnetic resonance imaging appears to slightly overestimate pathologic size, but measurement errors may be large enough to be clinically significant. Comparable performance by US was observed, but agreement with pathology was poorer for mammography and clinical examination. Percentage agreement can provide supplementary information to MDs and LOA, but Pearson's/Spearman's correlation does not provide evidence of agreement and should be avoided. Further comparisons of MRI and other tests using the recommended methods are warranted.

Noninvasive identification of viable cell populations in docetaxel-treated breast tumors using ferritin-based magnetic resonance imaging

Background

Cancer stem cells (CSCs) are highly tumorigenic and are responsible for tumor progression and chemoresistance. Noninvasive imaging methods for the visualization of CSC populations within tumors in vivo will have a considerable impact on the development of new CSC-targeting therapeutics.

Methodology/Principal Findings

In this study, human breast cancer stem cells (BCSCs) transduced with dual reporter genes (human ferritin heavy chain [FTH] and enhanced green fluorescence protein [EGFP]) were transplanted into NOD/SCID mice to allow noninvasive tracking of BCSC-derived populations. No changes in the properties of the BCSCs were observed due to ferritin overexpression. Magnetic resonance imaging (MRI) revealed significantly different signal intensities (R₂* values) between BCSCs and FTH-BCSCs in vitro and in vivo. In addition, distinct populations of pixels with high R₂* values were detected in docetaxel-treated FTH-BCSC tumors compared with control tumors, even before the tumor sizes changed. Histological analysis revealed that areas showing high R₂* values in docetaxel-treated FTH-BCSC tumors by MRI contained EGFP+/FTH+ viable cell populations with high percentages of CD44+/CD24− cells.

Conclusions/Significance

These findings suggest that ferritin-based MRI, which provides high spatial resolution and tissue contrast, can be used as a reliable method to identify viable cell populations derived from BCSCs after chemotherapy and may serve as a new tool to monitor the efficacy of CSC-targeting therapies in vivo.

Pre-treatment differences and early response monitoring of neoadjuvant chemotherapy in breast cancer patients using magnetic resonance imaging: a systematic review

OBJECTIVES

To assess whether magnetic resonance imaging (MRI) can identify pre-treatment differences or monitor early response in breast cancer patients receiving neoadjuvant chemotherapy.

METHODS

PubMed, Cochrane library, Medline and Embase databases were searched for publications until January 1, 2012. After primary selection, studies were selected based on predefined inclusion/exclusion criteria. Two reviewers assessed study contents using an extraction form.

RESULTS

In 15 studies, which were mainly underpowered and of heterogeneous study design, 31 different parameters were studied. Most frequently studied parameters were tumour diameter or volume, K(trans), K(ep), V(e), and apparent diffusion coefficient (ADC). Other parameters were analysed in only two or less studies. Tumour diameter, volume, and kinetic parameters did not show any pre-treatment differences between responders and non-responders. In two studies, pre-treatment differences in ADC were observed between study groups. At early response monitoring significant and non-significant changes for all parameters were observed for most of the imaging parameters.

CONCLUSIONS

Evidence on distinguishing responders and non-responders to neoadjuvant chemotherapy using pre-treatment MRI, as well as using MRI for early response monitoring, is weak and based on underpowered study results and heterogeneous study design. Thus, the value of breast MRI for response evaluation has not yet been established.

KEY POINTS

Few well-validated pre-treatment MR parameters exist that identify responders and non-responders. Eligible studies showed heterogeneous study designs which hampered pooling of data. Confounders and technical variations of MRI accuracy are not studied adequately. Value of MRI for response evaluation needs to be established further.

Promise and pitfalls of quantitative imaging in oncology clinical trials

Quantitative imaging using computed tomography, magnetic resonance imaging and positron emission tomography modalities will play an increasingly important role in the design of oncology trials addressing molecularly targeted, personalized therapies. The advent of molecularly targeted therapies, exemplified by antiangiogenic drugs, creates new complexities in the assessment of response. The Quantitative Imaging Network addresses the need for imaging modalities which can accurately and reproducibly measure not just change in tumor size but changes in relevant metabolic parameters, modulation of relevant signaling pathways, drug delivery to tumor and differentiation of apoptotic cell death from other changes in tumor volume. This article provides an overview of the applications of quantitative imaging to phase 0 through phase 3 oncology trials. We describe the use of a range of quantitative imaging modalities in specific tumor types including malignant gliomas, lung cancer, head and neck cancer, lymphoma, breast cancer, prostate cancer and sarcoma. In the concluding section, we discuss potential constraints on clinical trials using quantitative imaging, including complexity of trial conduct, impact on subject recruitment, incremental costs and institutional barriers. Strategies for overcoming these constraints are presented.

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.