Variation of breast vascular maps on dynamic contrast-enhanced MRI after primary chemotherapy of locally advanced breast cancer

Predictive value of dynamic contrast-enhanced breast magnetic resonance imaging and diffusion-weighted imaging findings for sentinel lymph node metastasis in early-stage invasive breast cancer

OBJECTIVES

This retrospective study aimed to evaluate the predictive value of the preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) findings of mass lesions for predicting sentinel lymph node (SLN) metastasis in early breast cancer.

METHODS

A total of 310 patients with suspicious mass lesions detected in preoperative MRI who subsequently underwent surgery and SLN biopsy (SLNB) between September 2015 and September 2022 were analysed. The relationship between DCE-MRI and DWI findings and SLNB positivity was analysed.

RESULTS

SLNB was positive for SLN metastasis in 108 of 310 lesions. Younger age (P = 0.001) and larger lesion size (P < 0.001) were found to be associated with SLNB positivity. Findings associated with SLN metastasis included peritumoural oedema in 53%, adjacent vessel sign (AVS) in 81%, and increased whole-breast vascularity (WBV) in 58% of patients with positive SLNB (P < 0.001). The SLNB positivity rate was higher in mass lesions with DCE-MRI findings of heterogenous enhancement pattern (P = 0.003), medium or rapid initial phase enhancement (P = 0.001), and washout delayed phase kinetic curve (P = 0.001). It was found that lower tumoural apparent diffusion coefficient (ADC) values (P = 0.003) and higher peritumoural/tumoural ADC ratios (P = 0.018) increased the probability of encountering SLN metastasis.

CONCLUSIONS

Patient age, presence of peritumoural oedema, presence of AVS, increased WBV, and initial phase kinetic curve of the lesions on MRI were found to be associated with SLN metastasis.

ADVANCES IN KNOWLEDGE

We found that younger age and MR findings obtained from the perilesional area of breast cancer may be helpful in the preoperative prediction of SLN metastasis.

Institutional Variability in Ultrafast Breast MR Imaging: Comparing Compressed Sensing and View Sharing Techniques with Different Patient Populations and Contrast Injection Protocols

PURPOSE

To assess the institutional variability in ultrafast dynamic contrast-enhanced (UF-DCE) breast MRI using time-resolved angiography with stochastic trajectories (TWIST)-volumetric interpolated breath-hold examination (VIBE) and compressed sensing (CS)-VIBE sequences acquired at 2 different institutions with different patient populations and contrast injection protocols.

METHODS

UF-DCE MR images of 18 patients from site A acquired using a TWIST-VIBE sequence, and UF-DCE MR images of 18 patients from site B acquired with a CS-VIBE sequence, were retrospectively evaluated and compared. The 2-site patient cohort was matched for patient age, background parenchymal enhancement, malignancy or benignity, and lesion size. Qualitative assessments included noise, blurring, poor fat suppression, aliasing artifact, motion artifact, lesion conspicuity, lesion morphology, time-intensity-curve smoothness, and vessel delineation. For quantitative assessment, the bolus arrival time was evaluated for each lesion, and its diagnostic performance in discriminating between benign and malignant lesions was examined using receiver operating characteristics analysis.

RESULTS

Thirteen malignant and five benign lesions were included from each site. Qualitative evaluation revealed that poor fat suppression and aliasing artifacts were visible in images from site A with TWIST-VIBE (P = 0.004 and P < 0.001), whereas motion artifacts were present in images from site B with CS-VIBE (P = 0.04). Lesion morphology assessments (P < 0.001) and vessel delineation (P < 0.001) were superior for images from site B with CS-VIBE. Bolus arrival time was significantly longer with TWIST-VIBE than with CS-VIBE, for both benign and malignant lesions (P < 0.001). The area under the receiver operating characteristics curve was 0.55 for site A and 0.69 for site B (P = 0.39).

CONCLUSION

Both acquisitions allowed evaluation of breast lesions with good lesion conspicuity and time-intensity-curve smoothness, whereas CS-VIBE was superior to TWIST-VIBE for morphological evaluation of breast lesions and depiction of blood vessels in the breast. Injection rate appears to have a significant impact on semi-quantitative parameters derived from UF-DCE MRI.

Development and validation of peritumoral vascular and intratumoral radiomics to predict pathologic complete responses to neoadjuvant chemotherapy in patients with triple-negative breast cancer

BACKGROUND

To develop and validate a peritumoral vascular and intratumoral radiomics model to improve pretreatment predictions for pathologic complete responses (pCRs) to neoadjuvant chemoradiotherapy (NAC) in patients with triple-negative breast cancer (TNBC).

METHODS

A total of 282 TNBC patients (93 in the primary cohort, 113 in the validation cohort, and 76 in The Cancer Imaging Archive [TCIA] cohort) were retrospectively included. The peritumoral vasculature on the maximum intensity projection (MIP) from pretreatment DCE-MRI was segmented by a Hessian matrix-based filter and then edited by a radiologist. Radiomics features were extracted from the tumor and peritumoral vasculature of the MIP images. The LASSO method was used for feature selection, and the k-nearest neighbor (k-NN) classifier was trained and validated to build a predictive model. The diagnostic performance was assessed using the ROC analysis.

RESULTS

One hundred of the 282 patient (35.5%) with TNBC achieved pCRs after NAC. In predicting pCRs, the combined peritumoral vascular and intratumoral model (fusion model) yields a maximum AUC of 0.82 (95% confidence interval [CI]: 0.75, 0.88) in the primary cohort, a maximum AUC of 0.67 (95% CI: 0.57, 0.76) in the internal validation cohort, and a maximum AUC of 0.65 (95% CI: 0.52, 0.78) in TCIA cohort. The fusion model showed improved performance over the intratumoral model and the peritumoral vascular model, but not significantly (p > 0.05).

CONCLUSION

This study suggested that combined peritumoral vascular and intratumoral radiomics model could provide a non-invasive tool to enable prediction of pCR in TNBC patients treated with NAC.

Hypertrophic breasts versus normal-sized breasts: Comparison of blood supply to the nipple-areola complex based on DCE-MRI

BACKGROUND

Understanding the blood supply to the nipple-areola complex (NAC) in hypertrophic breasts is essential to reduce the risk of NAC necrosis during reduction mammaplasty. The aim of this study was to use dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to determine the NAC blood supply of hypertrophic breasts compared with normal-sized breasts.

METHODS

DCE-MRI images of 100 Asian women (100 hypertrophic breasts and 100 normal-sized breasts) were included retrospectively. All vessels supplying the NAC were identified using axial, coronal, and sagittal maximum-intensity projection images. The diameter, length, and distance to the skin surface of source vessels were measured.

RESULTS

The number of source vessels in the hypertrophic breasts was larger than that in the normal-sized breasts. 97.0% of hypertrophic breasts had multizone blood supply to the NAC. In hypertrophic and normal-sized breasts, the proportion of vessels was highest in the supermedial zone, followed by the superolateral zone and central zone. The diameter of medial and lateral vessels was significantly increased in hypertrophic breasts. Besides, the length of source vessels in hypertrophic breasts was larger than that in normal-sized breasts.

CONCLUSIONS

Hypertrophic breasts tend to have a richer blood supply to the NAC than normal-sized breasts. The predominant vessels supplying the NAC of hypertrophic breasts are the superomedial, followed by the superolateral and central.

LEVEL OF EVIDENCE

IV.

The potential of predictive and prognostic breast MRI (P2-bMRI)

Magnetic resonance imaging (MRI) is an important part of breast cancer diagnosis and multimodal workup. It provides unsurpassed soft tissue contrast to analyse the underlying pathophysiology, and it is adopted for a variety of clinical indications. Predictive and prognostic breast MRI (P2-bMRI) is an emerging application next to these indications. The general objective of P2-bMRI is to provide predictive and/or prognostic biomarkers in order to support personalisation of breast cancer treatment. We believe P2-bMRI has a great clinical potential, thanks to the in vivo examination of the whole tumour and of the surrounding tissue, establishing a link between pathophysiology and response to therapy (prediction) as well as patient outcome (prognostication). The tools used for P2-bMRI cover a wide spectrum: standard and advanced multiparametric pulse sequences; structured reporting criteria (for instance BI-RADS descriptors); artificial intelligence methods, including machine learning (with emphasis on radiomics data analysis); and deep learning that have shown compelling potential for this purpose. P2-bMRI reuses the imaging data of examinations performed in the current practice. Accordingly, P2-bMRI could optimise clinical workflow, enabling cost savings and ultimately improving personalisation of treatment. This review introduces the concept of P2-bMRI, focusing on the clinical application of P2-bMRI by using semantic criteria.

Optical Imaging of the Breast: Basic Principles and Clinical Applications

OBJECTIVE

The objective of this article is to summarize the physical principles, technology features, and first clinical applications of optical imaging techniques to the breast.

CONCLUSION

Light-breast tissue interaction is expressed as absorption and scattering coefficients, allowing image reconstruction based on endogenous or exogenous contrast. Diffuse optical spectroscopy and imaging, fluorescence molecular tomography, photoacoustic imaging, and multiparametric infrared imaging show potential for clinical application, especially for lesion characterization, estimation of cancer probability, and monitoring the effect of neoadjuvant therapy.

Clinical Report on the First Prototype of a Photoacoustic Tomography System with Dual Illumination for Breast Cancer Imaging

Photoacoustic tomography is a recently developed imaging modality that can provide high spatial-resolution images of hemoglobin distribution in tissues such as the breast. Because breast cancer is an angiogenesis-dependent type of malignancy, we evaluated the clinical acceptability of breast tissue images produced using our first prototype photoacoustic mammography (PAM) system in patients with known cancer. Post-excisionally, histological sections of the tumors were stained immunohistochemically (IHC) for CD31 (an endothelial marker) and carbonic anhydrase IX (CAIX) (a marker of hypoxia). Whole-slide scanning and image analyses were used to evaluate the tumor microvessel distribution pattern and to calculate the total vascular perimeter (TVP)/area for each lesion. In this clinical study, 42 lesions were primarily scanned using PAM preoperatively, three of which were reported to be benign and were excluded from statistical analysis. Images were produced for 29 out of 39 cancers (visibility rate = 74.4%) at the median depth of 26.5 (3.25-51.2) mm. Age, menopausal status, body mass index, history of neoadjuvant treatment, clinical stage and histological tumor angiogenesis markers did not seem to affect the visibility. The oxygen saturation level in all of the measured lesions was lower than in the subcutaneous counterpart vessels (Wilcoxon test, p value<0.001), as well as in the counterpart contralateral normal breast region of interest (ROI) (Wilcoxon test, p value = 0.001). Although the oxygen saturation level was not statistically significant between CAIX-positive vs. -negative cases, lesional TVP/area showed a positive correlation with the oxygen saturation level only in the group that had received therapy before PAM. In conclusion, the vascular and oxygenation data obtained by PAM have great potential for identifying functional features of breast tumors.

Evaluation of the treatment response to neoadjuvant chemotherapy in locally advanced breast cancer using combined magnetic resonance vascular maps and apparent diffusion coefficient

PURPOSE

To evaluate the treatment response of locally advanced breast cancer (LABC) to neoadjuvant chemotherapy using magnetic resonance (MR) vascular maps and apparent diffusion coefficient (ADC) at 3T. Materials and Methods Thirty-one patients with LABC who underwent breast MR studies before, after the first course, and after completing neoadjuvant chemotherapy were enrolled. Vascular morphology was retrieved via Hessian matrix and the voxels of the vessels and volume of vessels were measured automatically. Whole tumor mean ADC values were calculated. Clinical responders were defined as >50% tumor reduction in the final MR studies. Pathologically complete responders were also recorded.

RESULTS

There were 21 clinical responders and 10 nonresponders. Compared to the nonresponders after the first course, the responders were characterized by more vascular reduction of the breast lesion and decreased bilateral vascular discrepancy (voxels and volume), and increments in the ADC value and ADC percentage of the lesions (all P < 0.05). There were three pathological complete responders who showed more apparent early vascular reduction of the lesion breast (voxels and volume) and increments in the ADC value than others (P = 0.02, 0.01 and 0.02, respectively).

CONCLUSION

The early changes of MR vascular maps and ADC are associated with the final treatment response of LABC.

A new algorithm for automatic vascular mapping of DCE-MRI of the breast: Clinical application of a potential new biomarker

BACKGROUND AND OBJECTIVE

Vascularity evaluation on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a potential diagnostic value, but it represents a time consuming procedure, affected by intra- and inter-observer variability. This study tests the application of a recently published method to reproducibly quantify breast vascularity, and evaluates if the vascular volume of cancer-bearing breast, calculated from automatic vascular maps (AVMs), may correlate with pathologic tumor response after neoadjuvant chemotherapy (NAC).

METHODS

Twenty-four patients with unilateral locally advanced breast cancer underwent DCE-MRI before and after NAC, 8 responders and 16 non-responders. A validated algorithm, based on multiscale 3D Hessian matrix analysis, provided AVMs and allowed the calculation of vessel volume before the initiation and after the last NAC cycle for each breast. For cancer bearing breast, the difference in vascular volume before and after NAC was compared in responders and non-responders using the Wilcoxon two-sample test. A radiologist evaluated the vascularity on the subtracted images (first enhanced minus unenhanced), before and after treatment, assigning a vascular score for each breast, according to the number of vessels with length ≥30mm and maximal transverse diameter ≥2mm. The same evaluation was repeated with the support of the simultaneous visualization of the AVMs. The two evaluations were compared in terms of mean number of vessels and mean vascular score per breast, in responders and non-responders, by use of Wilcoxon two sample test. For all the analysis, the statistical significance level was set at 0.05.

RESULTS

For breasts harboring the cancer, evidence of a difference in vascular volume before and after NAC for responders (median=1.71cc) and non-responders (median=0.41cc) was found (p=0.003). A significant difference was also found in the number of vessels (p=0.03) and vascular score (p=0.02) before or after NAC, according to the evaluation supported by the AVMs.

CONCLUSIONS

The encouraging, although preliminary, results of this study suggest the use of AVMs as new biomarker to evaluate the pathologic response after NAC, but also support their application in other breast DCE-MRI vessel analysis that are waiting for a reliable quantification method.

Tumor microvasculature characteristics studied by image analysis: histologically-driven angiogenic profile

Angiogenesis, a hallmark of cancer, has been studied to be a potential marker for diagnosis, prognosis and therapy in breast cancer. To evaluate tumor angiogenesis, histological assessment has been a common approach and counting tumor microvessels after visualizing them by immunohistochemistry has been in use for a long time. With recent advances in digital pathology and image analysis, other characteristics of tumor vasculature can also be evaluated. In this article we briefly review the potentials of image analysis in assessing tumor microvessel morphologically that might be helpful in defining a better angiogenesis marker than other common markers like vessel count.

A fully automatic multiscale 3-dimensional Hessian-based algorithm for vessel detection in breast DCE-MRI

OBJECTIVES

The objectives of this study were to develop a fully automatic method for detecting blood vessels in dynamic contrast-enhanced magnetic resonance imaging of the breast on the basis of a multiscale 3-dimensional Hessian-based algorithm and to evaluate the improvement in reducing the number of vessel voxels incorrectly classified as parenchymal lesions by a computer-aided diagnosis (CAD) system.

MATERIALS AND METHODS

The algorithm has been conceived to work on images obtained with different sequences, different acquisition parameters, such as the use of fat-saturation, and different contrast agents. The analysis was performed on 28 dynamic contrast-enhanced magnetic resonance imaging examinations, with 39 malignant (28 principal and 11 satellite) and 8 benign lesions, acquired at 2 centers using 2 different 1.5-T magnetic resonance scanners, radiofrequency coils, and contrast agents (14 studies from group A and 14 studies from group B). The method consists of 2 main steps: (a) the detection of linear structures on 3-dimensional images, with a multiscale analysis based on the second-order image derivatives and (b) the exclusion of non-vessel enhancements based on their morphological properties through the evaluation of the covariance matrix eigenvalues. To evaluate the algorithm performances, the identified vessels were converted into a 2-dimensional vasculature skeleton and then compared with manual tracking performed by an expert radiologist. When assessing the outcome of the algorithm performances in identifying vascular structures, the following terms must be considered: the correct-detection rate refers to pixels identified by both the algorithm and the radiologist, the missed-detection rate refers to pixels detected only by the radiologist, and the incorrect-detection rate refers to pixels detected only by the algorithm. The Wilcoxon rank sum test was used to assess differences between the performances of the 2 subgroups of images obtained from the different scanners.

RESULTS

For the testing set, which is composed of 28 patients from 2 different clinical centers, the median correct-detection rate was 89.1%, the median missed-detection rate was 10.9%, and the median incorrect-detection rate was 27.1%. The difference between group A and group B was not significant (P > 0.25). The exclusion of vascular voxels from the lesion detection map of a CAD system leads to a reduction of 68.4% (30.0%) (mean [SD]) of the total number of false-positives because of vessels, without a significant difference between the 2 subgroups (P = 0.50).

CONCLUSIONS

The system showed promising results in detecting most vessels identified by an expert radiologist on both fat-saturated and non-fat-saturated images obtained from different scanners with variable temporal and spatial resolutions and types of contrast agent. Moreover, the algorithm may reduce the labeling of vascular voxels as parenchymal lesions by a CAD system for breast magnetic resonance imaging, improving the CAD specificity and, consequently, further stimulating the use of CAD systems in clinical workflow.

A novel functional infrared imaging system coupled with multiparametric computerised analysis for risk assessment of breast cancer

OBJECTIVE

We evaluated a functional three-dimensional (3D) infrared imaging system (3DIRI) coupled with multiparametric computer analysis for risk assessment of breast cancer. The technique provides objective risk assessment for the presence of a malignant tumour based on automated parameters derived from a clinically known training set.

METHODS

Following institutional review board approval, we recruited 434 women for this prospective multicentre trial, including 256 healthy woman undergoing routine screening mammography with BI-RADS-1 results and 178 women with newly diagnosed breast cancer. This was a two-phase study: an initial training and calibration phase, followed by a two-armed blinded evaluation phase (52 healthy and 66 with breast cancer). 3DIRI data sets were acquired using a non-contact, no radiation system.

RESULTS

The sensitivity and specificity of functional infrared imaging in providing the correct risk for the presence of breast cancer were 90.9 % and 72.5 %, respectively. The area under the ROC curve was 86 %. Forty-two of the 60 (70 %) cancers in women correctly classified by the system as suspicious were smaller than 20 mm in size.

CONCLUSION

The preliminary blinded results of this novel technology show sufficient performance of functional infrared imaging in providing risk assessment for breast cancer to warrant further clinical studies.

KEY POINTS

• 3D functional infrared imaging (3DIRI) provides new metabolic signatures from breast lesions. • 3DIRI offers high sensitivity for risk assessment of breast cancer. • It also has reasonable specificity. • This initial experience warrants further evaluation in larger clinical trials.

Volumetric contrast-enhanced ultrasound imaging to assess early response to apoptosis-inducing anti-death receptor 5 antibody therapy in a breast cancer animal model

OBJECTIVES

The objective of this study was to determine whether volumetric contrast-enhanced ultrasound (US) imaging could detect early tumor response to anti-death receptor 5 antibody (TRA-8) therapy alone or in combination with chemotherapy in a preclinical triple-negative breast cancer animal model.

METHODS

Animal experiments had Institutional Animal Care and Use Committee approval. Thirty breast tumor-bearing mice were administered Abraxane (paclitaxel; Celgene Corporation, Summit, NJ), TRA-8, TRA-8 + Abraxane, or saline as a controlon days 0, 3, 7, 10, 14, and 17. Volumetric contrast-enhanced US imaging was performedon days 0, 1, 3, and 7 before dosing. Changes in parametric maps of tumor perfusion were compared with the tumor volume and immunohistologic findings.

RESULTS

Therapeutic efficacy was detected within 7 days after drug administration using parametric volumetric contrast-enhanced US imaging. Decreased tumor perfusion was observed in both the TRA-8-alone- and TRA-8 + Abraxane-dosed animals compared to control tumors (P = .17; P = .001, respectively). The reduction in perfusion observed in the TRA-8 + Abraxane group was matched with a corresponding regression in tumor size over the same period. Survival curves illustrate that the combination of TRA-8 + Abraxane improves drug efficacy compared to the same drugs administered alone. Immunohistologic analysis revealed increased levels of apoptotic activity in the TRA-8-dosed tumors, confirming enhanced antitumor effects.

CONCLUSIONS

Preliminary results are encouraging, and volumetric contrast-enhanced US-based tumor perfusion imaging may prove clinically feasible for detecting and monitoring the early antitumor effects in response to combination TRA-8 + Abraxane therapy.

A paradigm shift in tumour response evaluation of targeted therapy: the assessment of novel drugs in exploratory clinical trials

PURPOSE OF REVIEW

To describe the difficulty in assessing the biological activity of a novel agent in phase II trials.

RECENT FINDINGS

Two major fields of research provide interesting new potential endpoints: endpoints based on new imaging techniques (e.g. PET or spectral imaging that explore tumour metabolism, dynamic contrast enhanced (DCE) ultrasonography or DCE-MRI that explore tumour vascularization and tumour growth inhibition) and endpoints integrating assessment of tumour burden across time, such as the growth modulation index.

SUMMARY

Most of the recently described techniques appear attractive, but require formal validation.