Role of apparent diffusion coefficient values for the differentiation of viable and necrotic areas of breast cancer and its potential utility to guide voxel positioning for MRS in the absence of dynamic contrast-enhanced MRI data

A Brief Review on Breast Carcinoma and Deliberation on Current Non Invasive Imaging Techniques for Detection

BACKGROUND

Breast carcinoma is a life threatening disease that accounts for 25.1% of all carcinoma among women worldwide. Early detection of the disease enhances the chance for survival.

DISCUSSION

This paper presents comprehensive report on breast carcinoma disease and its modalities available for detection and diagnosis, as it delves into the screening and detection modalities with special focus placed on the non-invasive techniques and its recent advancement work done, as well as a proposal on a novel method for the application of early breast carcinoma detection.

CONCLUSION

This paper aims to serve as a foundation guidance for the reader to attain bird's eye understanding on breast carcinoma disease and its current non-invasive modalities.

Application of in vivo MR methods in the study of breast cancer metabolism

In the last two decades, various in vivo MR methodologies have been evaluated for their potential in the study of cancer metabolism. During malignant transformation, metabolic alterations occur, leading to morphological and functional changes. Among various MR methods, in vivo MRS has been extensively used in breast cancer to study the metabolism of cells, tissues or whole organs. It provides biochemical information at the metabolite level. Altered choline, phospholipid and energy metabolism has been documented using proton (¹ H), phosphorus (³¹ P) and carbon (¹³ C) isotopes. Increased levels of choline-containing compounds, phosphomonoesters and phosphodiesters in breast cancer, which are indicative of altered choline and phospholipid metabolism, have been reported using in vivo, in vitro and ex vivo NMR studies. These changes are reversed on successful therapy, which depends on the treatment regimen given. Monitoring the various tumor intermediary metabolic pathways using nuclear spin hyperpolarization of ¹³ C-labeled substrates by dynamic nuclear polarization has also been recently reported. Furthermore, the utility of various methods such as diffusion, dynamic contrast and perfusion MRI have also been evaluated to study breast tumor metabolism. Parameters such as tumor volume, apparent diffusion coefficient, volume transfer coefficient and extracellular volume ratio are estimated. These parameters provide information on the changes in tumor microstructure, microenvironment, abnormal vasculature, permeability and grade of the tumor. Such changes seen during cancer progression are due to alterations in the tumor metabolism, leading to changes in cell architecture. Due to architectural changes, the tissue mechanical properties are altered; this can be studied using magnetic resonance elastography, which measures the elastic properties of tissues. Moreover, these structural MRI methods can be used to investigate the effect of therapy-induced changes in tumor characteristics. This review discusses the potential of various in vivo MR methodologies in the study of breast cancer metabolism.

Direct Regularization From Co-Registered Contrast MRI Improves Image Quality of MRI-Guided Near-Infrared Spectral Tomography of Breast Lesions

An approach using direct regularization from co-registered dynamic contrast enhanced magnetic reson- ance images was used to reconstruct near-infrared spectral tomography patient images, which does not need image segmentation. 20 patients with mammography/ultrasound confirmed breast abnormalities were involved in this paper, and the resulting images indicated that tumor total hemoglobin concentration contrast differentiated malignant from benign cases (p-value = 0.021). The approach prod- uced reconstructed images, which significantly reduced surface artifacts near the source-detector locations (p-value = 4.16e-6).

Combining multiparametric MRI with receptor information to optimize prediction of pathologic response to neoadjuvant therapy in breast cancer: preliminary results

Pathologic complete response following neoadjuvant therapy (NAT) is used as a short-term surrogate marker of eventual outcome in patients with breast cancer. Analyzing voxel-level heterogeneity in MRI-derived parametric maps, obtained before and after the first cycle of NAT ([Formula: see text]), in conjunction with receptor status, may improve the predictive accuracy of tumor response to NAT. Toward that end, we incorporated two MRI-derived parameters, the apparent diffusion coefficient and efflux rate constant, with receptor status in a logistic ridge-regression model. The area under the curve (AUC) and Brier score of the model computed via 10-fold cross validation were 0.94 (95% CI: 0.85, 0.99) and 0.11 (95% CI: 0.06, 0.16), respectively. These two statistics strongly support the hypothesis that our proposed model outperforms the other models that we investigated (namely, models without either receptor information or voxel-level information). The contribution of the receptor information was manifested by an 8% to 15% increase in AUC and a 14% to 21% decrease in Brier score. These data indicate that combining multiparametric MRI with hormone receptor status has a high likelihood of improved prediction of pathologic response to NAT in breast cancer.

Pre-operative assessment of residual disease in locally advanced breast cancer patients: A sequential study by quantitative diffusion weighted MRI as a function of therapy

PURPOSE

The potential of diffusion weighted imaging (DWI) in assessing pathologic response and surgical margins in locally advanced breast cancer patients (n=38) undergoing neoadjuvant chemotherapy was investigated.

METHODS

DWI was performed at pre-therapy (Tp0), after I (Tp1) and III (Tp3) NACT at 1.5T. Apparent diffusion coefficient (ADC) of whole tumor (ADC_WT), solid tumor (ADC_ST), intra-tumoral necrosis (ADC_Nec) was determined. Further, ADC of 6 consecutive shells (5mm thickness each) including tumor margin to outside tumor margins (OM1 to OM5) was calculated and the data analyzed to define surgical margins.

RESULTS

Of 38 patients, 6 were pathological complete responders (pCR), 19 partial responders (pPR) and 13 were non-responders (pNR). Significant increase was observed in ADC_ST and ADC_WT in pCR and pPR following therapy. Pre-therapy ADC was significantly lower in pCR compared to pPR and pNR indicating the heterogeneous nature of tumor which may affect drug perfusion and consequently the response. ADC of outside margins (OM1, OM2, and OM3) was significantly different among pCR, pPR and pNR at Tp3 which may serve as response predictive parameter. Further, at Tp3, ADC of outside margins (OM1, OM2, and OM3) was significantly lower compared to that seen at Tp0 in pCR, indicating the presence of residual disease in these shells.

CONCLUSION

Pre-surgery information may serve as a guide to define cancer free margins and the extent of residual disease which may be useful in planning breast conservation surgery.

Is there an association between enhanced choline and β-catenin pathway in breast cancer? A pilot study by MR Spectroscopy and ELISA

Total choline (tCho) was documented as a biomarker for breast cancer diagnosis by in vivo MRS. To understand the molecular mechanisms behind elevated tCho in breast cancer, an association of tCho with β-catenin and cyclin D1 was evaluated. Hundred fractions from 20 malignant, 10 benign and 20 non-involved breast tissues were isolated. Cytosolic and nuclear expressions of β-catenin and cyclin D1 were estimated using ELISA. Higher tCho was seen in malignant compared to benign tissues. Malignant tissues showed higher cytosolic and nuclear β-catenin expressions than benign and non-involved tissues. Within malignant tissues, β-catenin and cyclin D1 expressions were higher in the nucleus than cytosol. Cyclin D1 expression was higher in the cytosolic fractions of benign and non-involved than malignant tissues. Furthermore, in malignant tissues, tCho showed a positive correlation with the cytosolic and nuclear expression of β-catenin and cyclin D1 and also a correlation between nuclear expressions of both these proteins was seen. Higher cytosolic β-catenin expression was seen in progesterone receptor negative than positive patients. Results provide an evidence of correlation between non-invasive biomarker, tCho and the Wnt/β-catenin pathway. The findings explain the molecular mechanism of tCho elevation which may facilitate exploration of additional therapeutic targets for breast cancer.

Evaluating the diagnostic sensitivity of computed diffusion-weighted MR imaging in the detection of breast cancer

PURPOSE

To evaluate the diagnostic sensitivity of computed diffusion-weighted (DW)-MR imaging for the detection of breast cancer.

MATERIALS AND METHODS

Local research ethics approval was obtained. A total of 61 women (median 48 years) underwent dynamic contrast enhanced (DCE)- and DW-MR between January 2011 and March 2012, including 27 with breast cancer on core biopsy and 34 normal cases. Standard ADC maps using all four b values (0, 350, 700, 1150) were used to generate computed DW-MR images at b = 1500 s/mm(2) and b = 2000 s/mm(2) . Four image sets were read sequentially by two readers: acquired b = 1150 s/mm(2) , computed b = 1500 s/mm(2) and b = 2000 s/mm(2) , and DCE-MR at an early time point. Cancer detection was rated using a five-point scale; image quality and background suppression were rated using a four-point scale. The diagnostic sensitivity for breast cancer detection was compared using the McNemar test and inter-reader agreement with a Kappa value.

RESULTS

Computed DW-MR resulted in higher overall diagnostic sensitivity with b = 2000 s/mm(2) having a mean diagnostic sensitivity of 76% (range 49.8-93.7%) and b = 1500 s/mm(2) having a mean diagnostic sensitivity of 70.3% (range 32-97.7%) compared with 44.4% (range 25.5-64.7%) for acquired b = 1150 s/mm(2) (both p = 0.0001). Computed DW-MR images produced better image quality and background suppression (mean scores for both readers: 2.55 and 2.9 for b 1500 s/mm(2) ; 2.55 and 3.15 for b 2000 s/mm(2) , respectively) than the acquired b value 1150 s/mm(2) images (mean scores for both readers: 2.4 and 2.45, respectively).

CONCLUSION

Computed DW-MR imaging has the potential to improve the diagnostic sensitivity of breast cancer detection compared to acquired DW-MR. J. Magn. Reson. Imaging 2016;44:130-137.

Potential of Diffusion-Weighted Imaging in the Characterization of Malignant, Benign, and Healthy Breast Tissues and Molecular Subtypes of Breast Cancer

The role of apparent diffusion coefficient (ADC) in the diagnosis of breast cancer and its association with molecular biomarkers was investigated in 259 patients with breast cancer, 67 with benign pathology, and 54 healthy volunteers using diffusion-weighted imaging (DWI) at 1.5 T. In 59 breast cancer patients, dynamic contrast-enhanced MRI (DCEMRI) was also acquired. Mean ADC of malignant lesions was significantly lower (1.02 ± 0.17 × 10⁻³ mm²/s) compared to benign (1.57 ± 0.26 × 10⁻³ mm²/s) and healthy (1.78 ± 0.13 × 10⁻³ mm²/s) breast tissues. A cutoff ADC value of 1.23 × 10⁻³ mm²/s (sensitivity 92.5%; specificity 91.1%; area under the curve 0.96) to differentiate malignant from benign diseases was arrived by receiver operating curve analysis. In 10/59 breast cancer patients, indeterminate DCE curve was seen, while their ADC value was indicative of malignancy, implying the potential of the addition of DWI in increasing the specificity of DCEMRI data. Further, the association of ADC with tumor volume, stage, hormonal receptors [estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor (HER2)], and menopausal status was investigated. A significant difference was seen in tumor volume between breast cancer patients of stages IIA and IIIA, IIB and IIIA, and IIB and III (B + C), respectively (P < 0.05). Patients with early breast cancer (n = 52) had significantly lower ADC and tumor volume than those with locally advanced breast cancer (n = 207). No association was found in ADC and tumor volume with the menopausal status. Breast cancers with ER−, PR−, and triple-negative (TN) status showed a significantly larger tumor volume compared to ER+, PR+, and non-triple-negative (nTN) cancers, respectively. Also, TN tumors showed a significantly higher ADC compared to ER+, PR+, and nTN cancers. Patients with ER− and TN cancers were younger than those with ER+ and nTN cancers. The present study demonstrated that ADC may increase the diagnostic specificity of DCEMRI and be useful for treatment management in clinical setting. Additionally, it provides an insight into characterization of molecular types of breast cancer and may serve as an indicator of metabolic reprograming underlying tumor proliferation.

Significance of the ADC ratio in the differential diagnosis of breast lesions

BACKGROUND

Magnetic resonance imaging (MRI) has high sensitivity but low specificity for breast cancer, and consequently, new techniques to improve the specificity of breast MRI in diagnosing breast cancer are under development.

PURPOSE

To assess the ability of the apparent diffusion coefficient (ADC) compared with the ADC ratio (ADCr) to differentially diagnose benign compared with malignant breast lesions.

MATERIAL AND METHODS

Forty-eight women with breast lesions (average age, 45 years) underwent MRI scanning including T1-weighted dynamic contrast-enhanced (DCE) scanning and diffusion-weighted imaging (DWI). The average ADC and ADCr values for both lesions and pectoralis major muscles (ADCrmuscle and ADCrmuscle) were measured in patients with malignant (n = 25) and benign (n = 23) breast lesions. The ADCr of the contralateral breast (ADCr contralateral) was also evaluated. All histology was confirmed by pathological analysis of biopsied tissue. ADC and ADCr values were analyzed using receiver-operating characteristic (ROC) curves.

RESULTS

For benign lesions compared with malignant lesions, lesion-side ADC was 1.45 vs. 1.05, respectively (P < 0.001), normal-side ADC was 1.82 vs.1.64 (P = 0.002), ADCrmuscle was 1.35 vs. 0.9 (P < 0.001), and ADCrcontralateral was 0.79 vs. 0.64 (P = 0.001). ADCrmuscle showed higher sensitivity (82.61%) and specificity (96.00%) than ADCrcontralateral (60.87% and 92.00%, respectively) and ADC (69.57% and 96.00%) for discriminating malignant from benign lesions. The AUC using ADCrmuscle had higher discriminatory power (0.92, P < 0.001) for malignant versus benign breast lesions compared with either ADC (0.82, P < 0.001) or ADCrcontralateral (0.78, P = 0.001).

CONCLUSION

The ADCrmuscle value showed higher sensitivity and specificity and improved diagnostic accuracy compared with either ADC or ADCrcontralateral in differentiating benign from malignant breast lesions.

Quantitative correlation at the molecular level of tumor response to docetaxel by multimodal diffusion-weighted magnetic resonance imaging and [¹⁸F]FDG/[¹⁸F]FLT positron emission tomography

We aimed to quantitatively characterize the treatment effects of docetaxel in the HCT116 xenograft mouse model, applying diffusion-weighted magnetic resonance imaging (MRI) and positron emission tomography (PET) using 2-deoxy-2-[¹⁸F]fluoro-d-glucose ([¹⁸F]FDG) and 3'-deoxy-3'-[¹⁸F]-fluorothymidine ([¹⁸F]FLT). Mice were imaged at four time points over 8 days. Docetaxel (15 mg/kg) was administered after a baseline scan. Voxel-wise scatterplots of PET and apparent diffusion coefficient (ADC) data of tumor volumes were evaluated with a threshold cluster analysis and compared to histology (GLUT1, GLUT3, Ki67, activated caspase 3a). Compared to the extensive tumor growth observed in the vehicle-treated group (from 0.32 ± 0.21 cm³ to 0.69 ± 0.40 cm³), the administration of docetaxel led to tumor growth stasis (from 0.32 ± 0.20 cm³ to 0.45 ± 0.23 cm³). The [¹⁸F]FDG/ADC cluster analysis and the evaluation of peak histogram values revealed a significant treatment effect matching histology as opposed to [¹⁸F]FLT/ADC. [¹⁸F]FLT uptake and the Ki67 index were not in good agreement. Our voxel-based cluster analysis uncovered treatment effects not seen in the separate inspection of PET and MRI data and may be used as an independent analysis tool. [¹⁸F]FLT/ADC cluster analysis could still point out the treatment effect; however, [¹⁸F]FDG/ADC reflected the histology findings in higher agreement.

[Diffusion-weighted breast imaging. Clinical implementation procedure]

Diffusion-weighted imaging (DWI) of the breast provides additional contrast information in breast magnetic resonance imaging (MRI). The DWI procedure can easily be implemented in the routine breast MRI protocol with little time expenditure regarding image acquisition and evaluation. Evaluation of the DW images can be performed with or without the routine breast MRI sequences (T2w and T1w with contrast material) but evaluation in combination with the routine program is highly recommended. Objective analysis of the tissue diffusion can be achieved by calculating the apparent diffusion coefficient (ADC) value with the scanner software. The choice of the DW sequence, evaluation and determination of the ADC threshold to differentiate between benign and malignant lesions should be scanner adapted. The use of DW imaging qualifies for routine use regarding the differentiation between malignant and benign breast lesions. Non-mass-like lesions and monitoring neoadjuvant chemotherapy can also be evaluated with DW sequences. The benefit of the additional information from DW-MR mammography to characterize non-mass-like lesions and in the course of neoadjuvant chemotherapy remains unclear to date.

Proof-of-the-Concept Study on Mathematically Optimized Magnetic Resonance Spectroscopy for Breast Cancer Diagnostics

Magnetic resonance (MR)-based modalities aid breast cancer detection without exposure to ionizing radiation. Magnetic resonance imaging is very sensitive but costly and insufficiently specific. Molecular imaging through magnetic resonance spectroscopy (MRS) can provide information about key metabolites. Here, the measured/encoded time signals cannot be interpreted directly, necessitating mathematics for mapping to the more manageable frequency domain. Conventional applications of MRS are hampered by data analysis via the fast Fourier transform (FFT) and postprocessing by fitting techniques. Most in vivo MRS studies on breast cancer rely upon estimations of total choline (tCHO). These have yielded only incremental improvements in diagnostic accuracy. In vitro studies reveal richer metabolic information for identifying breast cancer, particularly in closely overlapping components of tCHO. Among these are phosphocholine (PC), a marker of malignant transformation of the breast. The FFT cannot assess these congested spectral components. This can be done by the fast Padé transform (FPT), a high-resolution, quantification-equipped method, which we presently apply to noisy MRS time signals consistent with those encoded in breast cancer. The FPT unequivocally and robustly extracted the concentrations of all physical metabolites, including PC. In sharp contrast, the FFT produced a rough envelope spectrum with a few distorted peaks and key metabolites absent altogether. As such, the FFT has poor resolution for these typical MRS time signals from breast cancer. Hence, based on Fourier-estimated envelope spectra, tCHO estimates are unreliable. Using even truncated time signals, the FPT clearly distinguishes noise from true metabolites whose concentrations are accurately extracted. The high resolution of the FPT translates directly into shortened examination time of the patient. These capabilities strongly suggest that by applying the FPT to time signals encoded in vivo from the breast, MRS will, at last, fulfill its potential to become a clinically reliable, cost-effective method for breast cancer detection, including screening/surveillance.

Diffusion-weighted imaging of the high-risk breast: Apparent diffusion coefficient values and their relationship to breast density

PURPOSE

To document the apparent diffusion coefficient (ADC) of fibroglandular breast tissue in women at high-risk of developing breast cancer and investigate the relationship between ADC and breast density.

MATERIALS AND METHODS

Local research ethics approval was obtained. A total of 33 high-risk women including 17 BRCA1/2 mutation carriers (mean age, 43 years) and 16 women postmantle irradiation (mean age 40 years) underwent diffusion-weighted MRI between days 6 and 16 of their menstrual cycle. ADC histograms from a region of interest in fibroglandular tissue and mammographic breast density measurements were obtained. Mean, percentile ADC values (10th, 25th, 50th, 75th, 90th) and skew were compared for the two groups; ADC and mammographic breast density were correlated.

RESULTS

Mean ADC values (×10(-6) mm(2) /s) were 2017 ± 197 in postmantle irradiated women and 1827 ± 289 in BRCA1/2 mutation carriers (P = 0.035) with significant differences at all percentiles (P < 0.0001) but not skew (P = 0.44). ADC values showed weak positive correlation with mammographic breast density in BRCA1/2 mutation carriers (r = 0.51, P = 0.043) but not in postmantle radiotherapy patients (r = 0.49, P = 0.13).

CONCLUSION

Higher ADC values seen in fibroglandular tissue postmantle irradiation compared with BRCA1/2 mutation carriers has potential to improve tumor detection in these patients. Lack of correlation between ADC and breast density postmantle irradiation may be a result of microstructural changes.

Characterization of malignant breast tissue of breast cancer patients and the normal breast tissue of healthy lactating women volunteers using diffusion MRI and in vivo 1H MR spectroscopy

PURPOSE

To investigate the potential of diffusion weighted imaging (DWI) and in vivo proton MR spectroscopy (MRS) in the differentiation of breast tissue of healthy lactating women volunteers and breast cancer patients.

MATERIALS AND METHODS

DWI and MRS were carried out at 1.5 Tesla on 12 breast cancer patients and 12 normal lactating women volunteers. Apparent diffusion coefficient (ADC) and total choline (tCho) concentration were determined.

RESULTS

tCho was observed in all breast cancer patients and in 10/12 lactating women. Additionally a peak at 3.8 ppm corresponding to lactose was seen in 10/12 of lactating women. Concentration of tCho was similar in malignant breast tissue of patients (3.51 ± 1.72 mmol/kg) and in normal breast tissue of lactating women (3.52 ± 1.70 mmol/kg). However, ADC was significantly higher in the normal breast tissue of lactating women (1.62 ± 0.22 × 10(-3) mm(2)/s) compared with the malignant breast tissue of patients (1.01 ± 0.10 × 10(-3) mm(2)/s).

CONCLUSION

Observation of lactose peak with higher ADC in the breast tissue of healthy lactating women volunteers may aid in differentiation of changes that occur in breast tissue due to normal physiological conditions like lactation compared with malignant transformation.

Texture-based and diffusion-weighted discrimination of parotid gland lesions on MR images at 3.0 Tesla

The purpose of this study was to evaluate whether texture-based analysis of standard MRI sequences and diffusion-weighted imaging can help in the discrimination of parotid gland masses. The MR images of 38 patients with a biopsy- or surgery-proven parotid gland mass were retrospectively analyzed. All patients were examined on the same 3.0 Tesla MR unit, with one standard protocol. The ADC (apparent diffusion coefficient) values of the tumors were measured with three regions of interest (ROIs) covering the entire tumor. Texture-based analysis was performed with the texture analysis software MaZda (version 4.7), with ROI measurements covering the entire tumor in three slices. COC (co-occurrence matrix), RUN (run-length matrix), GRA (gradient), ARM (auto-regressive model), and WAV (wavelet transform) features were calculated for all ROIs. Three subsets of 10 texture features each were used for a linear discriminant analysis (LDA) in combination with k nearest neighbor classification (k-NN). Using histology as a standard of reference, benign tumors, including subtypes, and malignant tumors were compared with regard to ADC and texture-based values, with a one-way analysis of variance with post-hoc t-tests. Significant differences were found in the mean ADC values between Warthin tumors and pleomorphic adenomas, as well as between Warthin tumors and benign lesions. Contrast-enhanced T1-weighted images contained the most relevant textural information for the discrimination between benign and malignant parotid masses, and also for the discrimination between pleomorphic adenomas and Warthin tumors. STIR images contained the least relevant texture features, particularly for the discrimination between pleomorphic adenomas and Warthin tumors. Texture analysis proved to differentiate benign from malignant lesions, as well as pleomorphic adenomas from Warthin tumors, based on standard T(1w) sequences (without and with contrast). Of all benign parotid masses, Warthin tumors had significantly lower ADC values than the other entities.

Magnetic resonance in the detection of breast cancers of different histological types

Breast cancer incidence is increasing worldwide. Early detection is critical for long-term patient survival, as is monitoring responses to chemotherapy for management of the disease. Magnetic resonance imaging and spectroscopy (MRI/MRS) has gained in importance in the last decade for the diagnosis and monitoring of breast cancer therapy. The sensitivity of MRI/MRS for anatomical delineation is very high and the consensus is that MRI is more sensitive in detection than x-ray mammography. Advantages of MRS include delivery of biochemical information about tumor metabolism, which can potentially assist in the staging of cancers and monitoring responses to treatment. The roles of MRS and MRI in screening and monitoring responses to treatment of breast cancer are reviewed here. We rationalize how it is that different histological types of breast cancer are differentially detected and characterized by MR methods.