Apparent Diffusion Coefficient in Invasive Ductal Breast Carcinoma: Correlation with Detailed Histologic Features and the Enhancement Ratio on Dynamic Contrast-Enhanced MR Images

Relationship Between Metabolic Activity, Cellularity, Histopathological Features of Primary Tumors and Distant Metastatic Potential in Breast Cancer

Objectives

The aim of this study was to evaluate the relationship between the types of distant metastatic spread, histopathological features, and imaging features of primary tumor on positron emission tomography/magnetic resonance imaging (PET/MRI) for primary staging in newly diagnosed breast invasive ductal carcinoma (IDC) patients.

Methods

Data from 289 female patients were retrospectively evaluated. Maximum standardized uptake value, metabolic tumor volume (MTV), total lesion glycolysis (TLG), and minimum apparent diffusion coefficient (ADCmin) values of primary tumors were obtained from PET/MRI. The patients were grouped as non-metastatic, oligometastatic (1-5 metastatic lesions) and multimetastatic (>5 metastatic lesions) disease according to the number of distant metastases, and divided into two groups as isolated bone metastasis (IBM) and mixed/soft tissue metastasis (M-SM) groups according to the sites of metastatic spread.

Results

Metabolic parameters had higher values and ADCmin had lower values in the multimetastatic and oligometastatic groups than in the non-metastatic group. MTV was the only parameter that showed significant difference between the multimetastatic and oligometastatic groups. MTV and TLG were significantly higher in the M-SM group than in the IBM group. 18F-fluorodeoxyglucose PET parameters had significantly higher values in grade 3, hormone receptor negative, human epidermal growth factor receptor 2 positive, triple negative, and highly proliferative (Ki-67 ≥14%) tumors. The prediction models that included imaging parameters to predict the presence of distant metastasis had higher discriminatory powers than the prediction models that included only histopathological parameters.

Conclusion

Primary tumors with higher metabolic-glycolytic activity and higher cellularity were more aggressive and had higher metastatic potential in breast IDC. Compared with histopathological parameters alone, the combination of imaging parameters and histopathological features of primary tumors may help to better understand tumor biology and behavior.

Value of apparent diffusion coefficient factor in correlation with the molecular subtypes, tumor grade, and expression of Ki-67 in breast cancer

Background

Breast cancer is known to be the most common cancer in women; in the last decade, contrast-enhanced magnetic resonance imaging has become an important tool in the diagnosis of cancer breast. Numerous studies have analyzed associations between imaging and histopathological features as well as the proliferation potential of breast cancer. The purpose of this study was to evaluate the relationship between the apparent diffusion coefficient (ADC) and expression of Ki-67 as well as tumor molecular subtype in breast cancer.

Results

No significant difference between the mean ADC value of tumors of grade I, II, and III was found. However, there was a significant difference between the mean ADC value of tumors of molecular type A and molecular type B (P = 0.000), HER2 overexpression (P = 0.018), and TN (P = 0.000), respectively. However, there was no significant difference between molecular type B, HER2 overexpression and TN. Also, no significant difference was found between the Ki-67 value of tumors of grade I, II, and III. Yet there was a significant difference between the mean ADC value of tumors of molecular type A and molecular type B (P = 0.000), HER2 overexpression (P = 0.014), and TN (P = 0.000), respectively. However, there was no significant difference between molecular type B, HER2 overexpression, and TN.

Conclusions

There is a significant inverse correlation between ADC values and Ki-67 expression. DWI and Ki-67 could be a good discriminator between tumors of molecular subtype A from other subtypes, yet it did not show a correlation with the tumor grade.

On the Additional Information Provided by 3T-MRI ADC in Predicting Tumor Cellularity and Microscopic Behavior

BACKGROUND

to evaluate whether Apparent Diffusion Coefficient (ADC) values of invasive breast cancer, provided by 3T Diffusion Weighted-Images (DWI), may represent a non-invasive predictor of pathophysiologic tumor aggressiveness.

METHODS

100 Patients with histologically proven invasive breast cancers who underwent a 3T-MRI examination were included in the study. All MRI examinations included dynamic contrast-enhanced and DWI/ADC sequences. ADC value were calculated for each lesion. Tumor grade was determined according to the Nottingham Grading System, and immuno-histochemical analysis was performed to assess molecular receptors, cellularity rate, on both biopsy and surgical specimens, and proliferation rate (Ki-67 index). Spearman's Rho test was used to correlate ADC values with histological (grading, Ki-67 index and cellularity) and MRI features. ADC values were compared among the different grading (G1, G2, G3), Ki-67 (<20% and >20%) and cellularity groups (<50%, 50-70% and >70%), using Mann-Whitney and Kruskal-Wallis tests. ROC curves were performed to demonstrate the accuracy of the ADC values in predicting the grading, Ki-67 index and cellularity groups.

RESULTS

ADC values correlated significantly with grading, ER receptor status, Ki-67 index and cellularity rates. ADC values were significantly higher for G1 compared with G2 and for G1 compared with G3 and for Ki-67 < 20% than Ki-67 > 20%. The Kruskal-Wallis test showed that ADC values were significantly different among the three grading groups, the three biopsy cellularity groups and the three surgical cellularity groups. The best ROC curves were obtained for the G3 group (AUC of 0.720), for G2 + G3 (AUC of 0.835), for Ki-67 > 20% (AUC of 0.679) and for surgical cellularity rate > 70% (AUC of 0.805).

CONCLUSIONS

3T-DWI ADC is a direct predictor of cellular aggressiveness and proliferation in invasive breast carcinoma, and can be used as a supporting non-invasive factor to characterize macroscopic lesion behavior especially before surgery.

3T MRI-Radiomic Approach to Predict for Lymph Node Status in Breast Cancer Patients

Simple Summary

Breast cancer is the most common cancer in women worldwide. The axillary lymph node status is one of the main prognostic factors. Currently, the methods to define the lymph node status are invasive and not without sequelae (from biopsy to lymphadenectomy). Radiomics is a new tool, and highly varied, but with high potential that has already shown excellent results in numerous fields of application. In our study, we have developed a classifier validated on a relatively large number of patients, which is able to predict lymph node status using a combination of patients clinical features, primary breast cancer histological features and radiomics features based on 3 Tesla post contrast—MR images. This approach can accurately select breast cancer patients who may avoid unnecessary biopsy and lymphadenectomy in a non-invasive way.

Abstract

Background: axillary lymph node (LN) status is one of the main breast cancer prognostic factors and it is currently defined by invasive procedures. The aim of this study is to predict LN metastasis combining MRI radiomics features with primary breast tumor histological features and patients’ clinical data. Methods: 99 lesions on pre-treatment contrasted 3T-MRI (DCE). All patients had a histologically proven invasive breast cancer and defined LN status. Patients’ clinical data and tumor histological analysis were previously collected. For each tumor lesion, a semi-automatic segmentation was performed, using the second phase of DCE-MRI. Each segmentation was optimized using a convex-hull algorithm. In addition to the 14 semantics features and a feature ROI volume/convex-hull volume, 242 other quantitative features were extracted. A wrapper selection method selected the 15 most prognostic features (14 quantitative, 1 semantic), used to train the final learning model. The classifier used was the Random Forest. Results: the AUC-classifier was 0.856 (label = positive or negative). The contribution of each feature group was lower performance than the full signature. Conclusions: the combination of patient clinical, histological and radiomics features of primary breast cancer can accurately predict LN status in a non-invasive way.

Correlative study between ADC value and grading of invasive breast cancer

Background

Studying breast carcinoma is of great importance as it is the commonest female malignancy. Accurate preoperative assessment of disease characteristics and prognosis would be of great help in the diagnosis and treatment planning of breast cancer. The aim of this study was to evaluate the role of the apparent diffusion coefficient (ADC) value in detecting the grading of invasive breast carcinoma prior to management.

Results

There was a significant difference between the mean ADC value of tumors of grade I and III (p = 0.001) and between grade I and II (p = 0.002). However, there was no significant difference between grade II and III (p = 0.979). High ADC values were associated with low-grade tumors. The mean ADC value of 0.93 × 10–3 mm2/s showed sensitivity 98%, specificity 100%, PPV 100%, NPV 83.3%, accuracy 98.2%, AUC = 0.994, and 95% confidence interval of 0.978 to 1.000.

Conclusion

DWI is a contrast-free modality that allows for both morphological and quantitative analysis. ADC value may not be the proper modality to determine the prognosis of breast cancer due to overlap values, yet it could be a good discriminator between low- and high-grade tumors and hence predictor of breast cancer cells that would respond to chemotherapy.

Correlation of the tumour-stroma ratio with diffusion weighted MRI in rectal cancer

OBJECTIVE

This study evaluated the correlation between intratumoural stroma proportion, expressed as tumour-stroma ratio (TSR), and apparent diffusion coefficient (ADC) values in patients with rectal cancer.

METHODS

This multicentre retrospective study included all consecutive patients with rectal cancer, diagnostically confirmed by biopsy and MRI. The training cohort (LUMC, Netherlands) included 33 patients and the validation cohort (VHIO, Spain) 69 patients. Two observers measured the mean and minimum ADCs based on single-slice and whole-volume segmentations. The TSR was determined on diagnostic haematoxylin & eosin stained slides of rectal tumour biopsies. The correlation between TSR and ADC was assessed by Spearman correlation (r_s).

RESULTS

The ADC values between stroma-low and stroma-high tumours were not significantly different. Intra-class correlation (ICC) demonstrated a good level of agreement for the ADC measurements, ranging from 0.84-0.86 for single slice and 0.86-0.90 for the whole-volume protocol. No correlation was observed between the TSR and ADC values, with ADC_meanr_s= -0.162 (p= 0.38) and ADC_minr_s= 0.041 (p= 0.82) for the single-slice and r_s= -0.108 (p= 0.55) and r_s= 0.019 (p= 0.92) for the whole-volume measurements in the training cohort, respectively. Results from the validation cohort were consistent; ADC_meanr_s= -0.022 (p= 0.86) and ADC_minr_s = 0.049 (p= 0.69) for the single-slice and r_s= -0.064 (p= 0.59) and r_s= -0.063 (p= 0.61) for the whole-volume measurements.

CONCLUSIONS

Reproducibility of ADC values is good. Despite positive reports on the correlation between TSR and ADC values in other tumours, this could not be confirmed for rectal cancer.

Imaging diagnosis of metastatic breast cancer

Numerous imaging modalities may be used for the staging of women with advanced breast cancer. Although bone scintigraphy and multiplanar-CT are the most frequently used tests, others including PET, MRI and hybrid scans are also utilised, with no specific recommendations of which test should be preferentially used. We review the evidence behind the imaging modalities that characterise metastases in breast cancer and to update the evidence on comparative imaging accuracy.

Renal epithelioid angiomyolipoma: Incidence in a Japanese cohort and diagnostic utility of diffusion-weighted magnetic resonance imaging

OBJECTIVES

To show the epidemiological characteristics of epithelioid angiomyolipoma in a Japanese population, and to establish the preoperative diagnosis method of epithelioid angiomyolipoma.

METHODS

Among the 855 tumors of patients who underwent partial/radical nephrectomy or renal biopsy for presumed renal cell carcinoma between 2007 and 2018, 39 renal tumors were diagnosed as nonclassical angiomyolipoma, including epithelioid angiomyolipoma and fat-poor angiomyolipoma. We retrospectively evaluated the incidence of epithelioid angiomyolipoma. Furthermore, we analyzed computed tomography and magnetic resonance imaging results, including diffusion-weighted magnetic resonance imaging findings of epithelioid angiomyolipoma and fat-poor angiomyolipoma.

RESULTS

The incidence of epithelioid angiomyolipoma (n = 7) was 17.9% of surgically resected non-classical angiomyolipoma. The radiological appearance of epithelioid angiomyolipoma was hyperattenuating on unenhanced computed tomography images with iso or low intensity on T2-weighted magnetic resonance imaging. The mean apparent diffusion coefficient value of the solid component in epithelioid angiomyolipoma was significantly lower than that in fat-poor angiomyolipoma (median 0.79 × 10^-3 vs 1.07 × 10^-3 mm² /s, P = 0.0019).

CONCLUSIONS

The proportion of epithelioid angiomyolipoma in our Japanese cohort was equivalent to that of the reported series in the USA. The apparent diffusion coefficient value is potentially useful to differentiate between epithelioid angiomyolipoma and fat-poor angiomyolipoma. Further research is required to establish the imaging diagnostic criteria for epithelioid angiomyolipoma.

Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions

BACKGROUND

The purpose of the present meta-analysis was to provide evident data about use of Apparent Diffusion Coefficient (ADC) values for distinguishing malignant and benign breast lesions.

METHODS

MEDLINE library and SCOPUS database were screened for associations between ADC and malignancy/benignancy of breast lesions up to December 2018. Overall, 123 items were identified. The following data were extracted from the literature: authors, year of publication, study design, number of patients/lesions, lesion type, mean value and standard deviation of ADC, measure method, b values, and Tesla strength. The methodological quality of the 123 studies was checked according to the QUADAS-2 instrument. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance weights were used without any further correction to account for the heterogeneity between the studies. Mean ADC values including 95% confidence intervals were calculated separately for benign and malign lesions.

RESULTS

The acquired 123 studies comprised 13,847 breast lesions. Malignant lesions were diagnosed in 10,622 cases (76.7%) and benign lesions in 3225 cases (23.3%). The mean ADC value of the malignant lesions was 1.03 × 10^- 3 mm²/s and the mean value of the benign lesions was 1.5 × 10^- 3 mm²/s. The calculated ADC values of benign lesions were over the value of 1.00 × 10^- 3 mm²/s. This result was independent on Tesla strength, choice of b values, and measure methods (whole lesion measure vs estimation of ADC in a single area).

CONCLUSION

An ADC threshold of 1.00 × 10^- 3 mm²/s can be recommended for distinguishing breast cancers from benign lesions.

Diffusion-weighted imaging of the breast: current status as an imaging biomarker and future role

Diffusion-weighted imaging (DWI) of the breast is a MRI sequence that shows several advantages when compared to the dynamic contrast-enhanced sequence: it does not need intravenous contrast, it is relatively quick and easy to implement (artifacts notwithstanding). In this review, the current applications of DWI for lesion characterization and prognosis as well as for response evaluation are analyzed from the point of view of the necessary steps to become a useful surrogate of underlying biological processes (tissue architecture and cellularity): from the proof of concept, to the proof of mechanism, the proof of principle and finally the proof of effectiveness. Future applications of DWI in screening, DWI modeling and radiomics are also discussed.

Multiparametric Magnetic Resonance Imaging of Prostate Cancer Bone Disease: Correlation With Bone Biopsy Histological and Molecular Features

OBJECTIVES

The aim of this study was to correlate magnetic resonance imaging (MRI) of castration-resistant prostate cancer (CRPC) bone metastases with histological and molecular features of bone metastases.

MATERIALS AND METHODS

Forty-three bone marrow biopsies from 33 metastatic CRPC (mCRPC) patients with multiparametric MRI and documented bone metastases were evaluated. A second cohort included 10 CRPC patients with no bone metastases. Associations of apparent diffusion coefficient (ADC), normalized b900 diffusion-weighted imaging (nDWI) signal, and signal-weighted fat fraction (swFF) with bone marrow biopsy histological parameters were evaluated using Mann-Whitney U test and Spearman correlations. Univariate and multivariate logistic regression models were analyzed.

RESULTS

Median ADC and nDWI signal was significantly higher, and median swFF was significantly lower, in bone metastases than nonmetastatic bone (P < 0.001). In the metastatic cohort, 31 (72.1%) of 43 biopsies had detectable cancer cells. Median ADC and swFF were significantly lower and median nDWI signal was significantly higher in biopsies with tumor cells versus nondetectable tumor cells (898 × 10 mm/s vs 1617 × 10 mm/s; 11.5% vs 62%; 5.3 vs 2.3, respectively; P < 0.001). Tumor cellularity inversely correlated with ADC and swFF, and positively correlated with nDWI signal (P < 0.001). In serial biopsies, taken before and after treatment, changes in multiparametric MRI parameters paralleled histological changes.

CONCLUSIONS

Multiparametric MRI provides valuable information about mCRPC bone metastases. These data further clinically qualify DWI as a response biomarker in mCRPC.

Apparent diffusion coefficient mapping using diffusion-weighted MRI: impact of background parenchymal enhancement, amount of fibroglandular tissue and menopausal status on breast cancer diagnosis

OBJECTIVES

To investigate the impact of background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT) and menopausal status on apparent diffusion coefficient (ADC) values in differentiation between malignant and benign lesions.

METHODS

In this HIPAA-compliant study, mean ADC values of 218 malignant and 130 benign lesions from 288 patients were retrospectively evaluated. The differences in mean ADC values between benign and malignant lesions were calculated within groups stratified by BPE level (high/low), amount of FGT (dense/non-dense) and menopausal status (premenopausal/postmenopausal). Sensitivities and specificities for distinguishing malignant from benign lesions within different groups were compared for statistical significance.

RESULTS

The mean ADC value for malignant lesions was significantly lower compared to that for benign lesions (1.07±0.21 x 10^-3 mm²/s vs. 1.53±0.26 x 10^-3 mm²/s) (p<0.0001). Using the optimal cut-off point of 1.30 x 10^-3 mm²/s, an area under the curve of 0.918 was obtained, with sensitivity and specificity both of 87 %. There was no statistically significant difference in sensitivities and specificities of ADC values between different groups stratified by BPE level, amount of FGT or menopausal status.

CONCLUSIONS

Differentiation between benign and malignant lesions on ADC values is not significantly affected by BPE level, amount of FGT or menopausal status.

KEY POINTS

• ADC allows differentiation between benign and malignant lesions. • ADC is useful for breast cancer diagnosis despite different patient characteristics. • BPE, FGT or menopause do not significantly affect sensitivity and specificity.

Contrast Enhancement on Cone-Beam Breast-CT for Discrimination of Breast Cancer Immunohistochemical Subtypes

PURPOSE: To evaluate whether contrast enhancement on cone-beam breast-CT (CBBCT) could aid in discrimination of breast cancer subtypes and receptor status. METHODS: This study included female patients age >40 years with malignant breast lesions identified on contrast-enhanced CBBCT. Contrast enhancement of malignant breast lesions was standardized to breast fat tissue contrast enhancement. All breast lesions were approved via image-guided biopsy or surgery. Immunohistochemical staining was conducted for expression of estrogen (ER), progesterone (PR), human epidermal growth factor receptor-2 (HER2) and Ki-67 index. Contrast enhancement of breast lesions was correlated with immunohistochemical breast cancer subtypes (Luminal A, Luminal B, HER2 positive, triple negative), receptor status and Ki-67 expression. RESULTS: Highest contrast enhancement was seen for Luminal A lesions (93.6 HU) compared to Luminal B lesions (47.6 HU, P = .002), HER2 positive lesions (83.5 HU, P = .359) and triple negative lesions (45.3 HU, P = .005). Contrast enhancement of HER2 positive lesions was higher than Luminal B lesions (P = .044) and triple negative lesions (P = .039). No significant difference was evident between Luminal B and triple negative lesions (P = .439). Lesions with high Ki-67 index showed lower contrast enhancement than those with low Ki-67 index (P = .0043). ER, PR and HER2 positive lesions demonstrated higher contrast enhancement than their receptor negative counterparts, although differences did not reach statistical significance (P = .1714; P = .3603; P = .2166). CONCLUSIONS: Contrast enhancement of malignant breast lesions on CBBCT correlates with immunohistochemical subtype and proliferative potential. Thereby, CBBCT might aid in selecting individualized treatment strategies for breast cancer patients based on pre-operative imaging.

Cone-beam Breast Computed Tomography: CT Density Does Not Reflect Proliferation Potential and Receptor Expression of Breast Carcinoma

PURPOSE: Recently, cone-beam breast computed tomography (CBCT) is established for the breast investigation. The purpose of the present study was to investigate possible associations between CBCT findings and histopathological features in breast cancer. METHODS: Overall, 59 female patients, mean age of 64.6 years with histological proven breast cancer were included into the study. In all cases, non-contrast CBCT examination was done. The diagnosis of the identified lesions was confirmed histologically by biopsy. Immunohistochemical staining against estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki-67 was performed for every lesion. Collected data were evaluated by means of descriptive statistics. Spearman's correlation coefficient was used to analyze the association between CT density and Ki-67 values. P values <0.05 were taken to indicate statistical significance in all instances. RESULTS: The size of the lesion varied from 2.7 to 90.0, mean size, 15.88 ± 13.0 mm. The mean value of CT density of the lesions was 63.95 ± 38.18 HU. The density tended to be higher in tubular carcinoma. Correlation analysis identified no significant correlations between CT density and Ki-67 level (r = −0.031, P = .784). There were no statistically significant differences of CT density between tumors with different receptor status. CONCLUSIONS: No significant associations between CT density and receptor status in breast cancer. Tubular carcinoma tended to have higher CT density in comparison to other subtypes of breast carcinomas.

Apparent diffusion coefficient in estrogen receptor-positive and lymph node-negative invasive breast cancers at 3.0T DW-MRI: A potential predictor for an oncotype Dx test recurrence score

PURPOSE

To measure the apparent diffusion coefficient (ADC) values in estrogen receptor-positive (ER+) and axillary lymph node-negative (LN-) invasive breast cancer and investigate the correlation of ADC with Oncotype Dx test recurrence scores (ODxRS).

MATERIALS AND METHODS

This was a Health Insurance Portability and Accountability Act (HIPAA)-compliant single-site retrospective study. Patients underwent preoperative 3.0T MRI scans with additional diffusion-weighted imaging sequential scans (b = 0, 600 and b = 0, 1000 s/mm² ) from January 2011 to 2013. The study population included 31 ER+/LN- invasive breast cancers, which underwent ODxRS genomic testing. ADC₆₀₀ and ADC₁₀₀₀ parametric maps were generated, and ADC values were calculated from a user-drawn region of interest. ODxRS predicts 10-year recurrence risk in individual patients: low (RS <18), intermediate (RS: 18-30), or high (RS >30). All breast lesions, including subgroups of invasive ductal carcinoma (IDC) lesions and mass-only lesions were dichotomized by RS scores, low-risk versus intermediate/high-risk, and statistical analysis was performed using Mann-Whitney's test (statistical significance at P < 0.05) and receiver operating characteristic (ROC) curves. Multivariate analysis was also performed.

RESULTS

Invasive breast cancers, when scored as low-risk by ODxRS, had significantly higher ADC values compared with intermediate/high-risk lesions for both ADC₆₀₀ (P = 0.007) and ADC₁₀₀₀ (P = 0.008) mean values. This was true both when analyzing only mass-lesions (P = 0.03 and 0.01) or only IDCs (P = 0.001 and 0.009).

CONCLUSION

Preliminary findings suggest that lesion ADC values correlate with recurrence risk likelihood stratified using ODxRS. Hence, ADC is a potential surrogate biomarker for tumor aggressiveness.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018;47:401-409.

Diffusion-weighted Imaging as a Treatment Response Biomarker for Evaluating Bone Metastases in Prostate Cancer: A Pilot Study

Purpose To determine the usefulness of whole-body diffusion-weighted imaging (DWI) to assess the response of bone metastases to treatment in patients with metastatic castration-resistant prostate cancer (mCRPC). Materials and Methods A phase II prospective clinical trial of the poly-(adenosine diphosphate-ribose) polymerase inhibitor olaparib in mCRPC included a prospective magnetic resonance (MR) imaging substudy; the study was approved by the institutional research board, and written informed consent was obtained. Whole-body DWI was performed at baseline and after 12 weeks of olaparib administration by using 1.5-T MR imaging. Areas of abnormal signal intensity on DWI images in keeping with bone metastases were delineated to derive total diffusion volume (tDV); five target lesions were also evaluated. Associations of changes in volume of bone metastases and median apparent diffusion coefficient (ADC) with response to treatment were assessed by using the Mann-Whitney test and logistic regression; correlation with prostate-specific antigen level and circulating tumor cell count were assessed by using Spearman correlation (r). Results Twenty-one patients were included. All six responders to olaparib showed a decrease in tDV, while no decrease was observed in all nonresponders; this difference between responders and nonresponders was significant (P = .001). Increases in median ADC were associated with increased odds of response (odds ratio, 1.08; 95% confidence interval [CI]: 1.00, 1.15; P = .04). A positive association was detected between changes in tDV and best percentage change in prostate-specific antigen level and circulating tumor cell count (r = 0.63 [95% CI: 0.27, 0.83] and r = 0.77 [95% CI: 0.51, 0.90], respectively). When assessing five target lesions, decreases in volume were associated with response (odds ratio for volume increase, 0.89; 95% CI: 0.80, 0.99; P = .037). Conclusion This pilot study showed that decreases in volume and increases in median ADC of bone metastases assessed with whole-body DWI can potentially be used as indicators of response to olaparib in mCRPC. Online supplemental material is available for this article.

Diagnostic Performance of Diffusion Tensor Imaging with Readout-segmented Echo-planar Imaging for Invasive Breast Cancer: Correlation of ADC and FA with Pathological Prognostic Markers

Purpose:

To assess the diagnostic performance of readout-segmented echo-planar diffusion tensor imaging (DTI based on rs-EPI) for breast cancer and to determine the correlation between the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values obtained from DTI based on rs-EPI with prognostic markers of invasive breast cancer.

Materials and Methods:

This retrospective study examined 80 pathologically proven breast lesions (22 benign and 58 malignant lesions) of 80 patients who underwent both diffusion-weighted imaging based on single-shot echo-planar imaging (DWI based on ss-EPI) and DTI based on rs-EPI with b-values of 0 and 1000. We identified and compared the diagnostic performances of the DWI based on ss-EPI and the DTI based on rs-EPI using ADCs by conducting a receiver-operating-characteristics (ROC) analysis. We determined the correlations between the ADCs and the prognostic markers and those of the FA values and the same markers.

Results:

The median ADCs of the benign and malignant lesions based on the ss-EPI were 1.57 and 1.2 × 10⁻³ mm²/sec, and those based on the rs-EPI were 1.53 and 1.09 × 10⁻³ mm²/sec, respectively. The area under the curve on the ROC analysis based on rs-EPI (0.924) was greater than that based on ss-EPI (0.897). There were no significant correlations between the ADCs and the prognostic markers, but there were significant correlations between the FA values and the estrogen receptor status, a proliferative marker, the nuclear grade and the intrinsic subtype.

Conclusion:

For breast cancer, DTI based on rs-EPI had superior diagnostic performance compared to DWI based on ss-EPI. Compared with the ADCs, the FA values were more closely correlated with prognostic markers of invasive breast cancer.

Metabolomics of Breast Cancer Using High-Resolution Magic Angle Spinning Magnetic Resonance Spectroscopy: Correlations with 18F-FDG Positron Emission Tomography-Computed Tomography, Dynamic Contrast-Enhanced and Diffusion-Weighted Imaging MRI

Purpose

Our goal in this study was to find correlations between breast cancer metabolites and conventional quantitative imaging parameters using high-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) and to find breast cancer subgroups that show high correlations between metabolites and imaging parameters.

Materials and methods

Between August 2010 and December 2013, we included 53 female patients (mean age 49.6 years; age range 32–75 years) with a total of 53 breast lesions assessed by the Breast Imaging Reporting and Data System. They were enrolled under the following criteria: breast lesions larger than 1 cm in diameter which 1) were suspicious for malignancy on mammography or ultrasound (US), 2) were pathologically confirmed to be breast cancer with US-guided core-needle biopsy (CNB) 3) underwent 3 Tesla MRI with dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) and positron emission tomography-computed tomography (PET-CT), and 4) had an attainable immunohistochemistry profile from CNB. We acquired spectral data by HR-MAS MRS with CNB specimens and expressed the data as relative metabolite concentrations. We compared the metabolites with the signal enhancement ratio (SER), maximum standardized FDG uptake value (SUV max), apparent diffusion coefficient (ADC), and histopathologic prognostic factors for correlation. We calculated Spearman correlations and performed a partial least squares-discriminant analysis (PLS-DA) to further classify patient groups into subgroups to find correlation differences between HR-MAS spectroscopic values and conventional imaging parameters.

Results

In a multivariate analysis, the PLS-DA models built with HR-MAS MRS metabolic profiles showed visible discrimination between high and low SER, SUV, and ADC. In luminal subtype breast cancer, compared to all cases, high SER, ADV, and SUV were more closely clustered by visual assessment. Multiple metabolites were correlated with SER and SUV in all cases. Multiple metabolites showed correlations with SER and SUV in the ER positive, HER2 negative, and Ki-67 negative groups.

Conclusion

High levels of PC, choline, and glycine acquired from HR-MAS MRS using CNB specimens were noted in the high SER group via DCE MRI and the high SUV group via PET-CT, with significant correlations between choline and SER and between PC and SUV. Further studies should investigate whether HR-MAS MRS using CNB specimens can provide similar or more prognostic information than conventional quantitative imaging parameters.

Quantitative apparent diffusion coefficient measurement obtained by 3.0Tesla MRI as a potential noninvasive marker of tumor aggressiveness in breast cancer

PURPOSE

To assess the association between apparent diffusion coefficient (ADC), and histological prognostic parameters in malignant breast lesions. The ability of ADC to identify lesions with the presence of Lymphovascular invasion (LVI) in breast carcinoma was also examined.

MATERIALS AND METHODS

This HIPAA-compliant retrospective study consisted of 212 consecutive patients with known cancers who underwent 3.0T MRI between January 2011 and 2013. In this study, a total of 126 malignant lesions in 114 women, who had undergone DWI (b-values of 0 and 1000s/mm(2)) in addition to diagnostic MRI, were included. Patients with less than 0.8cm lesions, or those who underwent neoadjuvant chemotherapy or suboptimal DW images were excluded. Classical prognostic factors [lesion size, histopathological type and grade, lymph node (LN) status and lymphovascular invasion (LVI)], molecular prognostic markers [estrogen receptor (ER), progesterone receptor (PR) and human epidermal grow factor receptor 2 (HER2)] were reviewed and recorded. A region of interest (ROI) was drawn within the lesions to measure ADC values. Statistical analyses were performed by the Wilcoxon rank sum test (statistical significance at P<0.05). Adjusted p values from multiple comparison analysis were also calculated.

RESULTS

This study demonstrates an inverse correlation between ADC and LVI in malignant lesions and the ability of ADC to identify aggressiveness in lesions with positive LVI. Tumor size, grade, ER, PR, HER2 and lymph node status did not impact tumor ADC value. However, tumors with LVI showed significantly lower ADC values when compared to tumors without LVI, regardless of the enhancement type, histological grade, histological type, and LN status.

CONCLUSION

Our study shows that ADC could be a potential clinical adjunct in the evaluation of prognostic factors related to malignant lesion aggressiveness such as LVI.

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.

Intratumor Heterogeneity of Perfusion and Diffusion in Clear-Cell Renal Cell Carcinoma: Correlation With Tumor Cellularity

BACKGROUND

Magnetic resonance imaging (MRI) has the potential to noninvasively provide information about the tumor microenvironment. A correlation between arterial spin-labeled (ASL) MRI and tumor vasculature has been previously demonstrated; however, its correlation with tumor cellularity is unknown. We sought to assess intratumor heterogeneity of perfusion and diffusion in vivo in clear-cell renal cell carcinoma (ccRCC) using MRI and to correlate these findings with tumor vascularity and cellularity at histopathology.

PATIENTS AND METHODS

Twenty-three ccRCC patients underwent ASL and diffusion-weighted MRI before surgery after signing an informed consent in this prospective institutional review board-approved, HIPAA (Insurance Portability and Accountability Act)-compliant study. Quantitative ASL perfusion and diffusion were measured in 2 areas within the same tumor with high and low perfusion. Microvessel density (MVD) on CD31 and CD34 immunostains and tumor cellularity in anatomically coregistered tissue samples were correlated to MRI measurements (Spearman; P < .05 statistically significant).

RESULTS

ASL perfusion (P < .0001), CD31 MVD (P = .02), CD34 MVD (P = .04), and cellularity (P = .002) from high and low perfusion areas were significantly different across all tumors. There were positive correlations between tumor cellularity and CD31 MVD (ρ = 0.350, P = .021), CD31 and CD34 MVD (ρ = 0.838, P < .0001), ASL perfusion and cellularity (ρ = 0.406, P = .011), and ASL perfusion and CD31 MVD (ρ = 0.468, P = .003), and a negative correlation between tissue diffusion coefficient and cellularity (ρ = -0.316, P = .039).

CONCLUSION

Tumor areas with high ASL perfusion exhibit higher cellularity and MVD compared to areas with low perfusion in the same tumor. A positive correlation between tumor vascularity and cellularity in ccRCC is newly reported. A negative correlation between tumor diffusion and cellularity is confirmed.

Association between dynamic contrast enhanced MRI imaging features and WHO histopathological grade in patients with invasive ductal breast cancer

The present study aimed to investigate the dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and World Health Organization (WHO) histopathological grade in patients with invasive ductal breast cancer. A retrospective analysis on the results of DCE-MRI of 92 patients, who were diagnosed with invasive ductal breast cancer following surgery or biopsy, and these results were correlated with WHO histopathological grade. The statistical analysis demonstrated that the tumor size, shape and characteristics of early enhancement were associated with the WHO histopathological grade: The larger the lesion's long diameter, the higher the WHO histopathological grade; the WHO histopathological grades of round and oval masses were relatively lower, while those of lobulated and irregular masses were higher; and tumors with heterogeneous and ring-like enhancement exhibited higher WHO histopathological grades, while those of homogeneous enhancement were lower. The lesion's margin shape was not associated with the WHO histopathological grade. The present study demonstrates that features of DCE-MRI and WHO histopathological grade in patients with invasive ductal breast cancer are correlated, and these MRI features could be used to evaluate the biological behavior and prognosis of lesions.

Diffusion-weighted imaging and (18) F-fluorodeoxyglucose positron emission tomography/computed tomography in breast cancer: Correlation of the apparent diffusion coefficient and maximum standardized uptake values with prognostic factors

PURPOSE

To evaluate the correlations between the apparent diffusion coefficient (ADC) value and the standardized uptake value (SUV) with prognostic factors in breast cancer.

MATERIALS AND METHODS

Seventy women with invasive breast cancer (56 cases of invasive ductal carcinoma, four of mixed ductal and lobular invasive carcinoma, three of lobular invasive carcinoma, two of micropapillary carcinoma, and one each of mixed ductal and mucinous carcinoma, mucinous carcinoma, medullary carcinoma, metaplastic carcinoma, and tubular carcinoma) were included in this study. All patients underwent presurgical breast magnetic resonance imaging (MRI) with diffusion-weighted imaging (DWI) at 1.5T and whole-body (18) F-fluorodeoxyglucose ((18) F-FDG) positron emission tomography (PET) / computed tomography (CT). For all invasive breast cancers and invasive ductal carcinomas, we assessed the relationships among ADC, SUV, and pathological prognostic factors.

RESULTS

Both the median ADC value and maximum SUV (SUVmax) were significantly associated with vascular invasion (P = 0.008 and P = 0.026, respectively). SUVmax was also significantly correlated with tumor size (P = 0.001), histological grade (P = 0.001), lymph node status (P = 0.0015), estrogen receptor status (P = 0.010), and human epidermal growth factor receptor 2 status (P = 0.020), whereas ADC values were not. The correlation between the ADC and SUVmax was not significant (P = 0.356; R = -0.112). Mucinous carcinoma showed high ADC and relatively low SUVmax. Medullary carcinoma showed low ADC and high SUVmax. When we evaluated the relationships among ADC, SUVmax, and prognostic factors in the 56 invasive ductal carcinomas, our statistical results were not significantly changed, except SUVmax was also significantly associated with progesterone receptor status (P = 0.034), but not lymph node status.

CONCLUSION

SUVmax may be valuable for predicting the prognosis of breast cancer. Both ADC and SUVmax are useful to predict vascular invasion. J. Magn. Reson. Imaging 2016;43:1434-1444.

Correlation of tumor characteristics derived from DCE-MRI and DW-MRI with histology in murine models of breast cancer

The purpose of this work was to determine the relationship between the apparent diffusion coefficient (ADC, from diffusion-weighted (DW) MRI), the extravascular, extracellular volume fraction (ve , from dynamic contrast-enhanced (DCE) MRI), and histological measurement of the extracellular space fraction. Athymic nude mice were injected with either human epidermal growth factor receptor 2 positive (HER2+) BT474 (n = 15) or triple negative MDA-MB-231 (n = 20) breast cancer cells, treated with either Herceptin (n = 8), Abraxane (low dose n = 7, high dose n = 6), or saline (n = 7 for each cell line), and imaged using DW- and DCE-MRI before, during, and after treatment. After the final imaging acquisition, the tissue was resected and evaluated by histological analysis. H&E-stained central slices were scanned using a digital brightfield microscope and evaluated with thresholding techniques to calculate the extracellular space. For both BT474 and MDA-MB-231, the median ADC of the central slice exhibited a significantly positive correlation with the corresponding central slice extracellular space as measured by H&E (p = 0.03, p < 0.01, respectively). Median ve calculated from the central slice showed differing results between the two cell lines. For BT474, a significant correlation between ve and extracellular space was calculated (p = 0.02), while MDA-MB-231 tumors did not demonstrate a significant correlation (p = 0.64). Additionally, there was no correlation discovered between ADC and ve with either whole tumor analysis or central slice analysis (p > 0.05). While ADC correlates well with the histologically determined fraction of extracellular space, these data add to the growing body of literature that suggests that ve derived from DCE-MRI is not a reliable biomarker of extracellular space for a range of physiological conditions.

Therapy monitoring of skeletal metastases with whole-body diffusion MRI

Current methods of assessing tumor response at skeletal sites with metastatic disease use a combination of imaging tests, serum and urine biochemical markers, and symptoms assessment. These methods do not always enable the positive assessment of therapeutic benefit to be made but instead provide an evaluation of progression, which then guides therapy decisions in the clinic. Functional imaging techniques such as whole-body diffusion magnetic resonance imaging (MRI) when combined with anatomic imaging and other emerging "wet" biomarkers can improve the classification of therapy response in patients with metastatic bone disease. A range of imaging findings can be seen in the clinic depending on the type of therapy and duration of treatment. Successful response to systemic therapy is usually depicted by reductions in signal intensity accompanied by apparent diffusion coefficient (ADC) increases. Rarer patterns of successful treatment include no changes in signal intensity accompanying increases in ADC values (T2 shine-through pattern) or reductions in signal intensity without ADC value changes. Progressive disease results in increases in extent/intensity of disease on high b-value images with variable ADC changes. Diffusion MRI therapy response criteria need to be developed and tested in prospective studies in order to address current, unmet clinical and pharmaceutical needs for reliable measures of tumor response in metastatic bone disease.

Correlations between functional imaging markers derived from PET/CT and diffusion-weighted MRI in diffuse large B-cell lymphoma and follicular lymphoma

Objectives

To investigate the correlations between functional imaging markers derived from positron emission tomography/computed tomography (PET/CT) and diffusion-weighted magnetic resonance imaging (DWI) in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). Further to compare the usefulness of these tumor markers in differentiating diagnosis of the two common types of Non-Hodgkin's lymphoma (NHL).

Materials and Methods

Thirty-four consecutive pre-therapy adult patients with proven NHL (23 DLBCL and 11 FL) underwent PET/CT and MRI examinations and laboratory tests. The maximum standardized uptake value (SUV_max), metabolic tumor volume (MTV), and metabolic tumor burden (MTB) were determined from the PET/CT images. DWI was performed in addition to conventional MRI sequences using two b values (0 and 800 s/mm²). The minimum and mean apparent diffusion coefficient (ADC_min and ADC_mean) were measured on the parametric ADC maps.

Results

The SUV_max correlated inversely with the ADC_min (r = −0.35, p<0.05). The ADC_min, ADC_mean, serum thymidine kinase (TK), Beta 2-microglobulin (B2m), lactate dehydrogenase (LD), and C-reactive protein (CRP) correlated with both whole-body MTV and whole-body MTB (p<0.05 or 0.01). The SUV_max, TK, LD, and CRP were significantly higher in the DLBCL group than in the FL group. Receiver operating characteristic curve analysis showed that they were reasonable predictors in differentiating DLBCL from FL.

Conclusions

The functional imaging markers determined from PET/CT and DWI are associated, and the SUV_max is superior to the ADC_min in differentiating DLBCL from FL. All the measured serum markers are associated with functional imaging markers. Serum LD, TK, and CRP are useful in differentiating DLBCL from FL.

Agreement and reproducibility of apparent diffusion coefficient measurements of dual-b-value and multi-b-value diffusion-weighted magnetic resonance imaging at 1.5 Tesla in phantom and in soft tissues of the abdomen

OBJECTIVE

To compare the coefficient of variation (CV) and long-term reproducibility of apparent diffusion coefficient (ADC) in a simple fluid-filled phantom and abdominal organs simultaneously.

MATERIALS AND METHODS

Retrospective institutional review board-approved and Health Insurance Portability and Accountability Act-compliant study sequentially selected 100 patients who underwent clinically indicated abdominal magnetic resonance imaging. A subset of 58 patients had repeat scans within 2 to 5 months after the initial magnetic resonance imaging. Two diffusion-weighted imaging techniques (b-values 0-750 mm/s) were performed to compare the ADC values. Mean ADC values were calculated for 10 locations and the reference phantom. The CV and Bland-Altman plots were calculated for the phantom and soft tissues at each session and location.

RESULTS

There were no significant differences in the mean ADC values between repeated acquisitions. However, ADC values were statistically higher using dual-b-value than multi-b-value diffusion-weighted imaging. The CV for the phantom was 8.6 versus 10.8 for dual-b-value and multi-b-value, respectively. The CVs for the soft tissues had a wider range compared with that of the phantom (liver, 12.6 vs 9.0; spleen, 11.7 vs 11.2; gallbladder, 11.0 vs 13.6; head of pancreas, 14.6 vs 14.7; body of pancreas, 13.4 vs 13.0; tail of pancreas, 14.8 vs 16.3; right kidney, 9.1 vs 9.6; left kidney, 9.3 vs 9.3; right paraspinal muscle, 7.9 vs 7.5; left paraspinal muscle, 7.3 vs 7.3, respectively).

CONCLUSIONS

A change in ADC less than 11% falls into the range of measurement variability. Paraspinal muscle could potentially be used as an internal reference parameter.

Bony metastases: assessing response to therapy with whole-body diffusion MRI

There are no universally accepted methods for assessing tumour response in skeletal sites with metastatic disease; response is assessed by a combination of imaging tests, serum and urine biochemical markers and symptoms assessments. Whole-body diffusion magnetic resonance imaging excels at bone marrow assessments at diagnosis and for therapy evaluations. It can potentially address unmet clinical and pharmaceutical needs for a reliable measure of tumour response. Signal intensity on high b-value images and apparent diffusion coefficient values can be related to underlying biophysical properties of skeletal metastases. Four patterns of change in response to therapy are described this review. Therapy response criteria need to be tested in prospective clinical studies that incorporate conventional measures of patient benefit.