Diffusion Weighted MR Imaging of Breast and Correlation of Prognostic Factors in Breast Cancer

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.

Correlation of apparent diffusion coefficient values and peritumoral edema with pathologic biomarkers in patients with breast cancer

PURPOSE

To investigate the relationship between breast cancer imaging features on magnetic resonance imaging (MRI) and histopathological characteristics.

METHODS AND MATERIALS

We prospectively enrolled 46 patients who underwent 1.5-T MRI with 68 breast malignant lesions from 2017 until 2019. Peritumoral edema was determined based on visual assessment on T2 weighted imaging. Lesions were categorized into two groups: A: with edema (48 lesions) and B: without edema (20 lesions).

RESULTS

The tumor size was not different among two groups but multifocal-multicentric lesions were more common in the group A (70% vs. 35%). The axillary lymph nodes are most involved in group A. ER and PR positive lesions were more common in group B (90% vs. 56.3%) but in the group A, HER2 positive lesions were found to be more common (31.3% vs. 15%). The mean ADC value in tumors and peritumoral regions were lower (0.97 × 10^-3 mm²/s, P = 0.023) and higher (1.85 × 10^-3 mm²/s, P < 0.0001) in group A, respectively. Peritumoral ADC value was significantly higher in HER2-positive group.

CONCLUSION

Breast carcinomas with peritumoral edema were found to be more multifocal-multicentric, with higher prevalence of axillary lymph node involvement, more HER 2-positive, with lower prevalence of ER/PR-positive, lower tumoral ADC and higher peritumoral ADC values.

Associations Between Apparent Diffusion Coefficient Value With Pathological Type, Histologic Grade, and Presence of Lymph Node Metastases of Esophageal Carcinoma

Objective:

To investigate the application value of apparent diffusion coefficient value in the pathological type, histologic grade, and presence of lymph node metastases of esophageal carcinoma.

Materials and Methods:

Eighty-six patients with pathologically confirmed esophageal carcinoma were divided into different groups according to pathological type, histological grade, and lymph node status. All patients underwent conventional magnetic resonance imaging and diffusion-weighted imaging scan, and apparent diffusion coefficient values of tumors were measured. Independent sample t test and 1-way variance were used to compare the difference of apparent diffusion coefficient value in different pathological types, histologic grades, and lymph node status. Correlation between the apparent diffusion coefficient value and the histologic grade was evaluated using Spearman rank correlation test. Receiver operating characteristic curve of apparent diffusion coefficient value was generated to evaluate the differential diagnostic efficiency of poorly and well/moderately differentiated esophageal carcinoma.

Results:

No significant difference was observed in apparent diffusion coefficient value between esophageal squamous cell carcinoma and adenocarcinoma and in patients between those with and without lymph node metastases (P > .05). The differences of apparent diffusion coefficient value were statistically significant between different histologic grades of esophageal carcinoma (P < .05). The apparent diffusion coefficient value was positively correlated with histologic grade (rs = 0.802). The apparent diffusion coefficient value ≤1.25 × 10⁻³ mm²/s as the cutoff value for diagnosis of poorly differentiated esophageal carcinoma with the sensitivity of 84.3%, and the specificity was 94.3%.

Conclusions:

The performance of apparent diffusion coefficient value was contributing to predict the histologic grade of esophageal carcinoma, which might increase lesions characterization before choosing the best therapeutic alternative. However, they do not correlate with pathological type and the presence of lymph node metastases of esophageal carcinoma.

Diffusion weighted imaging in breast cancer - Can it be a noninvasive predictor of nuclear grade?

BACKGROUND

DWI and ADC values are noninvasive MRI techniques, which provide quantitative information about tumor heterogeneity.

AIM

To determine the minimum and mean ADC values in breast carcinoma and to correlate ADC values with various prognostic factors.

SETTINGS AND DESIGN

Prospective observational study.

MATERIALS AND METHODS

Fifty-five patients with biopsy-proven breast carcinoma were included in this study. MRI with DWI was performed with Siemens 3T Skyra scanner. ADC values were measured by placing regions of interest (ROIs) within the targeted lesions on ADC maps manually. The histopathological and immunohistochemical analysis of surgical specimen was done to determine the prognostic factors.

STATISTICAL ANALYSIS

Students T test and ANOVA were used to study the difference in ADC between two groups. Pearson correlation coefficient was used to quantify the correlation between ADC values and prognostic factors.

RESULTS

Lower grade (grade I) breast carcinoma had a significantly high ADC value as compared to higher grade carcinoma (grade II and III). For differentiating Grade I tumors from grade II and III, a minimum ADC cut-off value was 0.79 × 10-3 mm2/sec (83% sensitivity and 84% specificity) and a mean ADC cut-off value was 0.82 × 10-3 mm2/sec (83% sensitivity and 71% specificity) was derived. There was no significant correlation between ADC and other prognostic factors.

CONCLUSION

ADC values can be used to differentiate lower grade breast carcinoma (grade I) from higher grades (grade II and III). Minimum ADC values are more accurate in predicting the grade of the breast tumor than mean ADC value.

Diffusion-Weighted Imaging of Breast Cancer: Correlation of the Apparent Diffusion Coefficient Value with Pathologic Prognostic Factors

Objective

The aim was to evaluate relationship between apparent diffusion coefficient (ADC) values with pathologic prognostic factors in breast carcinoma (BC).

Materials and Methods

83 patients were enrolled in this study. Prognostic factors included age, tumor size, expression of estrogen receptor (ER) and progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), nuclear grade (NG), lymph node involvement and histologic type. The relationship between ADC and prognostic factors was determined using Independent sample t-test, ANOVA, Pearson correlation and relative operating characteristics (ROC) analysis.

Results

There was no significant difference between ADC and prognostic factors, including age, tumor size, ER, HER2 and histologic type. The PR-positive tumors (p=0.03) and axillary lymph node involvement (p=0.000) showed a significant association with lower ADC values. The ADC values were significantly lower in high-grade tumors than low-grade tumors (p=0.000). ROC analysis showed an optimal ADC threshold of 0.66 (×10-3 mm2/s) for differentiating low-grade tumors from high-grade tumors (sensitivity, 85.5%; specificity, 81%; area under curve, 0.90).

Conclusion

The lower ADC values of BC were significantly associated with positive expression of PR, LN positivity and high-grade tumor. Especially, ADC values were valuable in predicting NG subgroups.

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.

Sequential [18F]FDG-[18F]FMISO PET and Multiparametric MRI at 3T for Insights into Breast Cancer Heterogeneity and Correlation with Patient Outcomes: First Clinical Experience

The aim of this study was to assess whether sequential multiparametric ¹⁸[F]fluoro-desoxy-glucose (¹⁸[F]FDG)/[¹⁸F]fluoromisonidazole ([¹⁸F]FMISO) PET-MRI in breast cancer patients is possible, facilitates information on tumor heterogeneity, and correlates with prognostic indicators. In this pilot study, IRB-approved, prospective study, nine patients with ten suspicious breast lesions (BIRADS 5) and subsequent breast cancer diagnosis underwent sequential combined [¹⁸F]FDG/[18F]FMISO PET-MRI. [¹⁸F]FDG was used to assess increased glycolysis, while [¹⁸F]FMISO was used to detect tumor hypoxia. MRI protocol included dynamic breast contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI). Qualitative and quantitative multiparametric imaging findings were compared with pathological features (grading, proliferation, and receptor status) and clinical endpoints (recurrence/metastases and disease-specific death) using multiple correlation analysis. Histopathology was the standard of reference. There were several intermediate to strong correlations identified between quantitative bioimaging markers, histopathologic tumor characteristics, and clinical endpoints. Based on correlation analysis, multiparametric criteria provided independent information. The prognostic indicators proliferation rate, death, and presence/development of recurrence/metastasis correlated positively, whereas the prognostic indicator estrogen receptor status correlated negatively with PET parameters. The strongest correlations were found between disease-specific death and [¹⁸F]FDG_mean (R=0.83, p < 0.01) and between the presence/development of metastasis and [¹⁸F]FDG_max (R=0.79, p < 0.01), respectively. This pilot study indicates that multiparametric [¹⁸F]FDG/[¹⁸F]FMISO PET-MRI might provide complementary quantitative prognostic information on breast tumors including clinical endpoints and thus might be used to tailor treatment for precision medicine in breast cancer.

Clinical role of breast MRI now and going forward

Magnetic resonance imaging (MRI) is a well-established method in breast imaging, with manifold clinical applications, including the non-invasive differentiation between benign and malignant breast lesions, preoperative staging, detection of scar versus recurrence, implant assessment, and the evaluation of high-risk patients. At present, dynamic contrast-enhanced MRI is the most sensitive imaging technique for breast cancer diagnosis, and provides excellent morphological and to some extent also functional information. To compensate for the limited functional information, and to increase the specificity of MRI while preserving its sensitivity, additional functional parameters such as diffusion-weighted imaging and apparent diffusion coefficient mapping, and MR spectroscopic imaging have been investigated and implemented into the clinical routine. Several additional MRI parameters to capture breast cancer biology are still under investigation. MRI at high and ultra-high field strength and advances in hard- and software may also further improve this imaging technique. This article will review the current clinical role of breast MRI, including multiparametric MRI and abbreviated protocols, and provide an outlook on the future of this technique. In addition, the predictive and prognostic value of MRI as well as the evolving field of radiogenomics will be discussed.

Diagnostic Usefulness of Combination of Diffusion-weighted Imaging and T2WI, Including Apparent Diffusion Coefficient in Breast Lesions: Assessment of Histologic Grade

PURPOSE

This study aimed to compare the diagnostic values of a combination of diffusion-weighted imaging and T2-weighted imaging (DWI-T2WI) with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and to evaluate the correlation of DWI with the histologic grade in breast cancer.

MATERIALS AND METHODS

This study evaluated a total of 169 breast lesions from 136 patients who underwent both DCE-MRI and DWI (b value, 1000s/mm²). Morphologic and kinetic analyses for DCE-MRI were classified according to the Breast Imaging-Reporting and Data System. For the DWI-T2WI set, a DWI-T2WI score for lesion characterization that compared signal intensity of DWI and T2WI (benign: DWI-T2WI score of 1, 2; malignant: DWI-T2WI score of 3, 4, 5) was used. The diagnostic values of DCE-MRI, DWI-T2WI set, and combined assessment of DCE and DWI-T2WI were calculated.

RESULTS

Of 169 breast lesions, 48 were benign and 121 were malignant (89 invasive ductal carcinoma, 24 ductal carcinoma in situ, 4 invasive lobular carcinoma, 4 mucinous carcinoma). The mean apparent diffusion coefficient (ADC) of invasive ductal carcinoma (0.92 ± 0.19 × 10^-3 mm²/s) and ductal carcinoma in situ (1.11 ± 0.13 × 10^-3 mm²/s) was significantly lower than the value seen in benign lesions (1.36 ± 0.22 × 10^-3 mm²/s). The specificity, positive predictive value (PPV), and accuracy of DWI-T2WI set and combined assessment of DCE and DWI-T2WI (specificity, 87.5% and 91.7%; PPV, 94.3% and 96.2%; accuracy, Az = 0.876 and 0.922) were significantly higher than those of the DCE-MRI (specificity, 45.8%; PPV, 81.7%; accuracy, Az = 0.854; P < .05). A low ADC value and the presence of rim enhancement were associated with a higher histologic grade cancer (P < .05).

CONCLUSION

Combining DWI, T2WI, and ADC values provides increased accuracy for differentiation between benign and malignant lesions, compared with DCE-MRI. A lower ADC value was associated with a higher histologic grade cancer.

Is there any relationship between adc values of diffusion-weighted imaging and the histopathological prognostic factors of invasive ductal carcinoma?

OBJECTIVE

MRI is being used increasingly as a modality that can provide important information about breast cancer. Diffusion-weighted imaging (DWI) is an imaging technique from which apparent diffusion coefficient (ADC) values can be calculated in addition to obtaining important structural information which cannot be obtained from other imaging studies. We did not find any significant relationships between ADC values and prognostic factors, but did provide some explanations for conflicting results in the literature.

METHODS

The ADC results of 61 females with invasive ductal carcinomas were evaluated. DWI was performed and ADC values were calculated from the area in which restriction of diffusion was the highest in ADC mapping. B value was 500 and region of interest (ROI) was designated between 49 and 100 mm². Calculations were performed automatically by the device. Tissue samples were obtained for prognostic factor evaluation. The relationships between ADC and prognostic factors were investigated. Comparisons between groups were made with one-way ANOVA and Kruskal Wallis test. Pairwise comparisons were made with Dunn's test. Analyses of categorical variables were made with Chi-square test.

RESULTS

We found a weak negative correlation between ADC and Ki-67 values (r = -0.279; p = 0.029). When we compared ADC values in regard to tumour type, we found no significant differences for tumour grade, Ki-67 positivity, estrogen receptor positivity, progesterone receptor positivity, C-erb B2, lymphovascular invasion and ductal carcinoma in situ or lobular carcinoma in situ component. On a side note, we found that mean ADC values decreased as tumour grade increased; however, this was not statistically significant.

CONCLUSION

The literature contains studies that report conflicting results which may be caused by differences in B values, ROI area and magnetic field strength. Multicentre studies and systematic reviews of these findings may produce crucial data for the use of DWI in breast cancer. Advances in knowledge: To determine if any significant relationship exists between DWI findings and prognostic factors of breast cancer.

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.

Abbreviated MRI Protocols for Detecting Breast Cancer in Women with Dense Breasts

Objective

To evaluate the validity of two abbreviated protocols (AP) of MRI in breast cancer screening of dense breast tissue.

Materials and Methods

This was a retrospective study in 356 participants with dense breast tissue and negative mammography results. The study was approved by the Nanjing Medical University Ethics Committee. Patients were imaged with a full diagnostic protocol (FDP) of MRI. Two APs (AP-1 consisting of the first post-contrast subtracted [FAST] and maximum-intensity projection [MIP] images, and AP-2 consisting of AP-1 combined with diffusion-weighted imaging [DWI]) and FDP images were analyzed separately, and the sensitivities and specificities of breast cancer detection were calculated.

Results

Of the 356 women, 67 lesions were detected in 67 women (18.8%) by standard MR protocol, and histological examination revealed 14 malignant lesions and 53 benign lesions. The average interpretation time of AP-1 and AP-2 were 37 seconds and 54 seconds, respectively, while the average interpretation time of the FDP was 3 minutes and 25 seconds. The sensitivities of the AP-1, AP-2, and FDP were 92.9, 100, and 100%, respectively, and the specificities of the three MR protocols were 86.5, 95.0, and 96.8%, respectively. There was no significant difference among the three MR protocols in the diagnosis of breast cancer (p > 0.05). However, the specificity of AP-1 was significantly lower than that of AP-2 (p = 0.031) and FDP (p = 0.035), while there was no difference between AP-2 and FDP (p > 0.05).

Conclusion

The AP may be efficient in the breast cancer screening of dense breast tissue. FAST and MIP images combined with DWI of MRI are helpful to improve the specificity of breast cancer detection.