How to measure breast cancer tumoral size at MR imaging?

Preoperative Dynamic Contrast-Enhanced and Diffusion-Weighted Breast Magnetic Resonance Imaging Findings for Prediction of Lymphovascular Invasion of the Lesions in Node-Negative Invasive Breast Cancer

Purpose: Our single-center retrospective study aimed to investigate the relationship between preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) findings and apparent diffusion coefficient (ADC) values and lymphovascular invasion (LVI) status of the lesions in patients with clinically-radiologically lymph node-negative invasive breast cancer. Methods: A total of 250 breast lesions diagnosed in preoperative magnetic resonance imaging were identified. All patients were divided into 2 subgroups: LVI-negative and LVI-positive according to the pathological findings of surgical specimens. The 2 groups' DCE-MRI findings, ADC values, and histopathological results of lesions were compared. Results: LVI was detected in 100 of 250 lesions. Younger age than 45 years and larger lesion size than 20 mm were found to be associated with the presence of LVI (P < .001). High histological and nuclear grade (P = .001), HER2-enriched molecular subtype (P = .001), and Ki-67 positivity (P = .016) were significantly associated with LVI. The LVI positivity rate was significantly higher in the lesions with medium-rapid initial phase kinetic curve and washout delayed phase kinetic curve (P = .001). The presence of LVI was significantly associated with the presence of peritumoral edema, sentinel lymph node metastasis, adjacent vessel sign, and increased whole breast vascularity (P < .001). When diffusion-weighted imaging findings were evaluated, it was determined that tumoral ADC values lower than 1068 × 10-6 mm2/second (P = .002) and peritumoral-tumoral ADC ratios higher than 1.5 (P = .001) statistically increased the probability of LVI. Conclusion: The patient's age, various histopathological and DCE-MRI findings, tumoral ADC value, and peritumoral-tumoral ADC ratio may be useful in the preoperative prediction of LVI status in breast cancer lesions.

Predictive value of ductal carcinoma in situ with invasive breast cancer in core needle biopsies for final pathologic size of intraductal elements

Preoperative evaluations of the size of ductal carcinoma in situ (DCIS) extension in invasive breast cancer (IBC) are problematic and markers of the actual size of DCIS remain elusive. This study aimed to quantify DCIS on core needle biopsy (CNB) and investigated its association with degree of DCIS extension on paired resection specimens, instead of with presence or absence of an extensive intraductal component or margin status as in earlier studies. This series examined 150 IBCs diagnosed from paired CNB and resection specimens. The DCIS/invasion ratio was calculated using the sum of each element size from CNB. In resection specimens, cases in which the greatest dimension of DCIS extension was longer than the greatest dimension of invasive size were defined as extended DCIS (Ext-DCIS). DCIS/invasion ratio level correlated positively with the degree of Ext-DCIS (P = 0.003). Using receiver operating characteristic curve analysis, setting cases with the subgroup of DCIS extension with greatest dimension > 2.5 times that of the invasive size in the resection specimen (Ext-DCIS > 2.5) as the positive class provided the best discrimination ability for DCIS/invasion ratio (0.375). In multivariate analysis, DCIS/invasion ratio > 0.375 was significantly associated with Ext-DCIS > 2.5 (P = 0.033). In conclusion, DCIS/invasion ratio > 0.375 in CNB was identified as a predictor of Ext-DCIS > 2.5 in resection specimens, suggesting that an approach combining DCIS/invasion ratio from CNB with preoperative staging may better predict the extent of DCIS and facilitate better surgical planning.

Prediction of tumor size in patients with invasive ductal carcinoma using FT-IR spectroscopy combined with chemometrics: a preliminary study

Precise detection of tumor size is essential for early diagnosis, treatment, and evaluation of the prognosis of breast cancer. However, there are some errors between the tumor size of breast cancer measured by conventional imaging methods and the pathological tumor size. Invasive ductal carcinoma (IDC) is a common pathological type of breast cancer. In this study, serum Fourier transform infrared spectroscopy (FT-IR) combined with chemometric methods was used to predict the maximum diameter and maximum vertical diameter of tumors in IDC patients. Three models were evaluated based on the pathological tumor size measured after surgery and included grid search support vector machine regression (GS-SVR), back propagation neural network optimized by genetic algorithm (GA-BP-ANN), and back propagation neural network optimized by particle swarm optimization (PSO-BP-ANN). The results show that three models can accurately predict tumor size. The GA-BP-ANN model provided the best fitting quality of the largest tumor diameter with the determination coefficients of 0.984 in test set. And the GS-SVR model provided the best fitting quality of the largest vertical tumor diameter with the determination coefficients of 0.982 in test set. The GS-SVR model had the highest prediction efficiency and the lowest time complexity of the models. The results indicate that serum FT-IR spectroscopy combined with chemometric methods can predict tumor size in IDC patients. In addition, compared with traditional imaging methods, we found that the experimental results of the three models are better than traditional imaging methods in terms of correlation and fitting degree. And the average fitting error of PSO-BP-ANN and GA-BP-ANN models was less than 0.3 mm. The minimally invasive detection method is expected to be developed into a new clinical diagnostic method for tumor size estimation to reduce the diagnostic trauma of patients and provide new diagnostic experience for patients. Graphical Abstract.

Influence of different post-contrast time points on dynamic contrast-enhanced (DCE) MRI T staging in breast cancer

PURPOSE

to assess whether MRI T stage of breast cancer lesions (BCLs) is affected by maximum diameter (MD) measured at different post-contrast time points (TPs) on different acquisition planes on dynamic contrast-enhanced (DCE) MRI sequence.

METHODS

53 DCE-MRI examinations of patients with BCLs were retrospectively selected. MD of BCLs was measured on axial, coronal and sagittal planes on DCE images at five different post-contrast TPs. Friedman test followed by Bonferroni-adjusted Wilcoxon-signed rank test for post-hoc analysis was performed to evaluate differences among the five measurements. Reliability of the measurements was evaluated with the intraclass correlation coefficient analysis. Differences between pathological and MRI T stage assessed at each TP on each acquisition plane were assessed using the Wilcoxon-sign rank test; p values <0.05 were considered statistically significant.

RESULTS

on axial, coronal and sagittal planes, MD measured at TP1 was significantly different (p < 0.0001) compared to those obtained at the subsequent TPs. No significant differences were found between MD measured at TPs 3, 4 and 5. Intra and inter-observer reliability resulted as very good, with ICC ranging between 0.915-0.992 and 0.845-0.911, respectively. MRI T stage assessed at TP1 on axial and sagittal plane as well as at all TPs on coronal plane was significantly different from pathological T stage.

CONCLUSION

MRI T stage definition of BCLs is significantly affected by the TP used for lesions' MD measurement. TPs 3, 4 and 5 are the preferred TPs for the assessment of MRI T stage of BCLs on both axial and sagittal planes.

Agreement between dynamic contrast-enhanced magnetic resonance imaging and pathologic tumour size of breast cancer and analysis of the correlation with BI-RADS descriptors

Purpose

The purpose of this study was to evaluate magnetic resonance imaging (MRI)-pathology concordance of tumour size in patients with invasive breast carcinoma, with an emphasis on Breast Imaging Reporting and Data System (BI-RADS) descriptors of dynamic contrast-enhanced MRI (DCE-MRI).

Material and methods

Of patients who had preoperative DCE-MRI, 94 were enrolled. Concordance between MRI and the pathological findings was defined as a difference in tumour size of 5 mm or less. The greatest dimension was measured by two radiologists, and BI-RADS descriptives were described in accordance. The gold standard was chosen as the pathologic assessment.

Results

Tumour measurements determined by MRI and the pathological reports were not statistically different (2.64 ± 1.16 cm, Wilcaxon Z = –1.853, p = 0.064). Tumour sizes were concordant in 72/94 patients (76.6%). The mean difference between the pathological and MRI tumour sizes was –0.1 cm. MRI overestimated the size of 17/94 tumours (18.1%) and underestimated the size of 5/94 tumours (5.3%). Discordance was associated with larger tumour size. Histologic and molecular type of tumours, patient age, histologic grade, lymphovascular invasion or perineural invasion positivity, fibroglandular volume, background parenchymal enhancement, and being mass or non-mass were not associated with concordance. Irregular margin and heterogenous enhancement in DCE-MRI were associated with discordance in logistic regression analysis (p = 0.035, OR: 4.24; p = 0.021, OR: 4.96).

Conclusions

Two BI-RADS descriptors of irregular contour and heterogeneous contrast uptake were found to be associated with tumour size discrepancy. This might be attributed to the dynamic and morphologic specialities of tumours primarily rather than tumour biology.

[Breast interventional imaging]

A wide diversity of diagnostic or therapeutic percutaneous biopsies exists under sonography, under mammography, under MRI or under CT. This review will detail the different techniques for helping diagnosis or therapeutic management.