Pathologic Findings of Breast Lesions Detected on Magnetic Resonance Imaging

Discriminative Factors of Malignancy of Ipsilateral Nonmass Enhancement in Women With Newly Diagnosed Breast Cancer on Initial Staging Breast MRI

BACKGROUND

Nonmass enhancement (NME) on breast MRI impacts surgical planning.

PURPOSE

To evaluate positive predictive values (PPVs) and identify malignancy discriminators of NME ipsilateral to breast cancer on initial staging MRI.

STUDY TYPE

Retrospective.

SUBJECTS

Eighty-six women (median age, 48 years; range, 26-75 years) with 101 NME lesions (BI-RADS 4 and 5) ipsilateral to known cancers and confirmed histopathology.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T dynamic contrast-enhanced fat-suppressed T1-weighted fast spoiled gradient-echo.

ASSESSMENT

Three radiologists blinded to pathology independently reviewed MRI features (distribution, internal enhancement pattern, and enhancement kinetics) of NME, locations relative to index cancers (contiguous, non-contiguous, and different quadrants), associated mammographic calcifications, lymphovascular invasion (LVI), axillary node metastasis, and radiology-pathology correlations. Clinical factors, NME features, and cancer characteristics were analyzed for associations with NME malignancy.

STATISTICAL TESTS

Fisher's exact, Chi-square, Wilcoxon rank sum tests, and mixed-effect multivariable logistic regression were used. Significance threshold was set at P < 0.05.

RESULTS

Overall NME malignancy rate was 48.5% (49/101). Contiguous NME had a significantly higher malignancy rate (86.7%) than non-contiguous NME (25.0%) and NME in different quadrants (10.7%), but no significant difference was observed by distance from cancer for non-contiguous NME, P = 0.68. All calcified NME lesions contiguous to the calcified index cancer were malignant. NME was significantly more likely malignant when index cancers were masses compared to NME (52.9% vs. 21.4%), had mammographic calcifications (63.2% vs. 39.7%), LVI (81.8% vs. 44.4%), and axillary node metastasis (70.8% vs. 41.6%). NME features with highest PPVs were segmental distribution (85.7%), clumped enhancement (66.7%), and nonpersistent kinetics (77.1%). On multivariable analysis, contiguous NME, segmental distribution, and nonpersistent kinetics were associated with malignancy.

DATA CONCLUSION

Malignancy discriminators of ipsilateral NME on staging MRI included contiguous location to index cancers, segmental distribution, and nonpersistent kinetics.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Evaluation of Features in Probably Benign and Malignant Nonmass Enhancement in Breast MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a highly sensitive breast imaging modality in detecting breast carcinoma. Nonmass enhancement (NME) is uniquely seen on MRI of the breast. The correlation between NME features and pathologic results has not been extensively explored. Our goal was to evaluate the characteristics of probably benign and suspicious NME lesions in MRI and determine which features are more associated with malignancy. We performed a retrospective research after approval by the hospital ethics committee on women who underwent breast MRI from March 2017 to March 2020 and identified 63 lesions of all 400 NME that were categorized as probably benign or suspicious according to the BI-RADS classification (version 2013). MRI features of NME findings including the location, size, distribution and enhancement pattern, kinetic curve, diffusion restriction, and also pathology result or 6-12-month follow-up MRI were evaluated and analyzed in each group (probably benign or suspicious NME). Vacuum-guided biopsies (VAB) were performed under mammographic or sonographic guidance and confirmed with MRI by visualization of the inserted clips. Segmental distribution and clustered ring internal enhancement were significantly associated with malignancy (p value<0.05), while linear distribution or homogeneous enhancement patterns were associated with benignity (p value <0.05). Additionally, the plateau and washout types in the dynamic curve were only seen in malignant lesions (p value <0.05). The presence of DWI restriction in NME lesions was also found to be a statistically important factor. Understanding the imaging findings of malignant NME is helpful to determine when biopsy is indicated. The correlation between NME features and pathologic results is critical in making appropriate management.

Pathology of MRI and second-look ultrasound detected multifocal breast cancer

INTRODUCTION

Targeted second-look ultrasound (US) is often performed following MRI of the breast to determine if an MRI-detected lesion is visible on US and thus amenable to US-guided biopsy. This study aimed to assess the pathology of lesions detected and biopsied on the second-look US. In particular, for multifocal cancers, whether the pathology of additional lesions detected by second-look US is different to the index lesion.

METHODS

Multicentre single-institution retrospective study of 300 consecutive cases of second-look US biopsies from August 2017 to April 2022 was performed, with their histopathology and imaging characteristics recorded. For multifocal cancers, Wilcoxon Signed Ranks Tests were used to compare differences between the index and additional lesions in the histopathology category (i.e., high-risk benign, precursor or malignant) and BRE grade.

RESULTS

69 multifocal cancers were detected. For the purposes of this study, additional lesions were considered more invasive if they were of a higher histopathological category or BRE grade, or demonstrated lymphovascular invasion when the primary lesion did not. 15/69 additional lesions were not seen on the initial mammogram/tomography or ultrasound, seen on subsequent MRI and second look US, and were less invasive than the index lesion. 3/69 additional lesions were more invasive than their index lesions. Wilcoxon Signed Ranks test showed additional lesions were of either similar or lesser invasiveness compared to index lesions (z= -3.207, p = 0.001) in the histopathological category, and the same or lower BRE grade (z= -2.972, p = 0.003).

CONCLUSION

In multifocal breast cancers, additional lesions detected on MRI and second-look US have the same or less invasive histopathology compared to the index lesion.

How Well Does Non-mass Enhancement Correlate With DCIS/Invasive Cancer?

INTRODUCTION

Contiguous non-mass enhancement (NME) often coexists with a solid tumor component on MRI, but it can be challenging to predict whether NME represents invasive breast cancer, ductal carcinoma in situ (DCIS), benign disease, or biopsy site reaction. The purpose of this study was to determine the association between the size/extent of NME and the presence of invasive cancer and/or DCIS on final pathology.

METHODS

This was a single institution retrospective analysis of a prospectively maintained breast cancer registry (2010-2020). Female patients who underwent surgical resection were included if they had a diagnosis of invasive breast cancer (with or without DCIS) and had an MRI showing both a solid mass and contiguous NME. The size of NME on MRI was compared with the size of invasive cancer and/or DCIS on the final pathology.

RESULTS

From a total of 3443 patients, 225 patients were included. 86.2% had invasive ductal carcinoma (IDC), and 12.0% had invasive lobular carcinoma 76.9% were ER+, 16.4% were HER2+, and 13.3% were triple negative breast cancer (TNBC). 18.7% received neoadjuvant chemotherapy (NCT) of whom 31% achieved a complete radiographic/pathologic response. Pearson correlation coefficients (r) between the size of NME and invasive cancer/DCIS showed a strong and positive correlation of MRI NME with DCIS on pathology in patients without NCT. Subgroup analysis showed the strongest correlations for NME and DCIS among non-white (r = .70) and HER2 + patients (r = .74) who did not receive NCT.

CONCLUSIONS

Strong correlations between NME and DCIS were found for HER2 + disease and non-white patients, but only modest correlations were found for other patient/disease characteristics. These correlations may impact decisions in surgical approach.

Sixteen-Year Institutional Review of Magnetic Resonance Imaging-Guided Breast Biopsies: Trends in Histologic Diagnoses With Radiologic Correlation

Background

Breast magnetic resonance imaging (MRI) is an important imaging tool for the management of breast cancer patients and for screening women at high risk for breast cancer.

Objectives

To examine long-term trends in the distribution of histologic diagnoses obtained from MRI-guided breast biopsies.

Design

Retrospective analysis.

Methods

We retrospectively reviewed the distribution of histologic diagnoses of MRI-guided breast biopsies from 2004 to 2019. All cases underwent central pathology review and lesions were classified based on the most prominent histologic finding present. Magnetic resonance imaging features were extracted from radiology reports when available and correlated with pathology diagnoses.

Results

Four hundred ninety-four MRI-guided biopsies were performed on 440 patients; overall, 73% of biopsies were benign and 27% were malignant. The annual percentages of benign and malignant diagnoses remained similar throughout the 16-year period. Of the benign entities commonly identified, the percentage of benign papillary and sclerosing lesions detected in the benign biopsies increased significantly (13% in 2004-2011 vs 31% in 2012-2019, P = .03). The mean size of malignant lesions was larger than benign lesions (30.1 mm compared with 14.2 mm, P = .045); otherwise, there were no distinguishing radiologic features between benign and malignant lesions.

Conclusion

The specificity of breast MRI remained constant over a 16-year period; however, there was a shift in the distribution of benign diagnoses with increased detection and biopsy of benign papillary and sclerosing lesions. Monitoring the distribution of breast MRI biopsy diagnoses over time with radiology-pathology correlation might improve the suboptimal specificity of breast MRI.

Artificial intelligence in breast cancer: application and future perspectives

Breast cancer is one of the most common cancers and is one of the leading causes of cancer-related deaths in women worldwide. Early diagnosis and treatment are the key for a favorable prognosis. The application of artificial intelligence technology in the medical field is increasingly extensive, including image analysis, automated diagnosis, intelligent pharmaceutical system, personalized treatment and so on. AI-based breast cancer imaging, pathology and adjuvant therapy technology cannot only reduce the workload of clinicians, but also continuously improve the accuracy and sensitivity of breast cancer diagnosis and treatment. This paper reviews the application of AI in breast cancer, as well as looks ahead and poses challenges to the future development of AI for breast cancer detection and therapeutic, so as to provide ideas for future research.

The morphologic spectrum of lobular carcinoma in situ (LCIS) observations on clinical significance, management implications and diagnostic pitfalls of classic, florid and pleomorphic LCIS

Lobular carcinoma in situ (LCIS) is a non-invasive proliferation of atypical dyscohesive epithelial cells characterized by loss or functional alteration of E-cadherin-mediated cell adhesion. The morphologic spectrum of LCIS encompasses classic (C-LCIS), florid (F-LCIS) and pleomorphic LCIS (P-LCIS), as recently defined by the World Health Organization (WHO) Expert Consensus Group. Atypical lobular hyperplasia (ALH) is also part of this spectrum.This article highlights the morphologic and immunohistochemical features of the three forms of LCIS and summarizes their management implications and prognosis, with emphasis on F-LCIS and P-LCIS.

Fibrocystic Changes of the Breast: Radiologic-Pathologic Correlation of MRI

Breast MRI provides high sensitivity but modest positive predictive value for identifying breast cancers, with approximately 75% of MRI-guided biopsies returning benign pathologies. Fibrocystic change (FCC) is a descriptive term used colloquially by many radiologists (and falling out of favor with many pathologists) to refer to several benign entities encountered in the breast. Many of the benign entities believed to comprise FCC can show enhancement on MRI. Recognizing the pathologic correlates of these enhancing lesions should help guide management after such a result on MRI-guided biopsy. Premenopausal women may present with clinical symptoms attributed to FCC, including pain, nipple discharge, breast lumps, or discrete masses. Benign entities associated with FCC include proliferative lesions such as usual ductal hyperplasia and sclerosing adenosis, and nonproliferative lesions including cysts, apocrine metaplasia, and stromal fibrosis. Fibrocystic change can be diffuse or focal. Diffuse FCC usually presents as non-mass enhancement (NME), often with persistent kinetics. Focal FCC can present as an irregular mass or focus with variable enhancement patterns including washout kinetics. Following a benign concordant MRI-guided biopsy result of one or more of the above entities, follow-up with MRI in 12 months is reasonable. Accurate radiologic-pathologic correlation can be achieved when careful review of histologic findings is carried out in the context of MRI features.

Unveiling the histopathologic spectrum of MRI-guided breast biopsies: an institutional pathological-radiological correlation

PURPOSE

Breast magnetic resonance imaging (MRI) has high sensitivity but suffers from low specificity, resulting in many benign breast biopsies for MRI-detected lesions. We sought to compare histologic findings between patients who underwent MRI-guided breast biopsy versus biopsy via other imaging modalities as well as to examine features associated with malignancy in the MRI cohort to help inform MRI-biopsy practice.

METHODS

A 2-year (2018-2019) retrospective review of breast biopsies at our enterprise was conducted. Biopsies were categorized as stereotactic, ultrasound, MRI, or palpation guided. Pathology was categorized as benign (further divided into nine categories), atypical, or malignant (subdivided into in situ and invasive carcinoma). Pathology was compared between biopsy groups. Clinical, pathologic, and imaging features were compared between pathology groups within the MRI cohort.

RESULTS

5828 biopsies from 4154 patients were reviewed, including 548 MRI-guided biopsies with stratification of MRI-biopsy pathology as follows: 69% benign, 13.8% atypical, and 17.2% malignant. Among benign MRI biopsies, there was higher frequency of "clustered cysts with papillary apocrine metaplasia" (56/548; 10.2%) and lower rate of fibroadenoma/fibroadenomatous change (55/548; 10%) compared to other modalities (158 or 3% and 1144 or 21.7% of 5280 biopsies, respectively). Multivariate analysis revealed indication of breast cancer (p < .0001), ipsilateral cancer (p < .0001) and rapid initial phase kinetics (p = .017) to remain significantly associated with malignant MRI-biopsy pathology.

CONCLUSIONS

A concurrent or recent breast cancer diagnosis was most predictive of malignancy on MRI-guided breast biopsy. Combined MRI feature evaluation and radiologic-pathologic concordance activities may allow for prognostic refinement and improved risk stratification.

Nonmass enhancement lesions of the breast on core needle biopsy: outcomes, frequency of malignancy, and pathologic findings

Nonmass enhancement (NME) on breast magnetic resonance imaging (MRI) is defined as an area whose internal enhancement characteristics can be distinguished from the normal surrounding breast parenchyma, without an associated mass in the Breast Imaging Reporting and Data System lexicon. In this study, we evaluated the pathologic correlates of NME lesions of the breast identified on MRI at our institution, including the frequency of atypical or malignant lesions in the core needle biopsies (CNBs), performed after such a radiologic finding. A retrospective study was performed on all CNBs performed for NME on breast MRI between 2010 and 2019. A total of 443 biopsies from 411 patients were identified, comprising 5.5% of all CNBs over the study period. The pathologic diagnoses were benign in the majority of the biopsies (68.0%), whereas 11.5% and 20.5% of the cases were atypical and malignant lesions, respectively. Of the malignant cases, 69.2% were ductal carcinoma in situ (DCIS) and 30.8% were invasive carcinomas. The most common invasive cancer was invasive ductal carcinoma (50%), followed by invasive lobular carcinoma (39.3%). NME identified on breast MRI carried a significant (32%) risk of atypia and malignancy in our cohort, which confirms that biopsy evaluation of these lesions is warranted. DCIS was the most commonly identified malignancy. Notably, among invasive cancers, invasive lobular carcinoma was identified at a substantially higher frequency that would be expected for that histotype.

Time density curve of dynamic contrast-enhanced computed tomography correlates with histological characteristics of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is characterized by an infiltrative growth pattern with intense desmoplastic stroma comprised of cancer-associated fibroblasts (CAFs). Additionally, the histological characteristics are considered to play a vital role in the poor prognosis of PDAC. However, the density of cancer cells, degree of desmoplasia and vascular proliferation varies in individual cases. We hypothesized that preoperative radiological images would reflect histological characteristics, such as cancer cell density, CAF density and microvessel density. To clarify the association between the histological characteristics and radiological images of PDAC, the cancer cell density, CAF density and microvessel density from surgical specimens were measured with immunostaining, and the time density curve of dynamic contrast-enhanced computed tomography (CECT) was analyzed. Overall, the initial slope between non-enhanced and arterial phases was correlated with microvessel density, and the second slope between arterial and portal phases was correlated with CAF and cancer cell densities. In conclusion, the present study suggested the possibility of estimating cancer cell, CAF and microvessel densities using the TDC of dynamic CECT.

Histopathologic Correlates of Nonmass Enhancement Detected by Breast Magnetic Resonance Imaging

CONTEXT.—

Dynamic, contrast-enhanced magnetic resonance imaging (MRI) is a highly sensitive imaging modality used for screening and diagnostic purposes. Nonmass enhancement (NME) is commonly seen on MRI of the breast. However, the pathologic correlates of NME have not been extensively explored. Consequently, concordance between MRI and pathologic findings in such cases may be uncertain and this uncertainty may cause the need for additional procedures.

OBJECTIVE.—

To examine the histologic alterations that correspond to NME on MRI.

DESIGN.—

We performed a retrospective search for women who underwent breast MRI between March 2014 and December 2016 and identified 130 NME lesions resulting in biopsy. The MRI findings and pathology slides for all cases were reviewed. The follow-up findings on any subsequent excisions were also noted.

RESULTS.—

Among the 130 cases, the core needle biopsy showed 1 or more benign lesions without atypia in 80 cases (62%), atypical lesions in 21 (16%), ductal carcinoma in situ in 22 (17%), and invasive carcinoma in 7 (5%). Review of the imaging features demonstrated some statistically significant differences in lesions that corresponded to malignant lesions as compared with benign alterations, including homogeneous or clumped internal enhancement, type 3 kinetics, and T2 dark signal; however, there was considerable overlap of features between benign and malignant lesions overall. Of 130 cases, 54 (41.5%) underwent subsequent excision with only 6 cases showing a worse lesion on excision.

CONCLUSIONS.—

This study illustrates that NME can be associated with benign, atypical, and/or malignant pathology and biopsy remains indicated given the overlap of radiologic features.

Precision pathology as applied to breast core needle biopsy evaluation: implications for management

With the shift to de-escalation of therapy for some breast cancers and fewer surgical excisions for high-risk lesions identified on breast imaging studies at one end of the spectrum, and the greater use of neoadjuvant systemic therapy at the other end, pathologists are ever more critical in guiding management decisions for women with breast disease following core needle biopsy. One important consequence of this shift in management paradigms is the elimination of the opportunity for a "second-look" with the excision specimen to confirm or refine the diagnosis rendered on core needle biopsy. Thus, not only is there the imperative for accuracy and precision of core needle biopsy diagnoses, increasingly it is the only opportunity for that diagnosis.

The role of breast MRI in newly diagnosed breast cancer: An evidence-based review

The utility of pre-operative MRI in patients with newly diagnosed invasive breast cancer remains a topic of debate. Those who advocate for pre-treatment imaging contend that MRI may detect additional disease not otherwise appreciated on conventional imaging and may provide more accurate staging information to guide treatment. Additionally, it has been proposed that MRI can be utilized to assess extent of residual disease in patients undergoing neoadjuvant chemotherapy. Conversely, those in opposition maintain that routine pre-operative MRI subjects patients to unnecessary ipsilateral mastectomies and prophylactic contralateral mastectomies with no difference in oncologic outcome. When stratified based on tumor biology and patient characteristics, the data suggests that pre-treatment MRI may be advantageous in certain subsets when compared to the general cohort of breast cancer patients. This review recapitulates the current literature on the impact of breast MRI on the surgical management and outcomes of newly diagnosed breast cancer.

Application of MRI Radiomics-Based Machine Learning Model to Improve Contralateral BI-RADS 4 Lesion Assessment

Objective

This study aimed to explore the potential of magnetic resonance imaging (MRI) radiomics-based machine learning to improve assessment and diagnosis of contralateral Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions in women with primary breast cancer.

Materials and Methods

A total of 178 contralateral BI-RADS 4 lesions (97 malignant and 81 benign) collected from 178 breast cancer patients were involved in our retrospective dataset. T1 + C and T2 weighted images were used for radiomics analysis. These lesions were randomly assigned to the training (n = 124) dataset and an independent testing dataset (n = 54). A three-dimensional semi-automatic segmentation method was performed to segment lesions depicted on T2 and T1 + C images, 1,046 radiomic features were extracted from each segmented region, and a least absolute shrinkage and operator feature selection method reduced feature dimensionality. Three support vector machine (SVM) classifiers were trained to build classification models based on the T2, T1 + C, and fusion image features, respectively. The diagnostic performance of each model was evaluated and tested using the independent testing dataset. The area under the receiver operating characteristic curve (AUC) was used as a performance metric.

Results

The T1+C image feature-based model and T2 image feature-based model yielded AUCs of 0.71 ± 0.07 and 0.69 ± 0.07 respectively, and the difference between them was not significant (P > 0.05). After fusing T1 + C and T2 imaging features, the proposed model’s AUC significantly improved to 0.77 ± 0.06 (P < 0.001). The fusion model yielded an accuracy of 74.1%, which was higher than that of the T1 + C (66.7%) and T2 (59.3%) image feature-based models.

Conclusion

The MRI radiomics-based machine learning model is a feasible method to assess contralateral BI-RADS 4 lesions. T2 and T1 + C image features provide complementary information in discriminating benign and malignant contralateral BI-RADS 4 lesions.

MRI-guided core needle biopsy of the breast: Radiology-pathology correlation and impact on clinical management

OBJECTIVE

Breast MRI is used to screen high-risk patients and determine extent of disease in breast cancer (BC) patients. The goal of this study was to determine the pathologic correlates of breast MRI abnormalities biopsied under MRI guidance.

METHODS

We retrospectively identified 101 MRI-guided core needle biopsies (CNB) of the breast from 79 women over a 4-year period. MRI-detected lesions biopsied with ultrasound or stereotactic guidance were excluded. MRI studies and pathology were reviewed by breast radiologists and pathologists.

RESULTS

Of the 79 patients, 72 (91%) had a history of prior (n = 13) or concurrent (n = 59) BC. There were 101 MRI abnormalities: 60 (59%) with non-mass enhancement (NME) and 41 (41%) with mass enhancement. Pathology was benign in 83/101 (82%), including in the majority of NME lesions (43/60, 72%). The most common benign findings were: fibrocystic changes (FCC) (49%), sclerosing lesions (13%), and fibroadenoma (FA) (9%). There were 18 (18%) malignant diagnoses: 8 (44%) invasive lobular carcinoma (ILC), 7 (39%) ductal carcinoma in situ (DCIS), and 3 (17%) invasive ductal carcinoma (IDC). Of the 18 malignant diagnoses, 16 (89%) occurred in 14 unique patients with concurrent BC. Based on the malignant MRI-guided CNB, 6 (46%) of these patients had additional (sentinel lymph node biopsy or contralateral breast surgery) or more extensive (wider lumpectomy) surgery.

CONCLUSION

In this series, most MRI-guided CNB of the breast were benign. The vast majority of malignant diagnoses occurred in patients with concurrent BC and frequently resulted in changes in clinical management.

Non-invasive lobular neoplasia of the breast: Morphologic features, clinical presentation, and management dilemmas

The designation of noninvasive lobular neoplasia applies to atypical epithelial proliferations composed of noncohesive cells secondary to loss or functional alteration of E-cadherin-mediated cell adhesion. The morphologic spectrum of noninvasive lobular neoplasia encompasses atypical lobular hyperplasia (ALH) and classic lobular carcinoma in situ (classic LCIS) and two LCIS variants, namely florid LCIS (F-LCIS) and pleomorphic LCIS (P-LCIS), as defined in the World Health Organization (WHO) Classification of Tumors of the Breast 5th ed. Herein, we review the morphologic, immunohistochemical, and molecular features of noninvasive lobular neoplasia, with special emphasis on F-LCIS and P-LCIS. We also review imaging features, management at core needle biopsy, upgrade rates at surgical excision, and clinical management dilemmas.

Differential diagnosis of plasma cell mastitis and invasive ductal carcinoma using multiparametric MRI

Background

Evaluate the potential of multiparametric magnetic resonance imaging (MRI) for the differential diagnosis of plasma cell mastitis (PCM) and invasive ductal carcinoma (IDC).

Methods

A total of 465 female patients, including 197 PCM (42.4%) and 268 IDC (57.6%), were examined using breast MRI scanning using routine sequences, dynamic contrast-enhanced MRI (DCE-MRI), diffusion-weighted imaging (DWI) and MR spectroscopy (MRS). The MRI features of PCM and IDC lesions were analyzed and compared to the histological results.

Results

Compared to IDC, the PCM lesions were more frequent in the subareolar regions, hyperintense on T2WI (P<0.01) and showed an initial signal increase ≤90%, a persistent and plateau pattern of time-intensity curves, non-mass enhancement, multiple rim enhancements, central hyperintensity on DWI, a higher ADC value, and total choline (tCho) peak negative and tCho peak integral <29.95 AU (P<0.01). The following breast-associated findings were also observed frequently in PCM: Ipsilateral breast enlargement, nipple retraction, skin thickening, peripheral edema and axillary lymphadenopathy. However, no significant difference was observed between the two groups for the shape, border and adjacent vessel signs of the lesion.

Conclusions

Some of the MRI features of PCM and IDC lesions were different. An integrated analysis of these multiparametric MRI features can thus assist in the differential diagnosis of PCM and IDC lesions.