Augmenting breast cancer diagnosis: Incorporating MRI for the assessment of major molecular subtypes

INTRODUCTION

Breast cancer (BC) is one of the most commonly encountered cancers in women around the world. It is a diverse medical disorder with multiple molecular subtypes that respond differently to therapy and have different prognoses. Patients with the same stage of cancer and similar histological findings can present with different clinical features having varying prognosis. Luminal A, Luminal B, Human epidermal growth factor receptor 2 (HER2) enriched, and triple-negative molecular subtypes were identified using novel technologies in expression analysis with DNA microarray.^[1,2] The precise identification of these subtypes is crucial for tailoring appropriate treatment strategies and improving patient outcomes. Dynamic contrast-enhanced magnetic resonance imaging (DCEMRI) is an excellent imaging technique for determining the extent of disease in BC patients prior to surgery. DECMRI with gadolinium-based contrasts is now the most sensitive identification tool for diagnosis, and it can be used coupled with mammography and ultrasound (USG). It aids in the detection of lesions not visible using other approaches.

Luminal A has a low proliferation index (Ki-67) and accounts for 50–60% of breast cancers. It has the best outlook. Luminal B has a high Ki-67 index expression and accounts for 20% of BC cases. In comparison to Luminal A, it has a bad prognosis. HER2 is not overexpressed in Luminal B. HER2+ types account for 10% of BCs and are distinguished by poor hormone receptor expression. They have higher HER2/neu gene expression. The triple-negative subtype accounts for 7–16% of breast cancer cases and is distinguished by the absence of hormone receptor expression and low HER2+ expression. It demonstrates increased expression of high-molecular-weight cytokeratin genes. It is a less differentiated invasive carcinoma that accounts for 70% of BCs. HER2+ and triple-negative cancers respond better to chemotherapy but have lower survival rates.^[3–5]

BC has surpassed lung cancer as the most prevalent global cancer in 2020, with around 2.3 million new cases, accounting for 11.7% of all cancer cases.^[6] The global burden may exceed 2 million by 2030.^[7] From 1965 to 1985, the frequency increased by approximately 50%.^[8] Between 1990 and 2016, the incidence of BC in India grew by 39.1%, with increases recorded in all states.^[9] According to Globocan data from 2020, BC accounted for 13.5% of all malignancies and 10.6% of all fatalities.^[10] There have been few investigations on the use of DCEMRI on breast cancer. As a result, the purpose of this study was to look at the effectiveness of DCE MRI in assessing molecular subtypes of BC.

The current study was done at our hospital NRI Medical College and General Hospital, Chinakakani, which is equipped with 1,100 beds. All necessary facilities were available in our department for checking all the study parameters. Around 80 women presented to the Radiodiagnosis department with suspected breast carcinoma during the study duration. From these patients, study patients were recruited.

Aim: To assess molecular subtypes of breast cancer using DCE-MRI.

MATERIALS AND METHODS

This study was done in the Department of Radiology, NRI Medical College, Chinakakani.

Study period: 12 months; from April 2021 to April 2022.

Type of study: Cross-sectional, observational study.

Source of data: After getting permission from the Institutional Ethics Committee (IEC), patients with suspected breast masses referred to the radiology department were taken as a study sample.

Sampling procedure: Convenience sampling was employed. It is a kind of nonprobability sampling. The sample was drawn from the part of the population that is close to hand or convenient.

Sample size calculation: As per the American Cancer Society, the prevalence of breast cancer among invasive cancers was 30% among women.^[11]

The sample size is calculated as N = Z²PQ/E².

N = sample size, P = prevalence, P = 30%, Q = 1–P, E = Error: 10%, 85% confidence limits, N = 44. Forty-four is the minimum size.

So, we included 50 patients in this study, considering a few losses to follow-up. All 50 patients provided consent for the study.

Results

Molecular subtype: 36% patients were found to be Luminal A, 24% as basal, 20% as HER2 enriched and another 20% as Luminal B type of molecular subtypes in our study with 50 patients.

Association between shape and molecular subtype: [Table 1] [Figure 1] There was a significant association between shape and molecular subtype. It was irregular in most of the luminal type of carcinoma, round in the basal type.

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Figure 1:

Shape and molecular subtypes.

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Association between margin and molecular subtype: [Table 2] There was no significant association between margin and molecular subtypes. However circumscribed margins were more commonly seen in luminal subtypes.

Association between internal enhancement and molecular subtype: [Table 3] [Figure 2] There was a significant association between internal enhancement and molecular subtype. Rim enhancement was more commonly seen in a basal subtype.

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Figure 2:

Internal enhancement and molecular subtypes.

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Association between kinetic curve assessment and molecular subtype: [Table 4] There was no significant association between kinetic curve assessment and molecular subtype.

Association between volume and molecular subtypes: [Table 5] There was a significant association between volume and molecular subtypes, as per ANOVA analysis. Tumor volume was calculated by approximating the tumor into an ellipsoid and taking the maximum dimensions of the tumor in the formula: V ≈ (4/3) × π × (L/2) × (W/2) × (H/2). L = length, W = width, and H = height of the tumor.

Association between T2 SI and molecular subtypes: [Table 6] There was a significant association between T2 signal intensity and molecular subtypes, as per chi-square analysis (p = 0.01)

Association between DWI and molecular subtypes: [Table 7] There was no significant association between DWI and molecular subtypes, as per ANOVA analysis. Illustrative images from our observational study are depicted in [Figures 3a, 3b, 4a, 4b, 5a, 5b, 6a, 6b].

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Figure 3a:

Invasive ductal carcinoma – nonspecial type. Luminal A molecular subtype. A 74-year-old female with a lump in the left breast. MRI revealed an irregular mass with noncircumscribed margins. It is predominantly hyperintense on T2 and STIR images, and shows diffusion restriction with ADC values in the range of 0.5–0.8 × 10^–3 mm²/s. Adjacent fibroglandular tissue shows mild STIR hyperintensity with no enhancement on contrast administration. It is showing moderate heterogeneous enhancement.

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Figure 3b:

Kinetic curve analysis shows rapid uptake in the initial phase. Persistent and plateau type of curve in delayed phase – Type I and II intensity-time curves.

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Figure 4a:

Invasive ductal carcinoma – nonspecial type. Medullary carcinoma. Luminal B molecular subtype. A 35-year-old female with a lump in the right breast. MRI revealed round to ovoid, noncircumscribed mass in posterior third depth at 1–2 o’clock position. It is predominantly hyperintense on T2 and STIR images with central cystic foci and shows diffusion restriction with ADC values in the range of 0.8–1.2 × 10^–3 mm²/sec. It is showing central heterogeneous enhancement. Perilesional STIR hyperintensity shows minimal enhancement in contrast study. The mass is abutting the pectoralis muscle fibers posteriorly with few enhancing superficial muscles – suggestive of pectoralis muscle invasion.

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Figure 4b:

Kinetic curve analysis shows rapid uptake in the initial phase. Plateau type of curve in delayed phase – Type II intensity-time curve.

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Figure 5a:

Invasive ductal carcinoma – nonspecial type. HER2 enriched molecular subtype. A 46-year-old female with a lump in the right axilla. MRI revealed enlarged right breast. An irregular shaped mass with non-circumscribed margins in the middle third depth of the right breast. The mass is predominantly hyperintense on T2 and STIR images, and shows diffusion restriction with ADC values in the range of 0.3–0.4 × 10^–3 mm²/s. It is showing moderate heterogeneous enhancement. Diffuse STIR hyperintensity in the fibroglandular tissue, pectoralis muscle, and subcutaneous planes.

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Figure 5b:

Kinetic curve analysis shows rapid uptake in the initial phase. Plateau and washout type of curve in delayed phase – Type II and III kinetic curves.

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Figure 6a:

Invasive ductal carcinoma – nonspecial type. Triple negative molecular subtype. A 72-year-old female with a lump in the right breast. MRI revealed exophytic, round circumscribed mass in the lower inner quadrant and the anterior third depth. It is showing T2 and STIR hyperintense signal with diffusion restriction and low ADC. Following contrast administration, it is showing rim enhancement with heterogeneous enhancement within. Perilesional and pectoralis edema noted in the form of STIR hyperintensities.

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Figure 6b:

Kinetic curve analysis revealed rapid uptake in the initial phase. Washout type of curves in delayed phase – Type III intensity – time curve.

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Discussion

This was a cross-sectional, observational study undertaken at NRI Medical College & General Hospital, Chinakakani, a well-equipped tertiary care hospital. It lasted a year, from April 2021 to April 2022.

Patients over the age of 18 with suspicious breast masses who signed the informed consent form were included.

Patients with incomplete data, claustrophobia, cardiac pacemakers, artificial heart valves, cochlear implants, or any metallic implants, as well as those who were pregnant or lactating, were excluded.

According to the sample size, 50 patients were included.

All patients’ age, gender, mass, related characteristics, mass location, depth, margins, internal enhancement, ki67 index, MRI diagnosis, DWI, molecular subtype, kinetic curve assessment, ER, PR, HER2 status, and HPE findings were evaluated.

Mean and standard deviation were used to evaluate numerical parameters. Statistical tests were done using Epi info software, Microsoft Excel 2019.

The majority of the metrics were expressed as percentages and frequencies.

Age was expressed as a mean and standard deviation.

Chi-square analysis and the ANOVA test were used to determine the relationship between form, margins, internal enhancement, tumor volume, kinetic curves, T2 signal, and DWI and molecular subtype.

Molecular subtypes

Luminal-type (which is ER- or PR-positive) breast cancer is the most common type of BC. It is classified as luminal-A and luminal-B subtypes.

It was defined by low- (Ki-67 below 20) and high- (HER2-positive or Ki-67 more than 20) proliferation subtypes.^[12–14]

Hormone receptors negative BCs include HER2-positive and basal subtypes. They were usually of higher grades with more Ki-67 indexes.^[15–19]

HER2 is over-expressed in around 20% of BC cases and is linked to a poor prognosis, but it shows a good response to HER2 therapies.^[20]

Basal-like BCs are usually triple negative BCs on semi-quantitative scoring.^[21]

BC subtype can be easily diagnosed by immunochemical staining of the biopsy sample, but receptor expression may modify during treatment.

Breast MRI provides details not only on the cross-sectional morphology of the mass but also on functional features.

CONCLUSION

Breast MR Imaging helps in determining various molecular subtypes of breast cancer, especially in Luminal A. The mass shows that noncircumscribed margins and rim enhancement were more commonly seen in TNBC subtypes.

Conventional MRI features like time-intensity curve and mean ADC may have a limited role in predicting breast cancer subtypes. Sophisticated evaluation of tumor heterogeneity, more studies on recently introduced techniques, and standardized interpretation of images can improve noninvasive breast cancer molecular subtype classification.

This form of subtype classification also aids in the provision of customized treatment for breast cancer patients.