OBJECTIVE: This study aims to review the typical and relatively atypical CXR manifestations of COVID-19 pneumonia in a tertiary care hospital.
METHODS: The CXRs of 136 COVID-19 patients confirmed through real-time RT-PCR from March to May 2020 were reviewed. A literature search was performed using PubMed.
RESULTS: A total of 54 patients had abnormal CXR whilst the others were normal. Typical CXR findings included pulmonary consolidation or ground-glass opacities in a multifocal, bilateral peripheral, or lower zone distribution, whereas atypical CXR features comprised cavitation and pleural effusion.
CONCLUSION: Typical findings of COVID-19 infection in chest computed tomography studies can also be seen in CXR. The presence of atypical features associated with worse disease outcome. Recognition of these features on CXR will improve the accuracy and speed of diagnosing COVID-19 patients.
CASE REPORT: An elderly lady presented with an enlarging painful left breast lump for 1 year. Palpable left breast lump noted on clinical examination. Mammography demonstrated a high density, oval lesion with a partially indistinct margin. Corresponding ultrasound showed a large irregular heterogeneous lesion with solid-cystic areas. Histopathology showed atypical spindle-shaped cells which stained positive for cytokeratins and negative for hormone and human epidermal growth factor receptors, which favours spindle cell metaplastic carcinoma. Left mastectomy and axillary dissection were performed, and the final diagnosis was consistent with metaplastic spindle cell carcinoma.
CONCLUSION: Spindle cell carcinoma of the breast is a rare aggressive histological type of carcinoma which may present with benign features on imaging. Tissue diagnosis is essential for prompt diagnosis with multidisciplinary team discussion to guide management and improve patient's outcome.
DISCUSSION: As surgery and radiotherapy alter the appearance of the breasts, distinguishing between recurrence and benign post-surgical changes can be challenging radiologically due to overlapping features. Despite this, differentiation between these two entities is usually possible by recognizing characteristic features of post-treatment sequelae and the evolution of the appearance of the conservatively treated breast by comparing interval findings on serial studies.
CONCLUSION: This pictorial review aims to describe the typical and unusual features of post-treated breasts in the multimodality imaging workup of an established breast care centre in a teaching hospital in Malaysia.
MATERIALS AND METHODS: Breast lesions and axillae of 107 patients were assessed using B-mode ultrasound and SWE. Histopathology was the diagnostic gold standard.
RESULTS: In metastatic axillary lymph nodes, qualitative SWE using color patterns had the highest area under curve (AUC) value, followed by B-mode Ultrasound (cortical thickening >3 mm) and quantitative SWE using Emax of 15.2 kPa (AUC of 81.3%, 70.1%, and 61.2%, respectively). Qualitative SWE exhibited better diagnostic performance than the other two parameters, with sensitivity of 96.0% and specificity of 56.1%. Combination of B-mode Ultrasound (using cortical thickness of >3 mm as cut-off point) and qualitative SWE (Color patterns of 2 to 4) showed sensitivity of 71.6%, specificity of 95%, PPV of 96%, NPV of 66.7%, and accuracy of 80.4%.
CONCLUSION: Qualitative SWE assessment exhibited higher accuracy compared to quantitative values. Qualitative SWE as an adjunct to B-mode ultrasound can further improve the diagnostic accuracy of metastatic ALN in breast cancer.
METHODS: We performed a literature search of published articles on the application of MRI phenotypic features in invasive breast cancer molecular subtype classifications by radiologists' interpretation on Medline Complete, Pubmed, and Google scholar from 1st January 2000 to 31st March 2021. Of the 1453 literature identified, 42 fulfilled the inclusion criteria.
RESULTS: All studies were case-controlled, retrospective study and research-based. The majority of the studies assessed the MRI features using American College of Radiology- Breast Imaging Reporting and Data System (ACR-BIRADS) classification and using dynamic contrast-enhanced (DCE) kinetic features, Apparent Diffusion Coefficient (ADC) values, and T2 sequence. Most studies divided invasive breast cancer into 4 main subtypes, luminal A, luminal B, HER2, and triple-negative (TN) cancers, and used 2 readers. We present a summary of the radiologists' extracted breast MRI phenotypical features and their correlating breast cancer subtypes classifications. The characteristic features are morphology, enhancement kinetics, and T2 signal intensity. We found that the TN subtype has the most distinctive MRI features compared to the other subtypes and luminal A and B have many similar features.
CONCLUSION: The MRI features which are predictive of each subtype are the morphology, internal enhancement features, and T2 signal intensity, predominantly between TN and the rest. Radiologists' visual interpretation of some of MRI features may offer insight into the respective invasive breast cancer molecular subtype. However, current evidence are still limited to "suggestive" features instead of a diagnostic standard. Further research is recommended to explore this potential application, for example, by augmentation of radiologists' visual interpretation by artificial intelligence.
METHODS: This cross-sectional study of women who underwent DBT and ABUS from December 2019 to March 2022 included opportunistic and targeted screening cases, as well as symptomatic women. Breast density, Breast Imaging Reporting and Data System categories and histopathology reports were collected and compared. The PPV3 (proportion of examinations with abnormal findings that resulted in a tissue diagnosis of cancer), biopsy rate (percentage of biopsies performed) and cancer detection yield (number of malignancies found by the diagnostic test given to the study sample) were calculated.
RESULTS: A total of 1089 ABUS examinations were performed (age range: 29-85 y, mean: 51.9 y). Among these were 909 screening (83.5%) and 180 diagnostic (16.5%) examinations. A total of 579 biopsies were performed on 407 patients, with a biopsy rate of 53.2%. There were 100 (9.2%) malignant lesions, 30 (5.2%) atypical/B3 lesions and 414 (71.5%) benign cases. In 9 cases (0.08%), ABUS alone detected malignancies, and in 19 cases (1.7%), DBT alone detected malignancies. The PPV3 in the screening group was 14.6%.
CONCLUSION: ABUS is useful as an adjunct to DBT in the opportunistic screening and diagnostic setting.
MATERIALS AND METHODS: A total of 84 patients with treatment-naïve invasive breast cancer were enrolled into this retrospective study. The tumour stroma ratio (TSR) was estimated from the amount of tumour stroma in the pathology specimen of the breast tumour. The MRI images of the patients were analysed based on Breast Imaging Reporting and Data Systems (ACR-BIRADS) for qualitative features which include T2- weighted, diffusion-weighted images (DWI) and dynamic contrast-enhanced (DCE) for kinetic features. The mean signal intensity (SI) of Short Tau Inversion Recovery (STIR), with the ratio of STIR of the lesion and pectoralis muscle (L/M ratio) and apparent diffusion coefficient (ADC) value, were measured for the quantitative features. Correlation tests were performed to assess the relationship between TSR and MRI features.
RESULTS: There was a significant correlation between the margin of mass, enhancement pattern, and STIR signal intensity of breast cancer and TSR. There were 54.76% (n = 46) in the low stromal group and 45.24% (n = 38) in the high stromal group. A significant association were seen between the margin of the mass and TSR (p = 0.034) between the L/M ratio (p <0.001), and between STIR SI of the lesion and TSR (p<0.001). The median L/M ratio was significantly higher in the high TSR group as compared to the lower TSR group (p < 0.001).
CONCLUSION: Breast cancer with high stroma had spiculated margins, lower STIR signal intensity, and a heterogeneous pattern of enhancement. Hence, in this preliminary study, certain MRI features showed a potential to predict TSR.
METHODS: Treatment-naive patients with invasive breast carcinoma were included in this retrospective study. Breast MRI features were recorded based on the American College of Radiology-Breast Imaging Reporting and Data System (ACR-BIRADS) criteria, with tumour size, and apparent diffusion coefficient value (ADC). The statistical association was tested with Pearson Chi-Square Test of Independence for categorical data or the Kruskal-Wallis/ Mann Whitney U test for numerical data between the MRI features and molecular subtype, receptor status, tumour grade, lymphovascular infiltration (LVI) and axillary lymph node (ALN). Multinomial logistic regression was used to test the predictive likelihood of the significant features. The breast cancer subtypes were determined via immunohistochemistry (IHC) and dual-color dual-hapten in-situ hybridization (D-DISH). The expression statuses of ER, PR, and HER-2, LVI, and ALN were obtained from the histopathology report. The ER / PR / HER-2 was evaluated according to the American Society of Clinical Oncology / College of American Pathologists.
RESULTS: The study included 194 patients; 41.8% (n = 81) Chinese, 40.7% (n = 79) Malay, and 17.5% (n = 34) Indian, involving 71.6%(n = 139) luminal-like, 12.9%(n = 25) HER-2 enriched, and 15.5%(n = 30) Triple-negative breast cancer (TNBC). TNBC was associated with rim enhancement (p = 0.002) and peritumoral oedema (p = 0.004). HER-2 enriched tumour was associated with larger tumour size (p = 0.041). Luminal-like cancer was associated with irregular shape (p = 0.005) with circumscribed margin (p = 0.003). Other associations were ER-negative tumour with circumscribed margin (p = 0.002) and PR-negative with round shape (p = 0.001). Tumour sizes were larger in ER-negative (p = 0.044) and PR-negative (p = 0.022). Rim enhancement was significantly associated with higher grade (p = 0.001), and moderate peritumoral oedema with positive axillary lymph node (p = 0.002).
CONCLUSION: Certain MRI features can be applied to differentiate breast cancer molecular subtypes, receptor status and aggressiveness, even in a multi-ethnic population.