Application of Artificial Intelligence (AI) System in Opportunistic Screening and Diagnostic Population in a Middle-income Nation.

OBJECTIVE: This study evaluates the effectiveness of artificial intelligence (AI) in mammography in a diverse population from a middle-income nation and compares it to traditional methods. METHODS: A retrospective study was conducted on 543 mammograms of 467 Malays, 48 Chinese, and 28 Indians in a middle-income nation. Three breast radiologists interpreted the examinations independently in two reading sessions (with and without AI support). Breast density and BI-RADS categories were assessed, comparing the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) results. RESULTS: Of 543 mammograms, 69.2% had lesions detected. Biopsies were performed on 25%(n=136), with 66(48.5%) benign and 70(51.5%) malignant. Substantial agreement in density assessment between the radiologist and AI software (κ =0.606, p < 0.001) and the BI-RADS category with and without AI (κ =0.74, p < 0.001). The performance of the AI software was comparable to the traditional methods. The sensitivity, specificity, PPV, and NPV or radiologists alone, radiologist + AI, and AI alone were 81.9%,90.4%,56.0%, and 97.1%; 81.0%, 93.1%,55.5%, and 97.0%; and 90.0%,76.5%,36.2%, and 98.1%, respectively. AI software enhances the accuracy of lesion diagnosis and reduces unnecessary biopsies, particularly for BI-RADS 4 lesions. The AI software results for synthetic were almost similar to the original 2D mammography, with AUC of 0.925 and 0.871, respectively. CONCLUSION: AI software may assist in the accurate diagnosis of breast lesions, enhancing the efficiency of breast lesion diagnosis in a mixed population of opportunistic screening and diagnostic patients. KEY MESSAGES: • The use of artificial intelligence (AI) in mammography for population-based breast cancer screening has been validated in high-income nations, with reported improved diagnostic performance. Our study evaluated the usage of an AI tool in an opportunistic screening setting in a multi-ethnic and middle-income nation. • The application of AI in mammography enhances diagnostic accuracy, potentially leading to reduced unnecessary biopsies. • AI integration into the workflow did not disrupt the performance of trained breast radiologists, as there is a substantial inter-reader agreement for BI-RADS category assessment and breast density.

MRI Breast: Current Imaging Trends, Clinical Applications, and Future Research Directions.

Magnetic Resonance Imaging (MRI) is the most sensitive and advanced imaging technique in diagnosing breast cancer and is essential in improving cancer detection, lesion characterization, and determining therapy response. In addition to the dynamic contrast-enhanced (DCE) technique, functional techniques such as magnetic resonance spectroscopy (MRS), diffusion-weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) further characterize and differentiate benign and malignant lesions thus, improving diagnostic accuracy. There is now an increasing clinical usage of MRI breast, including screening in high risk and supplementary screening tools in average-risk patients. MRI is becoming imperative in assisting breast surgeons in planning breast-conserving surgery for preoperative local staging and evaluation of neoadjuvant chemotherapy response. Other clinical applications for MRI breast include occult breast cancer detection, investigation of nipple discharge, and breast implant assessment. There is now an abundance of research publications on MRI Breast with several areas that still remain to be explored. This review gives a comprehensive overview of the clinical trends of MRI breast with emphasis on imaging features and interpretation using conventional and advanced techniques. In addition, future research areas in MRI breast include developing techniques to make MRI more accessible and costeffective for screening. The abbreviated MRI breast procedure and an area of focused research in the enhancement of radiologists' work with artificial intelligence have high impact for the future in MRI Breast.

Spindle Cell Metaplastic Breast Carcinoma.

INTRODUCTION: Metaplastic breast carcinoma is an uncommon malignancy that constitutes < 5% of all breast cancers. There are 5 subtypes which are spindle cell, squamous cell, carcinosarcoma, matrix-producing and metaplastic with osteoclastic giant cells. Spindle cell carcinoma represents approximately <0.3% of invasive breast carcinomas. It is typically a triple-negative cancer with distinct pathological characteristics, but relatively a non-conclusive on imaging findings. CASE REPORT: An elderly lady presented with an enlarging painful left breast lump for one year. Palpable left breast lump was found 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 that stained positive for cytokeratins and negative for hormone and human epidermal growth factor receptors, which favoured 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 and 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 outcomes.

Chest Radiograph (CXR) Manifestations of the Novel Coronavirus Disease 2019 (COVID-19): A Mini-review.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is highly contagious and has claimed more than one million lives, besides causing hardship and disruptions. The Fleischner Society has recommended chest X-ray (CXR) in detecting cases at high risk of disease progression, for triaging suspected patients with moderate-to-severe illness, and for eliminating false negatives in areas with high pre-test probability or limited resources. Although CXR is less sensitive than real-- time reverse transcription-polymerase chain reaction (RT-PCR) in detecting mild COVID-19, it is nevertheless useful because of equipment portability, low cost and practicality in serial assessments of disease progression among hospitalized patients. 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.

Primary Breast Angiosarcoma: Utilisation of Pre-surgical Magnetic Resonance Imaging (MRI) for Accurate Tumour Characterization and Planning - A Case Report and Literature Review.

BACKGROUND: Primary breast angiosarcoma is a rare malignancy with non-specific clinical and radiological findings. CASE REPORT: A 30-year-old lady presented with left breast pain and lumpiness for over one year. She has had several breast ultrasounds (US) and was treated for acute mastitis and abscess. Subsequently, in view of the rapid growth of the lump and worsening pain, she was re-investigated with US, elastography, digital breast tomosynthesis (DBT) and MRI. MRI raised the suspicion of angiosarcoma. The diagnosis was confirmed after biopsy and she underwent mastectomy. DISCUSSION: Literature review on imaging findings of breast angiosarcoma, especially on MRI, is discussed. MRI features showed heterogeneous low signal intensity on T1 and high signal intensity on T2. Dynamic contrast enhancement (DCE) features included either early enhancement with or without washout in the delayed phase, and some reported central areas of non-enhancement. CONCLUSION: This case report emphasises on the importance of MRI in clinching the diagnosis of breast angiosarcoma, and hence, should be offered sooner to prevent diagnostic delay.