optimization-breast-biopsy-mastectomy-sample-collection-procedures

Optimization of Breast Biopsy and Mastectomy Sample Collection Procedures for Biobanking, Personalized Medicine, and Research Applications

Breast cancer is the most prevalent cancer affecting women, particularly in Asia, with the highest incidence in the Philippines. Despite ongoing efforts, ...

University of the Philippines

To compare nonmydriatic (NM) and mydriatic (MD) handheld retinal imaging with standard ETDRS 7-field color fundus photography (ETDRS photographs) for the assessment of diabetic retinopathy (DR) and diabetic macular edema (DME).

Comparison of Handheld Retinal Imaging with ETDRS 7-Standard Field Photography for Diabetic Retinopathy and Diabetic Macular Edema.

To compare diabetic retinopathy (DR) severity identified on handheld retinal imaging with ultrawide field (UWF) images.

Comparisons of handheld retinal imaging devices with ultrawide field images for determining diabetic retinopathy severity.

To create and validate code-free automated deep learning models (AutoML) for diabetic retinopathy (DR) classification from handheld retinal images.

Performance of Automated Machine Learning for Diabetic Retinopathy Image Classification from Multi-field Handheld Retinal Images.

Handheld retinal imaging cameras are relatively inexpensive and highly portable devices that have the potential to significantly expand diabetic retinopathy (DR) screening, allowing a much broader population to be evaluated. However, it is essential to evaluate if these devices can accurately identify vision-threatening macular diseases if DR screening programs will rely on these instruments. Thus, the purpose of this study was to evaluate the detection of diabetic macular pathology using monoscopic macula-centered images using mydriatic handheld retinal imaging compared with spectral domain optical coherence tomography (SDOCT).

Comparisons of Handheld Retinal Imaging with Optical Coherence Tomography for the Identification of Macular Pathology in Patients with Diabetes.

To determine agreement of one-field (1F, macula-centred), two-field (2F, disc-macula) and five-field (5F, macula, disc, superior, inferior and nasal) mydriatic handheld retinal imaging protocols for the assessment of diabetic retinopathy (DR) as compared with standard seven-field Early Treatment Diabetic Retinopathy Study (ETDRS) photography.

One-field, two-field and five-field handheld retinal imaging compared with standard seven-field Early Treatment Diabetic Retinopathy Study photography for diabetic retinopathy screening.

The purpose of this study was to compare 2-field (2F) and 5-field (5F) mydriatic handheld retinal imaging for the assessment of diabetic retinopathy (DR) severity in a community-based DR screening program (DRSP).

Comparison of 2-Field and 5-Field Mydriatic Handheld Retinal Imaging in a Community-Based Diabetic Retinopathy Screening Program.

Optical coherence tomography (OCT) angiography (OCTA) has the potential to influence the diagnosis and management of diabetic eye disease. This study aims to determine the correlation between diabetic retinopathy (DR) findings on ultrawide field (UWF) color photography (UWF-CP), UWF fluorescein angiography (UWF-FA), and OCTA.

Comparison of Diabetic Retinopathy Lesions Identified Using Ultrawide Field Imaging and Optical Coherence Tomography Angiography.

To evaluate mydriatic handheld retinal imaging performance assessed by point-of-care (POC) artificial intelligence (AI) as compared with retinal image graders at a centralized reading center (RC) in identifying diabetic retinopathy (DR) and diabetic macular edema (DME).

Accuracy of Integrated Artificial Intelligence Grading Using Handheld Retinal Imaging in a Community Diabetic Eye Screening Program.

Lymphovascular invasion (LVI), the invasion of tumor cells into the lymphatic or vascular space, is an early indicator of potential metastasis, with its presence in breast cancer independently predicting poorer outcomes even after neoadjuvant chemotherapy. However, a major limitation is that LVI detection currently relies on postsurgical evaluation. To address this, we determined whether LVI breast tumors contain a unique gene signature that could facilitate earlier detection. Here, we conducted an integrative analysis of the gene profile between LVI and LVI primary breast tumors from various sources, including published data and our own research, using both microarray and RNA-seq data. Our analysis revealed protein binding and vesicle-related genes to be the most enriched categories in LVI vs LVI tumors. Furthermore, LVI tumors showed enrichment for xenobiotic metabolism genes, particularly drug metabolism enzymes, such as cytochrome P450 and uridine 5'-diphospho-glucuronosyltransferases. An elastic net regression model containing 13 of these uridine 5'-diphospho-glucuronosyltransferases and cytochrome P450 genes can predict LVI status with 92% accuracy. This suggests a potential link to drug resistance, which was further confirmed by the finding that patients with LVI tumors had a significantly lower clinical response rate than individuals with LVI tumors. We also observed this resistance in patient-derived organoids, with LVI organoids exhibiting lower sensitivity to doxorubicin, implying that doxorubicin might be less effective for LVI breast cancer, potentially contributing to poorer outcomes. Overall, our study unlocked an exciting opportunity for personalized medicine, in that, therapy efficacy and patient outcomes can be improved by incorporating the LVI-associated gene signature into treatment plans.

Article	Year
Comparison of Handheld Retinal Imaging with ETDRS 7-Standard Field Photography for Diabetic Retinopathy and Diabetic Macular Edema. Ophthalmology. Retina\| PubMed ID: 35278726	2022
Comparisons of handheld retinal imaging devices with ultrawide field images for determining diabetic retinopathy severity. Acta ophthalmologica\| PubMed ID: 36847205	2023
Performance of Automated Machine Learning for Diabetic Retinopathy Image Classification from Multi-field Handheld Retinal Images. Ophthalmology. Retina\| PubMed ID: 36924893	2023
Comparisons of Handheld Retinal Imaging with Optical Coherence Tomography for the Identification of Macular Pathology in Patients with Diabetes. Ophthalmic research\| PubMed ID: 37080187	2023
One-field, two-field and five-field handheld retinal imaging compared with standard seven-field Early Treatment Diabetic Retinopathy Study photography for diabetic retinopathy screening. The British journal of ophthalmology\| PubMed ID: 37094836	2024
Comparison of 2-Field and 5-Field Mydriatic Handheld Retinal Imaging in a Community-Based Diabetic Retinopathy Screening Program. Ophthalmologica. Journal international d'ophtalmologie. International journal of ophthalmology. Zeitschrift fur Augenheilkunde\| PubMed ID: 37231995	2023
Comparison of Diabetic Retinopathy Lesions Identified Using Ultrawide Field Imaging and Optical Coherence Tomography Angiography. Ophthalmic research\| PubMed ID: 37379803	2023
Accuracy of Integrated Artificial Intelligence Grading Using Handheld Retinal Imaging in a Community Diabetic Eye Screening Program. Ophthalmology science\| PubMed ID: 38317871	2024
Lymphovascular Invasion Is Associated With Doxorubicin Resistance in Breast Cancer. Laboratory investigation; a journal of technical methods and pathology\| PubMed ID: 39978641	2025

Lizzie Anne C. Aquino

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