Combining optoacoustic (OA) imaging with ultrasound (US) enables visualisation of functional blood vasculature in breast lesions by OA to be overlaid with the morphological information of US. Here, we develop a simple OA feature set to differentiate benign and malignant breast lesions. 94 female patients with benign, indeterminate or suspicious lesions were recruited and underwent OA-US. An OA-US imaging feature set was developed using images from the first 38 patients, which contained 14 malignant and 8 benign solid lesions. Two independent radiologists blindly scored the OA-US images of a further 56 patients, which included 31 malignant and 13 benign solid lesions, with a sensitivity of 96.8% and specificity of 84.6%. Our findings indicate that OA-US can reveal vascular patterns of breast lesions that indicate malignancy using a simple feature set based on single wavelength OA data, which is therefore amenable to application in low resource settings for breast cancer management.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441264PMC
http://dx.doi.org/10.1016/j.pacs.2022.100383DOI Listing

Publication Analysis

Top Keywords

feature set
16
breast lesions
16
optoacoustic imaging
8
imaging feature
8
benign malignant
8
malignant breast
8
simple feature
8
images patients
8
malignant benign
8
benign solid
8

Similar Publications

Frequently, we perceive emotional information through multiple channels (e.g., face, voice, posture).

View Article and Find Full Text PDF

Distractor-specific control adaptation in multidimensional environments.

Nat Hum Behav

January 2025

Department of Psychological and Brain Sciences, Washington University in St. Louis, St Louis, MO, USA.

Goal-directed behaviour requires humans to constantly manage and switch between multiple, independent and conflicting sources of information. Conventional cognitive control tasks, however, only feature one task and one source of distraction. Therefore, it is unclear how control is allocated in multidimensional environments.

View Article and Find Full Text PDF

Key features and guidelines for the application of microbial alpha diversity metrics.

Sci Rep

January 2025

Facultad de Ingeniería, Universidad Austral, LIDTUA, CIC, Buenos Aires, Argentina.

Studies of microbial communities vary widely in terms of analysis methods. In this growing field, the wide variety of diversity measures and lack of consistency make it harder to compare different studies. Most existing alpha diversity metrics are inherited from other disciplines and their assumptions are not always directly meaningful or true for microbiome data.

View Article and Find Full Text PDF

Development and Validation of an AI-Based Multimodal Model for Pathological Staging of Gastric Cancer Using CT and Endoscopic Images.

Acad Radiol

January 2025

Guangxi Medical University, Nanning, Guangxi 530021, China (C.Z., D.H., B.W., S.W., Y.S., X.W.); Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, Nanning, Guangxi 530021, China (C.Z., D.H., B.W., S.W., Y.S., X.W.); Department of Gastrointestinal Gland Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, China (D.H., X.W.). Electronic address:

Rationale And Objectives: Accurate preoperative pathological staging of gastric cancer is crucial for optimal treatment selection and improved patient outcomes. Traditional imaging methods such as CT and endoscopy have limitations in staging accuracy.

Methods: This retrospective study included 691 gastric cancer patients treated from March 2017 to March 2024.

View Article and Find Full Text PDF

Radiomics and Deep Learning Model for Benign and Malignant Soft Tissue Tumors Differentiation of Extremities and Trunk.

Acad Radiol

January 2025

Department of Radiology, Southeast University Zhongda Hospital, No. 87 Dingjiaqiao Road, Gulou District, Nanjing, Jiangsu Province, China (M.Y., J.J.). Electronic address:

Rationale And Objectives: To develop radiomics and deep learning models for differentiating malignant and benign soft tissue tumors (STTs) preoperatively based on fat saturation T2-weighted imaging (FS-T2WI) of patients.

Materials And Methods: Data of 115 patients with STTs of extremities and trunk were collected from our hospital as the training set, and data of other 70 patients were collected from another center as the external validation set. Outlined Regions of interest included the intratumor and the peritumor region extending outward by 5 mm, then the corresponding radiomics features were extracted respectively.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!