Synovial Oxygenation at Photoacoustic Imaging to Assess Rheumatoid Arthritis Disease Activity

Automated Deep Learning-Based Finger Joint Segmentation in 3-D Ultrasound Images With Limited Dataset

Ultrasound imaging has shown promise in assessing synovium inflammation associated early stages of rheumatoid arthritis (RA). The precise identification of the synovium and the quantification of inflammation-specific imaging biomarkers is a crucial aspect of accurately quantifying and grading RA. In this study, a deep learning-based approach is presented that automates the segmentation of the synovium in ultrasound images of finger joints affected by RA. Two convolutional neural network architectures for image segmentation were trained and validated in a limited number of 2-D images, extracted from N = 18 3-D ultrasound volumes acquired from N = 9 RA patients, with sparse ground truth annotations of the synovium. Various augmentation strategies were employed to enhance the diversity and size of the training dataset. The utilization of geometric and noise augmentation transforms resulted in the highest dice score (0.768 ± 0 . 031 , N = 6 ) , and intersection over union ( 0 . 624 ± 0.040, N = 6), as determined via six-fold cross-validation. In addition, the segmentation model is used to generate dense 3-D segmentation maps in the ultrasound volumes, based on the available sparse annotations. The developed technique shows promise in facilitating more efficient and standardized workflow for RA screening using ultrasound imaging.

Integrated nomogram to predict HER2 expression in breast tumor: Clinical, Ultrasound, and Photoacoustic imaging approaches

BACKGROUND

HER2 is a key biomarker for breast cancer treatment and prognosis. Traditional assessment methods like immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) are effective but costly and time-consuming. Our model incorporates these methods alongside photoacoustic imaging to enhance diagnostic accuracy and provide more comprehensive clinical insights.

MATERIALS AND METHODS

A total of 301 breast tumors were included in this study, divided into HER2-positive (3+ or 2+ with gene amplification) and HER2-negative (below 3+ and 2+ without gene amplification) groups. Samples were split into training and validation sets in a 7:3 ratio. Statistical analyses involved t-tests, chi-square tests, and rank-sum tests. Predictive factors were identified using univariate and multivariate logistic regression, leading to the creation of three models: ModA (clinical factors only), ModB (clinical plus ultrasound factors), and ModC (clinical, ultrasound, and photoacoustic imaging-derived oxygen saturation (SO2)).

RESULTS

The area under the curve (AUC) for ModA was 0.756 (95 % CI: 0.69-0.82), ModB increased to 0.866 (95 % CI: 0.82-0.91), and ModC showed the highest performance with an AUC of 0.877 (95 % CI: 0.83-0.92). These results indicate that the comprehensive model combining clinical, ultrasound, and photoacoustic imaging data (ModC) performed best in predicting HER2 expression.

CONCLUSION

The findings suggest that integrating clinical, ultrasound, and photoacoustic imaging data significantly enhances the accuracy of predicting HER2 expression. For personalised breast cancer treatment, the integrated model could provide a comprehensive and reproducible decision support tool.

Deep learning combined with attention mechanisms to assist radiologists in enhancing breast cancer diagnosis: a study on photoacoustic imaging

Accurate prediction of breast cancer (BC) is essential for effective treatment planning and improving patient outcomes. This study proposes a novel deep learning (DL) approach using photoacoustic (PA) imaging to enhance BC prediction accuracy. We enrolled 334 patients with breast lesions from Shenzhen People's Hospital between January 2022 and January 2024. Our method employs a ResNet50-based model combined with attention mechanisms to analyze photoacoustic ultrasound (PA-US) images. Experiments demonstrated that the PAUS-ResAM50 model achieved superior performance, with an AUC of 0.917 (95% CI: 0.884 -0.951), sensitivity of 0.750, accuracy of 0.854, and specificity of 0.920 in the training set. In the testing set, the model maintained high performance with an AUC of 0.870 (95% CI: 0.778-0.962), sensitivity of 0.786, specificity of 0.872, and accuracy of 0.836. Our model significantly outperformed other models, including PAUS-ResNet50, BMUS-ResAM50, and BMUS-ResNet50, as validated by the DeLong test (p < 0.05 for all comparisons). Additionally, the PAUS-ResAM50 model improved radiologists' diagnostic specificity without reducing sensitivity, highlighting its potential for clinical application. In conclusion, the PAUS-ResAM50 model demonstrates substantial promise for optimizing BC diagnosis and aiding radiologists in early detection of BC.

Multimodal PA/US imaging in Rheumatoid Arthritis: Enhanced correlation with clinical scores

Background

Accurate assessment of Rheumatoid Arthritis (RA) activity remains a challenge. Multimodal photoacoustic/ultrasound (PA/US) joint imaging emerges as a novel imaging modality capable of depicting microvascularization and oxygenation levels in inflamed joints associated with RA. However, the scarcity of large-scale studies limits the exploration of correlating joint oxygenation status with disease activity.

Objective

This study aimed to explore the correlation between multimodal PA/US imaging scores and RA disease activity, assessing its clinical applicability in managing RA.

Methods

In this study, we recruited 111 patients diagnosed with RA and conducted examinations of seven small joints on their clinically dominant side using a PA/US imaging system. The PA and power Doppler ultrasound (PDUS) signals were semi-quantitatively assessed using a 0-3 grading system. The cumulative scores for PA and PDUS across these seven joints (PA-sum and PDUS-sum) were calculated. Relative oxygen saturation (So2) values of inflamed joints on the clinically dominant side were measured, and categorized into four distinct PA+So2 patterns. The correlation between PA/US imaging scores and disease activity indices was systematically evaluated.

Results

Analysis of 777 small joints in 111 patients revealed that the PA-sum scores exhibited a strong positive correlation with standard clinical scores for RA, including DAS28 [ESR] (ρ = 0.682), DAS28 [CRP] (ρ = 0.683), CDAI (ρ = 0.738), and SDAI (ρ = 0.739), all with p < 0.001. These correlations were superior to those of the PDUS-sum scores (DAS28 [ESR] ρ = 0.559, DAS28 [CRP] ρ = 0.555, CDAI ρ = 0.575, SDAI ρ = 0.581, p < 0.001). Significantly, in patients with higher PA-sum scores, notable differences were observed in the erythrocyte sedimentation rate (ESR) (p < 0.01) and swollen joint count 28 (SJC28) (p < 0.01) between hypoxia and intermediate groups. Notably, RA patients in the hypoxia group exhibited higher clinical scores in certain clinical indices.

Conclusion

Multi-modal PA/US imaging introduces potential advancements in RA assessment, especially regarding So2 evaluations in synovial tissues and associated PA scores. However, further studies are warranted, particularly with more substantial sample sizes and in multi-center settings.

Summary

This study utilized multi-modal PA/US imaging to analyze Rheumatoid Arthritis (RA) patients' synovial tissues and affected joints. When juxtaposed with traditional PDUS imaging, the PA approach demonstrated enhanced sensitivity, especially concerning detecting small vessels in thickened synovium and inflamed tendon sheaths. Furthermore, correlations between the derived PA scores, PA+So2 patterns, and standard clinical RA scores were observed. These findings suggest that multi-modal PA/US imaging could be a valuable tool in the comprehensive assessment of RA, offering insights not only into disease activity but also into the oxygenation status of synovial tissues. However, as promising as these results are, further investigations, especially in larger and diverse patient populations, are imperative.

Key points

⸸ Multi-modal PA/US Imaging in RA: This novel technique was used to assess the So2 values in synovial tissues and determine PA scores of affected RA joints.⸸ Correlation significantly with Clinical RA Scores: Correlations significantly were noted between PA scores, PA+So2 patterns, and standard clinical RA metrics, hinting at the potential clinical applicability of the technique.

Assessment of Oxygen Saturation in Breast Lesions Using Photoacoustic Imaging: Correlation With Benign and Malignant Disease

BACKGROUND

Hypoxia is a hallmark of breast cancer (BC). Photoacoustic (PA) imaging, based on the use of laser-generated ultrasound (US), can detect oxygen saturation (So2) in the tissues of breast lesion patients.

PURPOSE

To measure the oxygenation status of tissue in and on both sides of the lesion in breast lesion participants using a multimodal Photoacoustic/ultrasound (PA/US) imaging system and to determine the correlation between So2 measured by PA imaging and benign or malignant disease.

MATERIALS AND METHODS

Multimodal PA/US imaging and gray-scale US (GSUS) of breast lesion was performed in consecutive breast lesion participants imaged in the US Outpatient Clinic between 2022 and 2023. Dual-wavelength PA imaging was used to measure the So2 value inside the lesion and on both sides of the tissue, and to distinguish benign from malignant lesions based on the So2 value. The ability of So2 to distinguish benign from malignant breast lesions was evaluated by the receiver operating characteristic curve (ROC) and the De-Long test.

RESULTS

A total of 120 breast lesion participants (median age, 42.5 years) were included in the study. The malignant lesions exhibited lower So2 levels compared to benign lesions (malignant: 71.30%; benign: 83.81%; P < .01). Moreover, PA/US imaging demonstrates superior diagnostic results compared to GSUS, with an area under the curve (AUC) of 0.89 versus 0.70, sensitivity of 89.58% versus 85.42%, and specificity of 86.11% versus 55.56% at the So2 cut-off value of 78.85 (P < .001). The false positive rate in GSUS reduced by 30.75%, and the false negative rate diminished by 4.16% with PA /US diagnosis. Finally, the So2 on both sides tissues of malignant lesions are lower than that of benign lesions (P < .01).

CONCLUSION

PA imaging allows for the assessment of So2 within the lesions of breast lesion patients, thereby facilitating a superior distinction between benign and malignant lesions.

An Automatic 3-D Ultrasound and Photoacoustic Combined Imaging System for Human Inflammatory Arthritis

Aiming at a point-of-care device for rheumatology clinics, we developed an automatic 3-D imaging system combining the emerging photoacoustic (PA) imaging with conventional Doppler ultrasound (US) for detecting human inflammatory arthritis. This system is based on a commercial-grade GE HealthCare (GEHC, Chicago, IL, USA) Vivid E95 US machine and a Universal Robot UR3 robotic arm. This system automatically locates the patient's finger joints from a photograph taken by an overhead camera powered by an automatic hand joint identification method, followed by the robotic arm moving the imaging probe to the targeted joint to scan and obtain 3-D PA and Doppler US images. The GEHC US machine was modified to enable high-speed, high-resolution PA imaging while maintaining the features available on the system. The commercial-grade image quality and the high sensitivity in detecting inflammation in peripheral joints via PA technology hold great potential to significantly benefit clinical care of inflammatory arthritis in a novel way.

Phototherapy techniques for the management of musculoskeletal disorders: strategies and recent advances

Musculoskeletal disorders (MSDs), which include a range of pathologies affecting bones, cartilage, muscles, tendons, and ligaments, account for a significant portion of the global burden of disease. While pharmaceutical and surgical interventions represent conventional approaches for treating MSDs, their efficacy is constrained and frequently accompanied by adverse reactions. Considering the rising incidence of MSDs, there is an urgent demand for effective treatment modalities to alter the current landscape. Phototherapy, as a controllable and non-invasive technique, has been shown to directly regulate bone, cartilage, and muscle regeneration by modulating cellular behavior. Moreover, phototherapy presents controlled ablation of tumor cells, bacteria, and aberrantly activated inflammatory cells, demonstrating therapeutic potential in conditions such as bone tumors, bone infection, and arthritis. By constructing light-responsive nanosystems, controlled drug delivery can be achieved to enable precise treatment of MSDs. Notably, various phototherapy nanoplatforms with integrated imaging capabilities have been utilized for early diagnosis, guided therapy, and prognostic assessment of MSDs, further improving the management of these disorders. This review provides a comprehensive overview of the strategies and recent advances in the application of phototherapy for the treatment of MSDs, discusses the challenges and prospects of phototherapy, and aims to promote further research and application of phototherapy techniques.

Longitudinal volumetric assessment of inflammatory arthritis via photoacoustic imaging and Doppler ultrasound imaging

Aiming at clinical translation, we developed an automatic 3D imaging system combining the emerging photoacoustic imaging with conventional Doppler ultrasound for detecting inflammatory arthritis. This system was built with a GE HealthCare (GEHC) Vivid™ E95 ultrasound system and a Universal Robot UR3 robotic arm. In this work, the performance of this system was examined with a longitudinal study utilizing a clinically relevant adjuvant induced arthritis (AIA) murine model. After adjuvant injection, daily imaging of the rat ankle joints was conducted until joint inflammation was obvious based on visual inspection. Processed imaging results and statistical analyses indicated that both the hyperemia (enhanced blood volume) detected by photoacoustic imaging and the enhanced blood flow detected by Doppler ultrasound reflected the progress of joint inflammation. However, photoacoustic imaging, by leveraging the highly sensitive optical contrast, detected inflammation earlier than Doppler ultrasound, and also showed changes that are more statistically significant. This side-by-side comparison between photoacoustic imaging and Doppler ultrasound using the same commercial grade GEHC ultrasound machine demonstrates the advantage and potential value of the emerging photoacoustic imaging for rheumatology clinical care of arthritis.

Photoacoustic/ultrasonic dual-mode imaging for monitoring angiogenesis and synovial erosion in rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by the formation of new vessels, synovial proliferation and destruction of articular cartilage. However, characteristic early diagnostic and therapeutic monitoring methods are still lacking. We report a study using a photoacoustic/ultrasound (PA/US) dual-mode imaging for RA disease. By establishing a collagen-induced (CIA) RA mouse model to classify disease states based on a subjective grading system, PA/US imaging allows real-time assessment of synovial erosion and vascular opacification within the knee joint in different disease states at high spatial resolution. The system also quantitatively monitors subcutaneous vascular physiology and morphology in the hind paw of mice, measuring the area and photoacoustic signal intensity of vascular proliferation and showing a positive correlation with disease grading. Compared to traditional subjective scoring of arthritis severity, the PA/US imaging is more sensitive i.e., vascular signals and synovial erosion can be observed early in the course of arthritis.