Dataset Information

Photoacoustic imaging provides an in vivo assessment of the preeclamptic placenta remodeling and function in response to therapy.

ABSTRACT:

Introduction

There is a lack of effective therapeutic interventions for preeclampsia. A central factor in the etiology of the disease is the development of placental hypoxia due to abnormal vascular remodeling. However, methods to assess the impact of potential therapies on placental growth and remodeling are currently lacking. Here, we develop and validate ultrasound-guided photoacoustic imaging methods to monitor the placental response to therapeutic intervention. Establishing non-invasive tools to image placental function opens up previously unachievable understandings of placental therapeutic response.

Methods

Studies were performed in the reduced uterine perfusion pressure (RUPP) rat model of preeclampsia. Preclinical research has identified tempol, a superoxide dismutase mimetic, and the phosphodiesterase inhibitor sildenafil as potential therapeutics for preeclampsia, as both improve in vivo maternal outcomes. PA images of the placental environment were acquired in RUPP rats receiving tempol (n = 8) or sildenafil (n = 8) to assess the longitudinal effects of treatment on placental oxygenation and vascular remodeling. Imaging measurements were validated with ex vivo histological analysis.

Results

Spectral photoacoustic imaging non-invasively measured placental hypoxia and impaired vascular growth two days after the RUPP procedure was implemented. Sildenafil significantly improved (p < 0.05) placental oxygenation and promoted vascular remodeling in RUPP animals, while RUPP animals treated with tempol had a diminished placental therapeutic response.

Discussion

We demonstrate that photoacoustic imaging provides in vivo measures of placental oxygenation and vascular remodeling, a previously unobtainable assessment of preeclamptic therapeutic response. These imaging tools have tremendous potential to accelerate the search for effective therapies for preeclampsia.

SUBMITTER: Lawrence DJ

PROVIDER: S-EPMC10236486 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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Publications

Photoacoustic imaging provides an in vivo assessment of the preeclamptic placenta remodeling and function in response to therapy.

Lawrence Dylan J DJ Bayer Carolyn L CL

Placenta 20220621

<h4>Introduction</h4>There is a lack of effective therapeutic interventions for preeclampsia. A central factor in the etiology of the disease is the development of placental hypoxia due to abnormal vascular remodeling. However, methods to assess the impact of potential therapies on placental growth and remodeling are currently lacking. Here, we develop and validate ultrasound-guided photoacoustic imaging methods to monitor the placental response to therapeutic intervention. Establishing non-inva ...[more]

PMID: 35764022

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Project description:BackgroundPreeclampsia (PE) is a hypertensive pregnancy disorder linked to placental dysfunction, often involving pathological lesions like acute atherosis, decidual vasculopathy, accelerated villous maturation, and fibrinoid deposition. However, there is no gold standard for the pathological diagnosis of PE and this limits the ability of clinicians to distinguish between PE and non-PE pregnancies. Recent advances in computational pathology have provided the opportunity to automate pathological analysis for diagnosis, classification, prediction, and prediction of disease progression. In this study, we assessed whether computational pathology could be used to identify PE placentas.MethodsA total of 168 placental whole-slide images (WSIs) of patients from Seoul National University Hospital (comprising 84 PE cases and 84 normal controls) were used for model development and internal validation. For external validation of the model, 76 placental slides (including 38 PE cases and 38 normal controls) were obtained from the Boramae Medical Center (BMC). To establish standard criteria for diagnosing PE and distinguishing it from controls using placental WSIs, patch characteristics and quantification of terminal and intermediate villi were employed. In unsupervised learning, K-means clustering was conducted as a feature obtained through an Auto Encoder to extract the ratio of each cluster for each WSI. For supervised learning, quantitative assessments of the villi were obtained using a U-Net-based segmentation algorithm. The prediction model was developed using an ensemble method and was compared with a clinical feature model developed by using placental size features.ResultsUsing ensemble modeling, we developed a model to identify PE placentas. The model showed good performance (area under the precision-recall curve [AUPRC], 0.771; 95% confidence interval [CI], 0.752-0.790), with 77.3% of sensitivity and 71.1% of specificity, whereas the clinical feature model showed an AUPRC 0.713 (95% CI, 0.694-0.732) with 55.6% sensitivity and 86.8% specificity. External validation of the predictive model employing the BMC-derived set of placental slides also showed good discrimination (AUPRC, 0.725; 95% CI, 0.720-0.730).ConclusionThe proposed computational pathology model demonstrated a strong ability to identify preeclamptic placentas. Computational pathology has the potential to improve the identification of PE placentas.

Dataset Information

Photoacoustic imaging provides an in vivo assessment of the preeclamptic placenta remodeling and function in response to therapy.

Introduction

Methods

Results

Discussion

Publications

Photoacoustic imaging provides an in vivo assessment of the preeclamptic placenta remodeling and function in response to therapy.

Similar Datasets

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