Deep Q-CapsNet Reinforcement Learning Framework for Intrauterine Cavity Segmentation in TTTS Fetal Surgery Planning

Perspective in diagnostic accuracy of prenatal ultrasound and MRI for placenta accreta

PURPOSE

Placenta accreta (PA) significantly increases the risk of life-threatening maternal outcomes, and its rising prevalence, driven by the increase in cesarean deliveries, underscores the need for precise diagnostic tools to improve clinical management and outcomes. This study aims to evaluate the advanced diagnostic capabilities of prenatal ultrasound and magnetic resonance imaging (MRI) in the detection of PA, a severe obstetric complication characterized by abnormal adherence of the placenta to the myometrium.

MATERIALS AND METHODS

The study utilized a review of current literature and clinical studies to assess the diagnostic accuracy and clinical utility of ultrasound and MRI in identifying PA. Both imaging modalities were evaluated for their ability to assess the depth and extent of placental invasion, as well as their complementary roles in prenatal diagnosis. The experimental system included detailed imaging protocols for ultrasound and MRI, focusing on placental and uterine structures, and their application in real-world clinical settings.

RESULTS

The findings demonstrate that ultrasound and MRI are highly effective in diagnosing PA, with each modality offering unique advantages. Ultrasound is widely accessible and serves as the first-line diagnostic tool, providing detailed visualization of placental adherence and vascular patterns. MRI, on the other hand, offers superior soft tissue contrast and is particularly valuable in complex cases or when ultrasound findings are inconclusive. Together, these imaging techniques enable accurate evaluation of placental invasion, facilitating timely and targeted prenatal interventions. The study also highlights the potential for improved maternal and fetal outcomes through early diagnosis and optimized pregnancy management.

CONCLUSIONS

Prenatal ultrasound and MRI are indispensable tools in the diagnosis and management of placenta accreta, offering complementary insights that enhance diagnostic precision. Their combined use allows for detailed assessment of placental and uterine structures, guiding clinical decision-making and improving outcomes for both mothers and infants. Future advancements in imaging technology and research hold promise for further enhancing diagnostic accuracy and expanding clinical applications, ultimately contributing to safer and more effective care for patients with PA.

Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey

Reinforcement learning takes sequential decision-making approaches by learning the policy through trial and error based on interaction with the environment. Combining deep learning and reinforcement learning can empower the agent to learn the interactions and the distribution of rewards from state-action pairs to achieve effective and efficient solutions in more complex and dynamic environments. Deep reinforcement learning (DRL) has demonstrated astonishing performance in surpassing the human-level performance in the game domain and many other simulated environments. This paper introduces the basics of reinforcement learning and reviews various categories of DRL algorithms and DRL models developed for medical image analysis and radiation treatment planning optimization. We will also discuss the current challenges of DRL and approaches proposed to make DRL more generalizable and robust in a real-world environment. DRL algorithms, by fostering the designs of the reward function, agents interactions and environment models, can resolve the challenges from scarce and heterogeneous annotated medical image data, which has been a major obstacle to implementing deep learning models in the clinic. DRL is an active research area with enormous potential to improve deep learning applications in medical imaging and radiation therapy planning.

Computer-assisted fetal laser surgery in the treatment of twin-to-twin transfusion syndrome recent trends and prospects

Fetal laser surgery has emerged as the preferred treatment of twin-to-twin transfusion syndrome (TTTS). However, the limited field of view of the fetoscope and the complexity of the procedure make the treatment challenging. Therefore, preoperative planning and intraoperative guidance solutions have been proposed to cope with these challenges. This review uncovers the literature on computer-assisted software solutions focused on TTTS. These solutions are classified by the pre- or intraoperative phase of the procedure and further categorized by discussed hardware and software approaches. In addition, it evaluates the current maturity of technologies by the technology readiness level and enumerates the necessary aspects to bring these new technologies to the clinical practice. This article is protected by copyright. All rights reserved.