Clinical Plans Research Articles

Validating knowledge-based volumetric modulated arc therapy plans with a multi-institution model (broad model) using a complete open-loop dataset for prostate cancer.

This study examined the characteristics of the broad model (KBPbroad) through a complete open-loop evaluation of volumetric modulated arc therapy (VMAT) plans for prostate cancer in 30 patients at two institutions. KBPbroad, trained using 561 prostate cancer VMAT plans from five institutions with different treatment protocols, was shared with two institutions. The institutions were not involved in the creation of KBPbroad. Plan created with KBPbroad were compared with clinical plans (CPs) and plans created using a single-institution model at each institution (KBPonsite). KBPbroad maintained the target coverage of CPs while meeting dose limits across varied settings at each institution. At institution X, KBPbroad provided 40, 60, and 70Gy (V40Gy, V60Gy, and V70Gy, respectively) to 30.8% ± 9.9%, 15.3% ± 8.5%, and 9.0% ± 6.4% of the volume at the rectal wall, respectively, which were significantly smaller than those provided by KBPonsite and CPs. At institution Y, compared with CPs, KBPbroad provided significantly greater V50Gy, V70Gy, dose to 2% of the volume (D2%) at the rectum, and D2% at the bladder but significantly lower V50Gy and V70Gy at the bladder, in addition to superior dose homogeneity and conformality at the planning target volume. Our complete open-loop evaluation of VMAT plans for prostate cancer at two institutions demonstrated the clinical effectiveness of KBPbroad at institutions producing plans with insufficient reductions in OAR doses. Thus, the quality of KBPbroad plans is likely greater than that of KBPonsite plans and CPs.

Does deformation of immobilization devices impact treatment accuracy in thoracic cancer radiotherapy?

Immobilization devices are essential for maintaining accurate and repeatable patient positioning in radiotherapy. This study aimed to evaluate the setup errors and dosimetric deviation induced by the deformation of immobilization devices in thoracic cancer radiotherapy using CT-linac. A retrospective analysis was conducted on 40 thoracic cancer patients who underwent radiotherapy, using vacuum cushion (VC) and thermoplastic mask (TM) for immobilization. A total of 206 weekly Fan-beam CT (FBCT) images (4-7 per patient) were analyzed to manually delineate immobilization devices and assess their geometric deformations against setup errors. Dosimetric deviations between the clinical plan (CT-plan) and the delivered plan (FBCT-plan) were compared for planning target volume (PTV) and organs at risk (OARs). Correlations between dose variations and setup errors were analyzed in lateral (LAT), longitudinal (LNG), and vertical (VRT) axes. The conformity of the VC (Nup) and TM (Ndown) with the patient in simulation CT exhibited moderate to strong correlations with VRT setup errors (Ndown: r=-0.484, p<0.01;Nup: r=-0.697, p<0.01). However, intra-fraction deformation of immobilization devices (in FBCT) showed no significant correlation with setup errors. In the dosimetric analysis of OARs, lung dose parameters (Dmean, V5, V20) and heart Dmean exhibited a consistent absolute difference with increasing setup errors. Dose variation decreased significantly when errors exceeded 5 mm, particularly in the VRT direction for most PTV indices, with the exception of CI and HI. Spinal cord Dmax variation correlated significantly with setup accuracy along the LNG axis, but not along other axes. The conformity of immobilization devices in simulation CT exhibits a stronger correlation with setup accuracy than the deformation of these devices in intra-fraction FBCT. FBCT is recommended for improving treatment precision through dosimetric assessment and planning adjustments.

Factors influencing Nirmatrelvir/Ritonavir concentration in patients with COVID-19

BackgroundIn the filed of antiviral therapy, effective therapeutic concentration is beneficial to shorten the recovery time of patients and reduce the transmission rate.The aim of this study is to retrospectively analyze the factors that lead to the drug concentration of Nirmatrelvir /Ritonavir (NMV/RTV) not reaching the standard.MethodsIn this study, the NMV/RTV drug concentration(Cnmv/rtv) data (n = 114) of COVID-19 patients over 18 years old were collected from May 2022 to July 2022, and the results of the patients were retrospectively compared. According to the analysis of the early study of NMV/RTV, combined with the research results at home and abroad, according to whether the measured drug concentration > 987 ng/ml, the patients were divided into target group and non-target group,The non-target group was defined as not reaching the trough concentration level.ResultsSerum NMV/RTV concentration in adult patients was correlated with prognostic nutritional index [PNI, (P < 0.05)], height (P < 0.05), weight (P < 0.05) and creatinine clearance [Crcl, (P < 0.05)]. Multivariate analysis showed that height, weight, PNI, lymphocyte (LYM) and CrCl were independent influencing factors of NMV/RTV trough concentration. However, after the correction of BMI calculation, there was no correlation between NMV/RTV and BMI, so in the clinical medication plan, the drug was not adjusted according to the height and weight.ConclusionsThe serum NMV/RTV concentration of adult patients gradually decreased with the increase of CrCl. For patients with high and low CrCl, the trough concentration of NMV/RTV should be continuously monitored and the dosing regimen should be adjusted to achieve the target trough concentration in these patients to reduce the effect of CrCl. PNI is also a key factor affecting drug concentration. For poor nutritional status, drug concentration should be closely monitored and the dose should be adjusted.

A benchmarking and evidence-informed gap analysis of the hemodialysis care provision in Iran

BackgroundPatients with end stage renal disease (ESRD) are increasing worldwide. This is especially paramount in low and middle income countries in which ESRD patients are struggling to access specialist services e.g. hemodialysis (HD). Benchmarking analysis of the offered healthcare packages in several countries and comparison of the utilized alternative healthcare models for ESRD patients may be auspicious for institutional capacity-building in the existing healthcare facilities. Main aim of this study was to perform a benchmarking and evidence-informed gap analysis of the ESRD care provision in Iran and recognize the gaps that cause diversification in care quality for ESRD patients that hinder efforts for care quality improvement in the Iranian National Healthcare System.MethodsDimensions of the Australian Anglicare Southern Queensland Clinical and Care Governance Framework (ASQCGF) were utilized as corner stones of a comprehensive clinical care plan that is essential in responding to HD patients’ needs in Iran. An extensive literature search was performed at the next stage to recognize the gold standard core elements. The ascertained components were assigned to the five separate dimensions of the ASQCGF and a preliminary draft (comprehensive package of care for HD patients) was prepared. A checklist was developed at a later stage which was sent to a panel of expert consisting professional healthcare providers in nephrology and hemodialysis wards for their opinions. A gap analysis was conducted to evaluate current care processes of the Iranian HD patients align with the elements of the gold standard framework.ResultsThe identified deficits were classified in five areas in accord with the elements of ASQCGF as follow: A) supply of resources, medical devices and equipment support B) recruitment and endorsement of clinics and general work force C) infection prevention and controlling procedures D) care effectiveness monitoring and quality improvement E) provision of safe environment for both HD patients and hospitals’ staff.ConclusionsThe study findings revealed considerable gaps in providing quality HD services to the Iranian HD patients that herald their therapeutic unmet needs and the shift that is needed to narrow down the widening organizational failure which fuels the current disenchantment among the both healthcare providers and HD patients.

Baseline characteristics of patients with degenerative cervical myelopathy in Australia: analysis from the MYelopathy NAtural History registry.

DegenerativeCervical Myelopathy (DCM) is the most common cause of non-traumatic, chronic spinal cord dysfunction worldwide, causing debilitating disability with a diminishing quality of life. The natural history of DCM is poorly understood. This is a preliminary report of the first 60 patients recruited to the MYelopathy NAtural History (MYNAH) Registry. MYNAH Registry is an investigator-initiated, multicenter, prospective, non-interventional, longitudinal, national observational study (Registry ID ACSQHC-ARCR-258). Given the observational nature of the Registry, participants' clinical management plan is neither changed nor affected. Participants are recruited via an opt-in approach. A patient with DCM diagnosed by a spine/neurosurgeon after 1st January 2018 onwards is eligible to participate regardless of their surgical status. The Patient-Reported Outcome Measures (PROMs) are NDI, EQ5D5L and EQ-VAS; and the Practitioner-Reported Outcome Measures (PrROMs) are mJOA Score and Nurick Grade. Sixty participants (n = 60) have now been recruited of which male participants 34 (56.7%) and females are 26 (43.3%), with a mean age of 62.3 years (SD 14.1) and biospecimens for Proteomics have been collected from 33 (66%) participants. The median mJOA Score was 16.5 (8-18), with myelopathy severity recorded as mild in 42 (70%), moderate in 13 (21.7%) and severe in 5 (8.3%) participants. Median Nurick Grade 0 (0-5), NDI 14 (0-45), EQ5D5L Score 0.850 (-0.288-1) and EQ-VAS 70 (10-96). The MYNAH National DCM Registry in Australia is a novel spinal surgical initiative, that will inform the decision(s) to proceed with the scientific, evidence-based and personalised management of DCM globally in the future.

Development and Validation of a Nomogram for Predicting Systemic Inflammatory Response Syndrome Following Percutaneous Nephrolithotomy.

Objective: To develop and validate a nomogram for predicting the occurrence of systemic inflammatory response syndrome (SIRS) following percutaneous nephrolithotomy (PCNL), aiming to enhance clinical decision-making and treatment planning. Methods: Clinical data of 1,047 patients undergoing PCNL at a single-center hospital between 2017 and 2023 were retrospectively analyzed. Independent risk factors influencing SIRS occurrence were identified through multi-variable logistic regression analysis, and a predictive model was constructed. The model's accuracy and reliability were evaluated through internal training and validation set. Results: Multi-variable regression analysis identified six key predictive factors: gender, diabetes, urine culture results, stone surface, staghorn stones, and operative time, leading to the establishment of a nomogram predictive model. Internal validation and validation set data demonstrated the model's high predictive accuracy and reliability, with areas under the receiver operating characteristic curve of 0.718 and 0.723, respectively. Conclusions: A nomogram predictive model for assessing SIRS following PCNL was successfully developed and validated. This model provides clinicians with a valuable tool for personalized treatment planning and implementing preventive measures.

Abstract PR002: EP300 loss of function is a pan-cancer sensitizer to BET inhibition

Abstract Genetically targeted therapies have proven to be a successful approach to treating cancer because they inhibit the causal (driver) biology of tumors that is absent in healthy cells. While targeted therapies exist for most oncogenes, only a small fraction of loss-of-function (LoF) tumor suppressor genes (TSGs) have been drugged to date, despite TSG mutations causing 2/3 of all cancer. Here we report a novel 1st-in-class genetically targeted opportunity using BET inhibitors to treat EP300 LoF cancers. Among the hundreds of pharmacogenetic screens that we have conducted, this interaction is similar to PARP-BRCA1/HRD in significance, and among the strongest we have discovered. It is cancer-type agnostic and holds up with all potent BET inhibitors in various pre-clinical models, including PDXs. Mechanistically, we demonstrate that apoptosis induced by DNA catastrophe arising from pre-mature entry into S phase plays a significant role. BET inhibition blocks timely assembly of DNA replication factors, which leads to G1 arrest in healthy cells; cancer cells that lack p300, a key regulator of CDK2, and CDK7, proceed through G1-S before replication deficiencies can be resolved. EP300 loss of function is a causal driver in more than 25,000 new cancer cases per year in the US and there currently are no genetically targeted options for these patients. This presentation will focus on the discovery, characterization, and clinical re-entry plan for our BET inhibitor LFB-190, to treat EP300 LoF solid tumors. Citation Format: Tomas Babak, Peter Truesdell, Greg Vontz, Peter Heinecke, Doris Coto Villa, Meiou Dai. EP300 loss of function is a pan-cancer sensitizer to BET inhibition. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr PR002

A Pilot Study of PSMA PET/CT and MRI Fusion for Prostate Cancer: Software to Replace PET/MRI Hardware.

Introduction: Prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT), in combination with magnetic resonance imaging (MRI), may enhance the diagnosis and staging of prostate cancer. Image fusion of separately acquired PET/CT and MRI images serve to facilitate clinical integration and treatment planning. This study aimed to investigate different PSMA PET/CT and MRI image fusion workflows for prostate cancer visualisation. Methods: Eighteen patients with prostate cancer who underwent PSMA PET/CT and MRI prior to radical prostatectomy were retrospectively selected. Alignment of the prostate was performed between PET/CT and MRI via three techniques: semi-automatic rigid, automatic rigid, and automatic non-rigid. Image fusion accuracy was evaluated through boundary and volume agreement, quantified by the Dice Similarity Coefficient (DSC), 95% Hausdorff Distance (HD), and Mean Surface Distance (MSD), with comparison against reconstructed histopathology slices. Results: Image fusion using all techniques resulted in clear lesion visualisation from PSMA PET/CT overlay and anatomical detail afforded by the MRI base and was consistent with histopathology tumour location. Image fusion accuracy was within the recommended range based on a DSC of 0.8-0.9. The automatic non-rigid registration method had the highest volume agreement (DSC: 0.96 ± <0.01) and boundary agreement (HD: 1.17 ± 0.35 mm) when compared to automatic rigid (DSC 0.88 ± 0.02, HD 3.18 ± 0.29 mm) and semi-automatic rigid (DSC 0.80 ± 0.06, HD 5.25 ± 1.68 mm). Conclusions: Image fusion of clinically obtained PET/CT and MRI is feasible and clinically acceptable for use in prostate cancer diagnosis and surgical management. While the best accuracy was observed with the automatic non-rigid technique, which requires further validation, image fusion with clinically accessible methods (semi-automatic rigid) may currently aid patient education, pre-operative planning, and intra-operative guidance.

Effectiveness of an Internet-Based Self-Help Acceptance and Commitment Therapy Program on Medical Students' Mental Well-Being: Follow-Up Randomized Controlled Trial.

Psychological distress is a growing problem among medical students worldwide. This highlights the need for psychological interventions to focus on mental health and improve well-being in this population. This study developed an internet-based, self-help, acceptance and commitment therapy program (iACT 2.0), aiming to examine its effectiveness in reducing depression, anxiety, stress, psychological inflexibility (PI), and obsessive-compulsive symptoms (OCSs) among medical students. A total of 520 Chinese postgraduate medical students were randomly assigned to either an iACT 2.0 intervention group (n=260; six online lessons, once every 5 days) or a control condition (n=260; without intervention). Participants completed questionnaires including the 21-item Depression Anxiety Stress Scale, the revised Obsessive-Compulsive Inventory, and the Multidimensional Psychological Flexibility Inventory at the preintervention (T1), postintervention (T2), and 1-month follow-up time points (T3). No therapist support was provided during the 1-month iACT 2.0 intervention period. Data were collected via an online platform and analyzed using repeated-measures ANOVA. Participants in the intervention group demonstrated a significant decrease in depression, anxiety, stress, PI, and OCSs compared to the control group after the intervention (F=22.9-672.04, all P<.001). Specifically, the intervention group showed significant reductions in all measured outcomes from the preintervention to postintervention time point and at the 1-month follow-up (all P<.001). In contrast, no significant changes were observed in the control group over the same period (all P>.05). The groups did not differ significantly at baseline (all P>.05). Significant differences were noted at both the postintervention and follow-up time points (all P<.001). This study demonstrated that the newly developed iACT 2.0 was effective in reducing depression, anxiety, stress, PI, and OCSs. Notably, the positive effects of the intervention persisted at the 1-month follow-up. This program can offer a useful addition to existing mental illness treatment and lead to improvements in clinical and psychotherapy planning while simultaneously reducing the burden on traditional counseling and services. Chinese Clinical Trial Registry ChiCTR2300070725; https://tinyurl.com/2h75wx8n.

Diagnostic and Treatment Challenges of Recurrent Tuberculosis in Patient with Drug-Induced Hepatotoxicity: A Case Report

Introduction: Pulmonary tuberculosis (TB) remains one of the most significant global health challenges, especially complicated by cases with incomplete treatment histories. The recurrence of TB poses diagnostic and therapeutic dilemmas that significantly impact patient outcomes. Case Presentation: We report a case of a 57-year-old female patient presenting with recurrent pulmonary TB after an incomplete treatment course. The patient's history revealed gaps in adherence to the prescribed TB regimen, leading to multiple relapses. In this study, we found that patients undergoing TB treatment may experience liver damage as a result of the TB medication, also known as DIH. Comprehensive diagnostic procedures, including chest radiography, sputum culture, and molecular testing, confirmed recurrent TB. The patient's clinical manifestations, treatment plan, and response to therapy are detailed. Conclusion: Recurrent TB is common, particularly in older adults, and is influenced more by environmental factors than occupation. Additionally, ATT poses risks of hepatotoxicity, especially in malnourished patients, underscoring the importance of managing side effects and addressing factors like malnutrition to prevent complications and improve outcomes. This case underscores the importance of complete adherence to TB treatment regimens and highlights the challenges in managing recurrent TB. It emphasizes the need for robust follow-up, patient education strategies, early diagnosis, and prompt intervention to prevent recurrence and enhance patient outcomes.

Assessing population-based to personalized planning strategies for head and neck adaptive radiotherapy.

Optimal head-and-neck cancer (HNC) treatment planning requires accurate and feasible planning goals to meet dosimetric constraints and generate robust online adaptive treatment plans. A new x-ray-based adaptive radiotherapy (ART) treatment planning system (TPS) version 2.0 emulator includes novel methods to drive the planning process including the revised intelligent optimization engine algorithm (IOE2). HNC is among the most challenging and complex sites and heavily depends on planner skill and experience to successfully generate a reference plan. Therefore, we evaluate the new TPS performance via conventionally accepted planning strategies with/without artificial intelligence (AI) and knowledge-based planning (KBP). Our institution has a pre-clinical release of the Varian Ethos2.0 TPS emulator which includes several changes that may affect current planning strategies. Twenty definitive and post-operative HNC patients were retrospectively selected with a two or three-level simultaneous integrated boost (SIB) dosing scheme. Patients were replanned in the emulator using population-based, KBP-guided with/without human intervention and AI-guided planning goals. These planning strategies were compared both dosimetrically and for plan deliverability. All strategies generally demonstrated acceptable plan quality with KBP- and AI-guided goals offering enhanced dosimetric sparing in organs-at-risk (OAR). The average contralateral parotid gland mean dose was 20.0±6.1Gy (p<0.001) for population-based and 15.0±6.1Gy (p=n.s.) for KBP-with human intervention versus 15.1±7.4Gy for clinical plans. Target coverage, minimum dose, and plan hotspot were acceptable in all cases. KBP-enabled strategy demonstrated higher modulation and faster optimization time than both population-based and AI-guided strategies. Simply entering population, automatic KBP-enabled or AI-generated planning goals into the new Ethos2.0 TPS produced dosimetrically compliant plans, with AI-guided goals demonstrating the most OAR sparing. Several of these approaches are easy to translate to other treatment sites and will help lower the barrier to entry for x-ray-based online-ART.

Evaluation of pelvic MRI-to-CT deformable registration for adaptive MR-guided particle therapy

PurposeWe aim to assess the MRI-to-CT deformable image registration (DIR) quality of our treatment planning system in the pelvic region, as the first step of an online MRI-guided particle therapy clinical workflow. Materials and MethodsUsing two different DIR algorithms, ANACONDA, the DIR algorithm incorporated in RayStation, and Elastix, an open source registration software, we retrospectively assessed the quality of the deformed CT (dCT) generation in the pelvic region for five patients. T1- and T2-weighted daily control MRI acquired prior to treatment delivery were used for the DIR. We compared the contours automatically mapped on the dCT against the manual contours on the MRI (ground-truth), by calculating the Dice similarity coefficients (DSC) and mean distances to agreement (MDA) for OAR, targets and outer contour. We assessed the dosimetric impact of the DIR on the clinical treatment plans, comparing the dose volume histograms (DVHs) and the value of the clinical goals achieved for each dCT. The water equivalent path lengths (WEPL) and dose range 80% (R80%) maps were compared by casting on the beams' eye view. ResultsThe T1 sequences performed better for the DIR with ANACONDA compared against the T2. ANACONDA's performance agreed with Elastix. The bladder and rectum led to the worst agreement. For the remaining structures analysed, DSC above 0.80 were obtained. Maximum median deviations of 7.1 mm and 2.1 mm were observed for WEPL and R80%, respectively, on the PTV. ConclusionThis works shows a good agreement on the DIR quality achieved with ANACONDA for the structures in the beams' path. By comparing the R80% generated with ANACONDA and Elastix, we give a first quantification of the uncertainties to be considered in an online MRI-guided particle therapy workflow for pelvic treatment.

Comparative Evaluation of CEUS and CECT in the Detection of Liver Metastases of Middle and Low Rectal Cancer.

To explore the imaging manifestations and clinical application value of contrast-enhanced ultrasound (CEUS) in liver metastases of middle and low rectal cancer by performing CEUS in patients. Additionally, we compared the results of CEUS with those of abdominal contrast-enhanced computed tomography (CECT) to assess the reliability of diagnosing liver metastases in patients with middle and low rectal cancer. Hepatic CEUS was performed in 1095 patients with middle and low rectal cancer, and all patients underwent abdominal CECT examinations to determine the presence or absence of liver metastases. The results of both examinations were compared to evaluate the value of hepatic CEUS for detecting liver metastases in patients with middle and low rectal cancer. Among 1095 patients with middle and low rectal cancer, 132 were diagnosed with liver metastases of middle and low rectal cancer. 130 cases of liver metastases of rectal cancer were identified using hepatic CEUS, whereas 126 cases were identified using abdominal CECT. The detection rates of hepatic CEUS and abdominal CECT for liver metastases of middle and low rectal cancer showed no statistically significant differences (P > 0.05). The Kappa value for the diagnosis of liver metastases of middle and low rectal cancer between hepatic CEUS and abdominal CECT was 0.974 (P < 0.001), indicating good consistency between the two imaging modalities in detecting liver metastases of middle and low rectal cancer. Hepatic CEUS can be used to diagnose liver metastases in middle and low rectal cancer, providing crucial imaging evidence for clinical treatment planning. It exhibited higher sensitivity than that of abdominal CECT in diagnosing liver metastases of middle and low rectal cancer, enabling the identification of higher number of liver metastases of middle and low rectal cancer cases.

Successful Treatment of Chronic Inflammatory Enteropathy in 2-Year-Old Yorkshire Terier. Case Report

Abstract Chronic enteropathy in dogs represents a significant clinical challenge that often requires innovative therapeutic strategies for effective management. This case study investigated the simultaneous use of budesonide, cannabidiol (CBD) oil and probiotics. Budesonide represents a corticoid therapy primarily used in human medicine for autoimmune diseases. Cannabidiol oil is one of the cannabinoids that does not affect sensory perception and is known for its anti-inflammatory properties. Probiotics help maintain gut microbiota balance as a treatment modality for chronic enteropathy in dogs. This report details the clinical symptoms, diagnosis, and treatment plan, highlighting the positive response seen in the patient. The findings suggested that the combination of budesonide, CBD oil, and probiotics may be a beneficial strategy for the treatment of chronic enteropathy in dogs.

Not Another Dual Attention UNet Transformer (NNDA-UNETR): a plug-and-play parallel dual attention block in U-Net with enhanced residual blocks for medical image segmentation.

Medical image segmentation is crucial for clinical diagnostics and treatment planning. Recently, hybrid models often neglect the local modeling capabilities of Transformers for medical image segmentation, despite the complementary nature of local information from both convolutional neural networks (CNNs) and transformers. This limitation is particularly problematic in multi-organ segmentation, where organs are closely adhered, and accurate delineation is essential. This study aims to develop a novel method that leverages the strengths of both CNNs and transformers to address the challenges of segmenting multiple closely adhered organs, improving accuracy and robustness in multi-organ segmentation. In this study, we present the Not Another Dual Attention block (NNDA-block), a versatile, plug-and-play module that seamlessly integrates channel and spatial attention mechanisms. This block can be incorporated at any stage within the Not Another Dual Attention UNet Transformer (NNDA-UNETR) framework. Our novel approach to spatial attention uniquely combines local modeling, significantly reducing detail and texture loss during the up- and down-sampling processes typical in U-shaped architectures. Evaluations on the Beyond the Cranial Vault (BTCV) and Automatic Cardiac Diagnosis Challenge benchmark datasets demonstrate our method's effectiveness in balancing model complexity with accuracy. On the BTCV dataset, our model sets new state-of-the-art benchmarks, achieving a Dice similarity coefficient of 84.13%, normalized surface dice of 86.96%, mean average surface distance of 3.46 mm, and an Hausdorff distance at 95% of 17.76 mm. Moreover, it reduces the parameter count by 34.2% compared to leading contemporary methods, all while maintaining low computational costs [measured in floating point operations per second (FLOPs)]. NNDA-UNETR offers a robust solution for accurate segmentation in multi-organ tasks, particularly where organ adhesion poses challenges. Its lightweight design also makes it well-suited for deployment in real-world medical environments with limited computational resources.

Quality and mechanical efficiency of automated knowledge-based planning for volumetric-modulated arc therapy in head and neck cancer.

This study aimed to examine the effectiveness of the automated RapidPlanin assessing plan quality and to explore how beam complexity affects the mechanical performance of volumetric modulated arc therapy for head and neck cancers. The plans were first generated using automated RapidPlan with scripting application programming interface (API) and then further refined through manual optimization (RP+MP) to improve plan quality. The quality of 20 plans was assessed, taking into account dose statistics and clinical plan acceptability. The impact of beam complexity on mechanical performance was analyzed using parameters such as leaf speed (LS), leaf acceleration (LA), mean-field area (MFA), cross-axis score (CAS), closed leaf score (CLS), small aperture score (SAS), and monitor units per control point (MU/CP). Patient-specific quality assurance (PSQA) was conducted to determine differences between the RP+MP and original plans. No differences in the heterogeneity index and conformity number were observed between the RP+MP and original plans. The RP+MP plan was superior to the original plan for sparing the left cochlea, left and right internal auditory canals, chiasm, and left optic nerve. Significant differences (p<0.05) were identified in CAS, SAS1mm, SAS2mm, and SAS10mm. However, there was no significant difference in PSQAbetween the RP+MP and original plans. The RP+MP plan without any modifications was clinically acceptable in 45% of cases. The automated RP with scripting API followed by MP (RP+MP) yielded a high-quality plan in terms of dose statistics and clinical acceptability. The RP+MP plan yielded a higher CAS and SAS compared with the original plan. Nevertheless, there was no significant difference in PSQAbetween the RP+MP and original plans.

Artificial intelligence and digital tools for design and execution of cardiovascular clinical trials.

Recent advances have given rise to a spectrum of digital health technologies that have the potential to revolutionize the design and conduct of cardiovascular clinical trials. Advances in domain tasks such as automated diagnosis and classification, synthesis of high-volume data and latent data from adjacent modalities, patient discovery, telemedicine, remote monitoring, augmented reality, and in silico modelling have the potential to enhance the efficiency, accuracy, and cost-effectiveness of cardiovascular clinical trials. However, early experience with these tools has also exposed important issues, including regulatory barriers, clinical validation and acceptance, technological literacy, integration with care models, and health equity concerns. This narrative review summarizes the landscape of digital tools at each stage of clinical trial planning and execution and outlines roadblocks and opportunities for successful implementation of digital tools in cardiovascular clinical trials.

Innovative multi-class segmentation for brain tumor MRI using noise diffusion probability models and enhancing tumor boundary recognition

Medical imaging, notably Magnetic Resonance Imaging (MRI), plays a vital role in contemporary healthcare by offering detailed insights into internal structures. Addressing the escalating demand for precise diagnostics, this research focuses on the challenges of multi-class segmentation in MRI. The proposed algorithm integrates diffusion models, capitalizing on their efficacy in capturing microstructural details, emphasizing the intricacies of human anatomy and tissue variations that challenge segmentation algorithms. Introducing the Diffusion Model, previously successful in various applications, the research applies it to medical image analysis. The method employs a two-step approach: a diffusion-based segmentation model and a dedicated network for enhancing tumor (ET) boundary recognition. Training is guided by a combined loss function, emphasizing Weighted Cross-Entropy and Weighted Dice Loss. Experiments, conducted using the BraTS2020 dataset for brain tumor segmentation, showcase the proposed algorithm’s competitive results, particularly in enhancing accuracy for the challenging ET region. Comparative analyses underscore its superiority over existing methods, emphasizing efficiency and simplicity in clinical implementation. In conclusion, this research pioneers an innovative approach that combines diffusion models and ET boundary recognition to optimize multi-class segmentation for brain tumors. The method holds promise for improving clinical diagnosis and treatment planning, providing accurate and interpretable segmentation results without the need for high-end equipment.

Dose distributions of proton therapy plans are robust against lowering the resolution of CTs combinedwith increasing noise.

Treatment planning in radiation therapy (RT) is performed on image sets acquired with commercial x-ray computed tomography (CT) scanners. Considering an increased frequency of verification scans for adaptive RT and the advent of alternatives to x-ray CTs, there is a need to review the requirements for image sets used in RT planning. This study aims to derive the required image quality (IQ) for the computation of the dose distribution in proton therapy (PT) regarding spatial resolution and the combination of spatial resolution and noise. The knowledge gained is used to explore the potential for dose reduction in tomography-guidedPT. Mathematical considerations indicate that the required spatial resolution for dose computation is on the scale of the set-up margins fed into the robust optimization. This hypothesis was tested by processing retrospectively 12 clinical PT cases, which reflect a variety of tumor localizations. Image sets were low-pass filtered and were made noisy in a generic manner. Dose distributions on the modified CT scans were computed with a Monte-Carlo dose engine. The similarity of these dose distributions with clinical ones was quantified with the gamma-index (1mm/1%). The potential reduction of the x-ray exposure compared to the planning CT scan was estimated. Dose distributions within the irradiated volume were robust against low-pass filtering of the CTs with kernels up to a full-width-at-half-maximum of 4mm, that is, the gamma pass rate (1mm/1%) was 98%. The limit of the filter width was 6mm for brain tumors and 8mm for targets in the abdomen. These pass rates remained approximately unchanged if a limited amount of noise was added to the CT image sets. The estimated potential reductions of the x-ray exposure were at least a factor of20. The requirements on IQ in terms of spatial resolution in combination with noise for computing the dose in PT are clearly lower than the IQ of current clinical planning. The results apply, for example, to ultra-low dose x-ray CTs, proton CTs with coarse spatial detection, and attenuation images from the joint reconstruction of time-of-flight PET scans.

A Case Report of Disseminated Nocardiosis

Objective: To summarize the clinical characteristics and treatment plan for a case of disseminated nocardiosis. Methods: The study summarized the clinical characteristics and treatment plan for a case of disseminated nocardiosis. Results: The primary symptoms of the patient included high fever and multiple enlarged lymph nodes. Chest computed tomography revealed a shadow of nodules in the upper lobe of the left lung, multiple nodules, and pleural effusion in both lungs. Additionally, bilateral blood cultures indicated the presence of Nocardia terpenica. The final diagnosis was disseminated Nocardia sp. infection. Upon admission, anti-infective treatment was initiated with sulfamethoxazole and linezolid. Conclusion: In patients with normal immune function, disseminated nocardiosis may present as high fever with lymph node enlargement, necessitating differentiation from lymphoma. This study reports on the diagnosis and treatment plan of a case of disseminated nocardiosis to enhance understanding and clinical management of this disease.