Therapy Planning Research Articles

Multi-label segmentation of carpal bones in MRI using expansion transfer learning.

The purpose of this study was to develop a robust deep learning approach trained with a small in-vivo MRI dataset for multi-label segmentation of all eight carpal bones for therapy planning and wrist dynamic analysis.
Approach: A small dataset of 15 3.0-T MRI scans from five health subjects was employed within this study. The MRI data was variable with respect to the Field Of View (FOV), wide range of image intensity, and joint pose. A two-stage segmentation pipeline using modified 3D U-Net was proposed. In the first stage, a novel architecture, introduced as Expansion Transfer Learning (ETL), cascades the use of a focused Region Of Interest (ROI) cropped around ground truth for pretraining and a subsequent transfer by an expansion to the original FOV for a primary prediction. The bounding box around the ROI generated was utilized in the second stage for high-accuracy,
labeled segmentations of eight carpal bones. Different metrics including Dice Similarity Coefficient (DSC), Average Surface Distance (ASD) and Hausdorff Distance (HD) were used to evaluate performance between proposed and four state-of-the-art approaches.
Main results: With an average DSC of 87.8 %, an ASD of 0.46 mm, an average HD of 2.42mm in all datasets (96.1 %, 0.16 mm, 0.38mm in 12 datasets after exclusion criteria, respectively), the proposed approach showed an overall strongest performance than comparisons.
Significance: To our best knowledge, this is the first CNN-based multi-label segmentation approach for MRI human carpal bones. The ETL introduced in this work improved the ability to localize a small ROI in a large FOV. Overall, the interplay of a two-stage approach and ETL culminated in convincingly accurate segmentation scores despite a very small amount of image data.

Novel Strategies for the Treatment of Lung Cancer: An In-depth Analysis of the Use of Immunotherapy, Precision Medicine, and Artificial Intelligence to Improve Prognoses.

Therapeutic hurdles persist in the fight against lung cancer, although it is a leading cause of cancer-related deaths worldwide. Results are still not up to par, even with the best efforts of conventional medicine, thus new avenues of investigation are required. Examining how immunotherapy, precision medicine, and AI are being used to manage lung cancer, this review shows how these tools can change the game for patients and increase their chances of survival. In the fight against cancer, immunotherapy has demonstrated encouraging results, especially in cases of small cell lung cancer [SCLC] and non-small cell lung cancer [NSCLC]. A key component in improving T cell responses against tumours is the use of immune checkpoint inhibitors, which include PD-1/PD-L1 and CTLA-4 blockers. Cancer vaccines and CAR T-cell therapy are two examples of adoptive cell therapies that might be used to boost the immune system's ability to eliminate tumours. In order to improve surgical results and decrease recurrence, neoadjuvant immunotherapy is being investigated for its ability to preoperatively reduce tumours. Precision medicine tailors treatment based on individual genetic profiles and tumour features, boosting therapeutic efficacy and avoiding unwanted effects. For certain types of non-small cell lung cancer [NSCLC], targeted treatments based on mutations in genes including EGFR, ALK, and ROS1 have shown excellent results. When it comes to optimizing treatment regimens, biomarker-driven approaches guarantee that the patients most likely to benefit from particular medicines are selected. Artificial intelligence [AI] is revolutionizing lung cancer care through increased diagnostic accuracy, prognostic assessments, and therapy planning. Machine learning algorithms examine enormous information to detect trends and forecast outcomes, permitting individualized treatment techniques. AI-driven imaging tools enable early diagnosis and monitoring of disease progression, while predictive models assist in evaluating therapy responses and potential toxicity. The convergence of these advanced technologies holds promise for overcoming the constraints of conventional therapy. Combining immunotherapy with targeted treatments and utilizing AI for precision medicine delivers a multimodal approach that tackles the heterogeneous and dynamic nature of lung cancer. The incorporation of these new tactics into clinical practice demands cross-disciplinary collaboration and continuing study to develop and confirm their effectiveness. The synergistic application of immunotherapy, precision medicine, and AI constitutes a paradigm shift in lung cancer management. These discoveries provide a robust basis for individualized and adaptable therapy, potentially altering the prognosis for lung cancer patients. Ongoing research and clinical studies are vital to unlocking the full potential of these technologies, paving the way for enhanced therapeutic outcomes and improved quality of life for people battling this tough disease.

Anatomic Variations Important for Dental Implantation in the Mandible—A Systematic Review

Background: This is a systematic review on the subject of anatomic landmarks and variations in the mandible that influence implantation placement. With this systematic review, we would like to summarize the results from different studies that are relevant to this subject and that are up to date, presenting their main findings, the measurements of mentioned landmarks, and giving clinical implications that will be helpful to practitioners in their better understanding of this topic. Methods: This study followed all of the elements of PRISMA. The criteria for inclusion and exclusion are described in detail. The following bibliographic databases were searched: PubMed (MEDLINE), The Cochrane Library, Wiley Online Library, EMBASE, and, additionally, Google Scholar. The search of articles was carried out using a combination of different keywords with a Boolean operator for each keyword. A total of 30 studies were included in this review and the risk of bias for each study was assessed. This review was registered with the PROSPERO ID number CRD42024609308. Results: The structure “SPIDER“ was used to present the findings in the summation table, followed by a detailed description of the quantitative findings and overall mean values of the most commonly used measured points. The morphometric measurements of anatomic details and variations in the mandible, such as the mandibular canal, mental foramen, lingual foramina, lingual canal, incisive canal, and mandibular concavity, are of high significance for clinicians dealing with implantation where gender, ethnicity, age groups, the side of the mandible, or remaining teeth can influence implantation planning. Conclusions: The distances of the named anatomic landmarks to the surrounding bone structures that are used as a guide during planning are of huge importance, so proper and detailed measurements must be executed by experienced professionals using CBCT. Knowledge of the position and variation in these landmarks may be used for any bone-guided augmentation, surgical transpositions of anatomic landmarks, and surgery intervention planning. The results of this study can aid in choosing appropriate measurement points and give the gross picture, for clinicians, in therapy planning, considering all the landmarks of significance in the mandible.

Dual-energy CT in head and neck applications.

Dual-energy CT (DECT), also known as spectral CT, has advanced diagnostic capabilities in head and neck pathologies beyond those of conventional single-energy CT (SECT). By having images at two distinct energy levels, DECT generates virtual monoenergetic images (VMIs), iodine maps, and quantitative features such as iodine concentration (IC) and spectral Hounsfield unit attenuation curves (SHUAC), which leads to enhancing tissue characterization, reducing artifacts, and differentiating head and neck pathologies. This review highlights DECT's applications in evaluating head and neck squamous cell carcinoma (SCC), thyroid cartilage invasion, cervical lymph node metastasis, radiation therapy planning, post-treatment assessment, and role in other head and neck conditions, such as infection and sialolithiasis. Additionally, it explores emerging applications of DECT in radiomics and artificial intelligence. The review also discusses about integrating DECT into clinical practice requires overcoming workflow challenges and ensuring radiologist proficiency with its diverse image reconstructions. As DECT technology evolves, its integration promises to further enhance the efficacy of managing head and neck pathologies.

The role of an inpatient aphasia-friendly choir for people with post-stroke communication impairment from the perspective of the multidisciplinary team: An exploratory study.

There is a growing body of evidence showing the value of community singing-based rehabilitation on psychosocial well-being and communication for people with post-stroke communication impairment (PSCI). However, there has been little consideration of the potential value an inpatient aphasia-friendly choir may have through the perspective of the stroke multidisciplinary team (MDT). To explore the experiences and views of the MDT on the role an established inpatient aphasia-friendly choir, at a stroke rehabilitation centre in South Wales, UK, may play in the rehabilitation of people with PSCI. Eight participants were recruited from the stroke rehabilitation centre's MDT. Semi-structured interviews were conducted and the verbatim transcripts were analysed using thematic analysis according to Braun and Clark's work of 2006. Four main themes were identified: (1) breaking down social isolation barriers; (2) patient voice and patient choice; (3) collective well-being and engagement; and (4) the therapeutic benefits across the MDT. The experiences and perceptions overlap, highlighting the wide-reaching therapeutic benefits of singing collaboratively. This research enables us to discover more about how the inpatient aphasia-friendly choir may enhance an individual's well-being, communication and confidence, and their overall rehabilitation from the MDT's perspective. By increasing our understanding of which aspects of the aphasia-friendly choir are most valued, future choir sessions can be better tailored to patients' needs. Additionally, the findings presented here could be taken forward and included in future speech and language therapy interventions, leading to increased patient ownership, not only of the choir but also of their other therapy goals. What is already known on this subject Previous research suggests positive implications for therapeutic collaborative singing on psychosocial well-being and communication for people with PSCI. There has been little consideration of the potential value an inpatient aphasia-friendly choir may have through the lens of the stroke MDT. The aim of this research was to explore the experiences and views of the MDT on the role an established inpatient aphasia-friendly choir may play in the rehabilitation of people with PSCI. What this paper adds to the existing knowledge This research highlights the benefits of an inpatient aphasia-friendly choir for an individual's well-being, communication and confidence. An increased understanding enables future choir sessions to be better tailored to patients' needs. What are the potential or actual clinical implications of this work? Participating in the choir was felt to offer an increased opportunity for functional therapy goals in an inpatient setting. The MDT frequently discussed the choir's ability to 'normalise' therapeutic approaches for the patients. A greater understanding of the choir participants empowers therapists to personalise therapy plans further, facilitating effectiveness, efficiency and holistic practice.

Whole-body tumor segmentation from FDG-PET/CT: Leveraging a segmentation prior from tissue-wise projections.

Background: Accurate tumor detection and quantification are important for optimized therapy planning and evaluation. Total tumor burden is also an appealing biomarker for clinical trials. Manual examination and annotation of oncologic PET/CT is labor-intensive and demands a high level of expertise. One significant challenge is the risk for human error, leading to potential omission of especially small tumors and tumors with low FDG uptake. Purpose: In this study, we introduced an automated framework with segmentation prior, from a tissue-wise multi-channel multi-angled based approach, to enhance tumor segmentation in whole-body FDG-PET/CT. Method: The proposed framework utilized a segmentation prior generated from tumor segmentations in tissue-wise multi-channel projections of the standardized uptake value (SUV) from PET. Projections were created from various angles and the tissues were identified based on their CT Hounsfield values. The resulting segmentation masks were subsequently backprojected into a unified 3D volume for creation of the segmentation prior. Finally, the segmentation prior was provided as an additional input channel along with the CT and SUV images to three variants of 3D segmentation networks (3D UNet, dynUNet, nnUNet) to enhance the overall tumor segmentation performance. All the methods were independently evaluated using 5-fold cross-validation on the autoPET dataset and subsequently tested on the U-CAN dataset. Results: Combining the segmentation prior with the original SUV and CT images improved overall tumor segmentation performance significantly compared to a baseline network. The increase in Dice coefficient for lymphoma, lung cancer, and melanoma across different segmentation networks were: 3D UNet ( , , ), dynUNet ( , , ), and nnUNet ( , , ), respectively; *, p-value < 0.05; ns, non-significance. Conclusion: The increased segmentation accuracy could be attributed to the segmentation prior generated from tissue-wise SUV projections, revealing information from various tissues that was useful for segmentation of tumors. The results from this study highlight the potential of the proposed method as a valuable future tool for time-efficient quantification of tumor burden in oncologic FDG-PET/CT.

Revolutionizing MRI Brain Tumor Detection Through GAN Augmentation and Smart Algorithms.

The accurate detection and classification of brain tumors in Magnetic Resonance Technology is critical to accurate diagnosis and therapy planning. However, the absence of annotated MR imaging datasets presents a significant challenge for advanced machine learning models, which require a range of data to achieve high accuracy and generalizability. This study provides a novel data augmentation method to enhance MR images for improved tumor identification by combining noise-to-image and image-to-image Generative Adversarial Networks (GANs). Noise-to-image GANs generate synthetic MR images from random noise, expanding the dataset with a range of anatomical variations, whereas image-to-image GANs refine and enhance existing MR images, highlighting important features relevant to tumor detection. The enlarged set of input data was taken to teach CNN, which was then correlated to a baseline model built solely on the original dataset. The GAN-augmented model beat the baseline cancer sorting and division tasks, as measured by parameters such as accuracy, recall, F1-score, and Dice coefficient. An ablation study verified the independent contributions of noise-to-image and image-to-image GANs, demonstrating that both types of augmentation operate together to improve model performance. This work illustrates the promise of GAN-based augmentation in medical imaging by giving a realistic solution to data restrictions and improving the robustness of deep learning models in brain tumor detection. This technology provides the way for more accurate and reliable based on artificial intelligence tools for diagnosis that can help medical practitioners make clinical decisions by integrating alternative GAN techniques. Key Words: GAN-based augmentation, Deep learning, Image augmentation techniques, Generative adversarial networks (GANs)

Современное состояние проблемы высокофункционального аутизма

&lt;p style="text-align: justify;"&gt;&lt;strong&gt;Objective.&lt;/strong&gt; Among autism spectrum disorders (ASD), high functional autism (HFA) is not considered a separate nosological entity. However, a number of foreign studies have shown that 10% of people with ASD are diagnosed with HFA. We discuss the characteristics of HFA as well as its differences from other ASD subgroups. The article also summarizes the current state of research on the HFA issue. A clearer understanding of both psychology and neurophysiology of high-functioning autism will help ensure accurate diagnosis, avoiding errors in therapy planning and support.&lt;/p&gt; &lt;p style="text-align: justify;"&gt;&lt;strong&gt;Methods.&lt;/strong&gt; We reviewed literature sources in the PubMed, MedLine, and Scientific Electronic Library databases. The main search terms were: high-functioning autism, HFA, Asperger&amp;rsquo;s syndrome, autism spectrum disorders (ASD), diagnosis and speech disorders. Forty-two articles by foreign and domestic specialists were included in the analysis.&lt;/p&gt; &lt;p style="text-align: justify;"&gt;&lt;strong&gt;Results.&lt;/strong&gt; The developmental profile of individuals with high-functioning autism differs from that of individuals with autism and cognitive or speech impairments. It is characterized by a distinctive style of social interaction and a higher level of speech and cognitive development. A high level of intelligence helps people with HFA master social rules and adapt more effectively.&lt;/p&gt; &lt;p style="text-align: justify;"&gt;&lt;strong&gt;Conclusions.&lt;/strong&gt; Social impairments in individuals with high-functioning autism are difficult to identify in early childhood, partly due to the lack of developed diagnostic tools. Therefore, there is a need for more careful assessment of children suspected of having high-functioning autism, as well as the development of reliable, sensitive assessment tools for follow-up therapy and support.&lt;/p&gt;

Endometriosis - A Medical Challenge: Impact on Fertility and Treatment Method

Aim of study: The subject of this review is to highlight the complexity of the disease known as endometriosis. This disease affects 10% of women of reproductive age, causing a number of symptoms of various origins, and additionally affects women’s fertility, mental health and role in society. The work aims to systematize knowledge about endometriosis, the mechanism by which it affects fertility and possible therapies, including surgical methods and assisted reproductive technology (ART.). The issue of infertility associated with endometriosis is has not been fully explored yet. A personalized treatment plan including medication, surgical assisted reproductive techniques and psychological support should be developed to improve the quality of life of patients with endometriosis and enable them to become pregnant. Material and methods: A systematic review of scientific and medical literature from the PubMed and Google Scholar databases was conducted. Results: Currently, the most effective treatment for infertility is in vitro fertilization (IVF). Successful treatment of endometriosis-related infertility should be discussed in detail with each patient and the decision on the therapy plan should be individual and comprehensive. Keywords: endometriosis, infertility, chronic pelvic pain, gynecology, IVF, IVI

Calcified Amorphous Tumor and Granulomatosis with Polyangiitis—Case Report and Systematic Review of the Literature

Background: Calcified amorphous tumor (CAT) is a rare, mostly incidental tumor-like cardiac lesion of unknown histogenesis. Current imaging modalities do not differentiate between CAT and other masses. As it can be a source for embolization, surgical excision of CAT is mandatory. CAT in patients with Granulomatosis with polyangiitis (GPA) is exceedingly rare. Methods: This systematic literature review was prompted by the case of a CAT in a patient with GPA. The search of all types of studies in two databases (PubMed and Scopus) was conducted through November 2024 to identify the relevant studies. Results: Nine studies were included describing cases of patients being diagnosed with GPA and a cardiac mass. All included patients had a histopathological examination of the either biopsied or surgically resected mass. Only one case reported a CAT. In our case, the patient was diagnosed with GPA through a kidney biopsy, whereas a cardiac mass in the right atrium was diagnosed by echocardiography during evaluation for possible kidney transplantation. One year later a progression was observed, and the mass was resected. The histopathological examination revealed a CAT. The patient could be successfully discharged in a good clinical condition. Conclusions: This systematic literature search and case report highlight the importance of regular echocardiographic examination in patients with GPA. Moreover, surgical excision is crucial for the diagnosis and for further therapy planning, regardless of whether the mass is neoplastic or not.

Predictors of treatment duration in conservative management of developmental dysplasia of hip -a retrospective cohort study

Developmental dysplasia of the hip is a prevalent condition in newborns. However, predicting the duration of conservative treatment remains challenging. This study aimed to determine the duration of treatment more precisely by analyzing associated factors. We conducted a retrospective analysis and developed a linear regression model based on 503 patients treated at our institution over the last 10 years. A linear regression model (GLM) was used for predicting treatment duration (df residuals 371, df model 3, Pearson Chi2 78.9, Number of iterations 15). The baseline scenario thereby feature a child with an average age at the beginning of treatment (35th day of life), both sides pathologically affected, and a minimum alpha angle of 29 degrees. The GLM identified age at treatment onset, alpha angle, and bilaterality as significant predictors of treatment duration. A four-week delay in treatment initiation extended the duration by one week, while a 5-degree increase in the alpha angle reduced it by two weeks. Bilaterality added 19 days to treatment duration. However, sex and clinical hip instability did not significantly affect the treatment time. These findings enable the calculation of treatment duration based on identified factors, potentially improving the management and planning of conservative therapies for developmental dysplasia of the hip in newborns.

In-House Fabrication and Validation of 3D-Printed Custom-Made Medical Devices for Planning and Simulation of Peripheral Endovascular Therapies.

Objectives: This study aims to develop and validate a standardized methodology for creating high-fidelity, custom-made, patient-specific 3D-printed vascular models that serve as tools for preoperative planning and training in the endovascular treatment of peripheral artery disease (PAD). Methods: Ten custom-made 3D-printed vascular models were produced using computed tomography angiography (CTA) scans of ten patients diagnosed with PAD. CTA images were analyzed using Syngo.via by a specialist to formulate a medical prescription that guided the model's creation. The CTA data were then processed in OsiriX MD to generate the .STL file, which is further refined in a Meshmixer. Stereolithography (SLA) 3D printing technology was employed, utilizing either flexible or rigid materials. The dimensional accuracy of the models was evaluated by comparing their CT scan images with the corresponding patient data, using OsiriX MD. Additionally, both flexible and rigid models were evaluated by eight vascular surgeons during simulations in an in-house-designed setup, assessing both the technical aspects and operator perceptions of the simulation. Results: Each model took approximately 21.5 h to fabricate, costing €140 for flexible and €165 for rigid materials. Bland-Alman plots revealed a strong agreement between the 3D models and patient anatomy, with outliers ranging from 4.3% to 6.9%. Simulations showed that rigid models performed better in guidewire navigation and catheter stability, while flexible models offered improved transparency and lesion treatment. Surgeons confirmed the models' realism and utility. Conclusions: The study highlights the cost-efficient, high-fidelity production of 3D-printed vascular models, emphasizing their potential to enhance training and planning in endovascular surgery.

The Intersection of Laboratory Testing and Physical Therapy: Implications for Patient Rehabilitation – A Systematic Review

This systematic review explores the intersection of laboratory testing and physical therapy in the context of patient rehabilitation, emphasizing the role of diagnostic markers in optimizing therapeutic outcomes. The integration of laboratory diagnostics into physical therapy practices has gained significant attention, as it enables more personalized and effective rehabilitation strategies. This review synthesizes findings from recent studies, highlighting the influence of laboratory tests, such as blood biomarkers, imaging, and metabolic evaluations, on tailoring therapy plans and enhancing recovery. Results demonstrate the potential of diagnostic data to refine physical therapy interventions, improve patient outcomes, and reduce recovery times. However, challenges such as cost, accessibility, and the need for interdisciplinary collaboration remain critical considerations. The findings underline the importance of leveraging laboratory diagnostics to advance evidence-based physical therapy and promote comprehensive, patient-centered care.

Performance of Commercial Deep Learning-Based Auto-Segmentation Software for Breast Cancer Radiation Therapy Planning: A Systematic Review

As yet, no systematic review on commercial deep learning-based auto-segmentation (DLAS) software for breast cancer radiation therapy (RT) planning has been published, although NRG Oncology has highlighted the necessity for such. The purpose of this systematic review is to investigate the performances of commercial DLAS software packages for breast cancer RT planning and methods for their performance evaluation. A literature search was conducted with the use of electronic databases. Fifteen papers met the selection criteria and were included. The included studies evaluated eight software packages (Limbus Contour, Manteia AccuLearning, Mirada DLCExpert, MVision.ai Contour+, Radformation AutoContour, RaySearch RayStation, Siemens syngo.via RT Image Suite/AI-Rad Companion Organs RT, and Therapanacea Annotate). Their findings show that the DLAS software could contour ten organs at risk (body, contralateral breast, esophagus-overlapping area, heart, ipsilateral humeral head, left and right lungs, liver, and sternum and trachea) and three clinical target volumes (CTVp_breast, CTVp_chestwall, and CTVn_L1) up to the clinically acceptable standard. This can contribute to 45.4%–93.7% contouring time reduction per patient. Although NRO Oncology has suggested that every clinical center should conduct its own DLAS software evaluation before clinical implementation, such testing appears particularly crucial for Manteia AccuLearning, Mirada DLCExpert, and MVision.ai Contour+ as a result of the methodological weaknesses of the corresponding studies such as the use of small datasets collected retrospectively from single centers for the evaluation.

Hypoxia-guided treatment planning for lung cancer with dose painting by numbers.

Tumor hypoxia significantly impacts the efficacy of radiotherapy. Recent developments in the technique of dose painting by numbers (DPBN) promise to improve the tumor control probability (TCP) in conventional radiotherapy for hypoxic cancer. The study initially combined the DPBN method with hypoxia-guided dose distribution optimization to overcome hypoxia for lung cancers and evaluated the effectiveness and appropriateness for clinical use of the DPBN plans. 18F-FMISO PET-CT scans from 13 lung cancer patients were retrospectively employed in our study to make hypoxia-guided radiotherapy. In the clinic, TCP and normal tissue complication probability (NTCP) derived from the DPBN plans in comparison to conventional intensity modulated radiation therapy (IMRT) plans were evaluated. Additionally, in order to investigate the improved clinical suitability, the robustness of DPBN plans in response to potential patient positioning errors and radiation resistance variations throughout the treatment course was assessed. The DPBN approach, employing voxelized prescription doses, led to an average increase of 24.47% in TCP, alongside a reduction of 1.83% in NTCP, compared to the conventional radiotherapy treatment plans. Regarding the robustness of the DPBN plans, it was observed that positional uncertainties were limited to 2mm and radiosensitivity deviations were within 4%. The lung NTCP showed a 0.05% increase when the isocenter was moved by 3mm in any direction, suggesting that the DPBN plan meets clinical acceptability criteria. Our study has shown that the DPBN technique has significant potential as an innovative approach to enhance the efficacy of radiotherapy for lung cancer with hypoxic regions.

Artificial intelligence in radiation therapy treatment planning: A discrete choice experiment.

The application of artificial intelligence (AI) in radiation therapy holds promise for addressing challenges, such as healthcare staff shortages, increased efficiency and treatment planning variations. Increased AI adoption has the potential to standardise treatment protocols, enhance quality, improve patient outcomes, and reduce costs. However, drawbacks include impacts on employment and algorithmic biases, making it crucial to navigate trade-offs. A discrete choice experiment (DCE) was undertaken to examine the AI-related characteristics radiation oncology professionals think are most important for adoption in radiation therapy treatment planning. Radiation oncology professionals completed an online discrete choice experiment to express their preferences about AI systems for radiation therapy planning which were described by five attributes, each with 2-4 levels: accuracy, automation, exploratory ability, compatibility with other systems and impact on workload. The survey also included questions about attitudes to AI. Choices were modelled using mixed logit regression. The survey was completed by 82 respondents. The results showed they preferred AI systems that offer the largest time saving, and that provide explanations of the AI reasoning (both in-depth and basic). They also favoured systems that provide improved contouring precision compared with manual systems. Respondents emphasised the importance of AI systems being cost-effective, while also recognising AI's impact on professional roles, responsibilities, and service delivery. This study provides important information about radiation oncology professionals' priorities for AI in treatment planning. The findings from this study can be used to inform future research on economic evaluations and management perspectives of AI-driven technologies in radiation therapy.

Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?

Knowledge-based planning (KBP) can consistently and efficiently create high-quality Volumetric Arc Therapy (VMAT) plans for cervix cancer. This study describes the cross-validation of two KBP models on geographically distinct populations and their comparison to manual plans from 67 centers. The purpose was to determine the universal applicability of a generic KBP model. Based on the EMBRACE-II protocol, two KBP models were developed at XXXX and YYYY using respective patient plans. The KBP models were exchanged between three institutions with different geo-ethnic populations and validated on reference manual plans of 20 node-positive and 20 node-negative patients. Additionally, one patient case was manually planned by 67 centres. These manual treatment plans were compared to the two KBP model plans using a score out of 80, based on 20 DVH parameters. The manual and the KBP plans adhered to the EMBRACE II protocol. OAR sparing in KBP plans was similar or slightly improved as compared to the manual plans. The differences between the medians of manual and either KBP model plans were significant for 8 parameters among node positive patients, and 4 parameters among node negative patients. The comparison between the XXXX and YYYY KBP plans to manual plans from 67 institutions showed that the two KPBs had superior plan quality in 88 % and 99 % of instances, respectively. KBP has the potential to generate high-quality plans across institutions and geo-ethnic populations by reducing inter-planner variation, thereby facilitating the global standardisation of radiotherapy for cervical cancer.

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.

68Ga-PSMA PET CT/MRI in the initial diagnosis and staging of prostate cancer: A review

Prostate-specific membrane antigen-positron emission tomography (PSMA-PET) imaging has demonstrated potential in addressing prostate cancer (PCa) diagnostic difficulties. According to current guidelines, gallium-68 (68Ga)-PSMA-PET is used as an adjunct to traditional imaging modalities in patients with primary PCa. The purpose of this review, conducted using Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, is to give an overview of studies that have examined the role of 68Ga-PSMA in the initial diagnosis of PCa, its performance in TNM staging, its correlation with prostate-specific antigen (PSA) levels, targeted biopsies, and the International Society of Urological Pathology (ISUP) scores using computed tomography (CT) or magnetic resonance imaging (MRI). The findings demonstrate that, in addition to MRI alone, combining 68Ga-PSMA-PET with MRI-targeted biopsy improves the initial identification of clinically significant prostate cancer (csPCa), particularly for ambiguous prostate imaging-reporting and data system (PI-RADS) three lesions. 68Ga-PSMA-PET/CT is useful when MRI results for csPCa are uncertain, but consistent techniques are required. Regarding risk assessment and therapy planning, 68Ga-PSMA-PET has a strong correlation with both PSA levels and ISUP scores. It accurately detects primary PCa lesions, making it suitable for high-risk patients. In 68Ga-PSMA-PET, higher maximum standardized uptake value (SUVmax) readings are linked to more aggressive illness. For N and M staging, 68Ga-PSMA-PET/CT is more sensitive and specific than conventional imaging; however, for T-staging, multiparametric MRI (mpMRI) provides better accuracy. 68Ga-PSMA-PET/MRI shows improved accuracy for primary PCa detection compared to mpMRI alone. Challenges include the lack of standardized SUVmax cutoff values. 68Ga-PSMA-PET is useful for the initial diagnosis and staging of PCa, complementing MRI, although further research is needed to standardize imaging techniques and interpretations.

Exploring the efficacy of integrative medicine for chronic conditions: The role of combining allopathy, ayurveda, homeopathy, naturopathy, diet and lifestyle

Chronic diseases are significant and increasing causes of illness and disability throughout the world with significant targeted implications for individual quality of life as well as health systems. Even though these medicines have been proven to be very effective in the so-called ‘acute ‘symptomatic relief ‘of ailments, the conventional biomedicine diagnosis and treatment regimens, particularly the drugs and medicines do not effectively address the chronic diseases that are lifestyle diseases with psychological connotations like cardiovascular diseases, diabetes mellitus or arthritis, etc. Thus, a treatment or therapy plan based on a patient’s constitution and lifestyle might be the solution to improved compliance as well as satisfaction with the integrative approach. However, this is a model that has some concerns of confusion with the pluralism of the treatment approach; thus, it may pose a threat to the modality and standardization while handled by specialized players. However, walking around various therapeutic modalities could initially amount to higher costs and although the costs could be higher, long-term implications such as lowered disease complications and hospitalizations could lead to more cost savings.