A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes.

Identifying cancer driver genes plays a curial role in the development of precision oncology and cancer therapeutics. Although a plethora of methods have been developed to tackle this problem, the complex cancer mechanisms and intricate interactions between genes still make the identification of cancer driver genes challenging. In this work, we propose a novel machine learning method of heterophilic graph diffusion convolutional networks (called HGDCs) to boost cancer-driver gene identification. Specifically, HGDC first introduces graph diffusion to generate an auxiliary network for capturing the structurally similar nodes in a biomolecular network. Then, HGDC designs an improved message aggregation and propagation scheme to adapt to the heterophilic setting of biomolecular networks, alleviating the problem of driver gene features being smoothed by its neighboring dissimilar genes. Finally, HGDC uses a layer-wise attention classifier to predict the probability of one gene being a cancer driver gene. In the comparison experiments with other existing state-of-the-art methods, our HGDC achieves outstanding performance in identifying cancer driver genes. The experimental results demonstrate that HGDC not only effectively identifies well-known driver genes on different networks but also novel candidate cancer genes. Moreover, HGDC can effectively prioritize cancer driver genes for individual patients. Particularly, HGDC can identify patient-specific additional driver genes, which work together with the well-known driver genes to cooperatively promote tumorigenesis.

Predicting Lipid-Rich Plaque Progression in Coronary Arteries Using Multimodal Imaging and Wall Shear Stress Signatures.

BACKGROUND: Plaque composition and wall shear stress (WSS) magnitude act as well-established players in coronary plaque progression. However, WSS magnitude per se does not completely capture the mechanical stimulus to which the endothelium is subjected, since endothelial cells experience changes in the WSS spatiotemporal configuration on the luminal surface. This study explores WSS profile and lipid content signatures of plaque progression to identify novel biomarkers of coronary atherosclerosis. METHODS: Thirty-seven patients with acute coronary syndrome underwent coronary computed tomography angiography, near-infrared spectroscopy intravascular ultrasound, and optical coherence tomography of at least 1 nonculprit vessel at baseline and 1-year follow-up. Baseline coronary artery geometries were reconstructed from intravascular ultrasound and coronary computed tomography angiography and combined with flow information to perform computational fluid dynamics simulations to assess the time-averaged WSS magnitude (TAWSS) and the variability in the contraction/expansion action exerted by WSS on the endothelium, quantifiable in terms of topological shear variation index (TSVI). Plaque progression was measured as intravascular ultrasound-derived percentage plaque atheroma volume change at 1-year follow-up. Plaque composition information was extracted from near-infrared spectroscopy and optical coherence tomography. RESULTS: Exposure to high TSVI and low TAWSS was associated with higher plaque progression (4.00±0.69% and 3.60±0.62%, respectively). Plaque composition acted synergistically with TSVI or TAWSS, resulting in the highest plaque progression (≥5.90%) at locations where lipid-rich plaque is exposed to high TSVI or low TAWSS. CONCLUSIONS: Luminal exposure to high TSVI, solely or combined with a lipid-rich plaque phenotype, is associated with enhanced plaque progression at 1-year follow-up. Where plaque progression occurred, low TAWSS was also observed. These findings suggest TSVI, in addition to low TAWSS, as a potential biomechanical predictor for plaque progression, showing promise for clinical translation to improve patient prognosis.

Plaque Ruptures Are Related to High Plaque Stress and Strain Conditions: Direct Verification by Using In Vivo OCT Rupture Data and FSI Models.

BACKGROUND: While it has been hypothesized that high plaque stress and strain may be related to plaque rupture, its direct verification using in vivo coronary plaque rupture data and full 3-dimensional fluid-structure interaction models is lacking in the current literature due to difficulty in obtaining in vivo plaque rupture imaging data from patients with acute coronary syndrome. This case-control study aims to use high-resolution optical coherence tomography-verified in vivo plaque rupture data and 3-dimensional fluid-structure interaction models to seek direct evidence for the high plaque stress/strain hypothesis. METHODS: In vivo coronary plaque optical coherence tomography data (5 ruptured plaques, 5 no-rupture plaques) were acquired from patients using a protocol approved by the local institutional review board with informed consent obtained. The ruptured caps were reconstructed to their prerupture morphology using neighboring plaque cap and vessel geometries. Optical coherence tomography-based 3-dimensional fluid-structure interaction models were constructed to obtain plaque stress, strain, and flow shear stress data for comparative analysis. The rank-sum test in the nonparametric test was used for statistical analysis. RESULTS: Our results showed that the average maximum cap stress and strain values of ruptured plaques were 142% (457.70 versus 189.22 kPa; P=0.0278) and 48% (0.2267 versus 0.1527 kPa; P=0.0476) higher than that for no-rupture plaques, respectively. The mean values of maximum flow shear stresses for ruptured and no-rupture plaques were 145.02 dyn/cm2 and 81.92 dyn/cm2 (P=0.1111), respectively. However, the flow shear stress difference was not statistically significant. CONCLUSIONS: This preliminary case-control study showed that the ruptured plaque group had higher mean maximum stress and strain values. Due to our small study size, larger scale studies are needed to further validate our findings.

Hemodynamics and Wall Mechanics of Vascular Graft Failure.

Blood vessels are subjected to complex biomechanical loads, primarily from pressure-driven blood flow. Abnormal loading associated with vascular grafts, arising from altered hemodynamics or wall mechanics, can cause acute and progressive vascular failure and end-organ dysfunction. Perturbations to mechanobiological stimuli experienced by vascular cells contribute to remodeling of the vascular wall via activation of mechanosensitive signaling pathways and subsequent changes in gene expression and associated turnover of cells and extracellular matrix. In this review, we outline experimental and computational tools used to quantify metrics of biomechanical loading in vascular grafts and highlight those that show potential in predicting graft failure for diverse disease contexts. We include metrics derived from both fluid and solid mechanics that drive feedback loops between mechanobiological processes and changes in the biomechanical state that govern the natural history of vascular grafts. As illustrative examples, we consider application-specific coronary artery bypass grafts, peripheral vascular grafts, and tissue-engineered vascular grafts for congenital heart surgery as each of these involves unique circulatory environments, loading magnitudes, and graft materials.

Patient-specific signaling signatures predict optimal therapeutic combinations for triple negative breast cancer.

Triple negative breast cancer (TNBC) is a heterogeneous group of tumors which lack estrogen receptor, progesterone receptor, and HER2 expression. Targeted therapies have limited success in treating TNBC, thus a strategy enabling effective targeted combinations is an unmet need. To tackle these challenges and discover individualized targeted combination therapies for TNBC, we integrated phosphoproteomic analysis of altered signaling networks with patient-specific signaling signature (PaSSS) analysis using an information-theoretic, thermodynamic-based approach. Using this method on a large number of TNBC patient-derived tumors (PDX), we were able to thoroughly characterize each PDX by computing a patient-specific set of unbalanced signaling processes and assigning a personalized therapy based on them. We discovered that each tumor has an average of two separate processes, and that, consistent with prior research, EGFR is a major core target in at least one of them in half of the tumors analyzed. However, anti-EGFR monotherapies were predicted to be ineffective, thus we developed personalized combination treatments based on PaSSS. These were predicted to induce anti-EGFR responses or to be used to develop an alternative therapy if EGFR was not present.In-vivo experimental validation of the predicted therapy showed that PaSSS predictions were more accurate than other therapies. Thus, we suggest that a detailed identification of molecular imbalances is necessary to tailor therapy for each TNBC. In summary, we propose a new strategy to design personalized therapy for TNBC using pY proteomics and PaSSS analysis. This method can be applied to different cancer types to improve response to the biomarker-based treatment.

A patient-based murine model recapitulates human STAT3 gain-of-function syndrome.

STAT3 gain-of-function (GOF) variants results in a heterogeneous clinical syndrome characterized by early onset immunodeficiency, multi-organ autoimmunity, and lymphoproliferation. While 191 documented cases with STAT3 GOF variants have been reported, the impact of individual variants on immune regulation and the broad clinical spectrum remains unclear. We developed a Stat3p.L387R mouse model, mirroring a variant identified in a family exhibiting common STAT3 GOF symptoms, and rare phenotypes including pulmonary hypertension and retinal vasculitis. In vitro experiments revealed increased STAT3 phosphorylation, nuclear migration, and DNA binding of the variant. Our Stat3p.L387R model displayed similar traits from previous Stat3GOF strains, such as splenomegaly and lymphadenopathy. Notably, Stat3p.L387R/+ mice exhibited heightened embryonic lethality compared to prior Stat3GOF/+ models and ocular abnormalities were observed. This research underscores the variant-specific pathology in Stat3p.L387R/+ mice, highlighting the ability to recapitulate human STAT3 GOF syndrome in patient-specific transgenic murine models. Additionally, such models could facilitate tailored treatment development.

Initial needle tracking with the first standalone combined infrared camera - CT system for brachytherapy-analysis of tracking accuracy and uncertainties.

PURPOSE: A prototype infrared camera - cone-beam computed tomography (CBCT) system for tracking in brachytherapy has recently been developed. We evaluated for the first time the corresponding tracking accuracy and uncertainties, and implemented a tracking-based prediction of needles on CBCT scans. METHODS: A marker tool rigidly attached to needles was 3D printed. The precision and accuracy of tool tracking was then evaluated for both static and dynamic scenarios. Euclidean distances between the tracked and CBCT-derived markers were assessed as well. To implement needle tracking, ground truth models of the tool attached to 200 mm and 160 mm needles were matched to the tracked positions in order to project the needles into CBCT scans. Deviations between projected and actual needle tips were measured. Finally, we put our results into perspective with simulations of the system's tracking uncertainties. RESULTS: For the stationary scenario and dynamic movements, we achieved tool-tracking precision and accuracy of 0.04 ± 0.06 mm and 0.16 ± 0.18 mm, respectively. The tracked marker positions differed by 0.52 ± 0.18 mm from the positions determined via CBCT. In addition, the predicted needle tips in air deviated from the actual tip positions by only 1.62 ± 0.68 mm (200 mm needle) and 1.49 ± 0.62 mm (160 mm needle). The simulated tracking uncertainties resulted in tip variations of 1.58 ± 0.91 mm and 1.31 ± 0.69 mm for the 200 mm and 160 mm needles, respectively. CONCLUSION: With the innovative system it was possible to achieve a high tracking and prediction accuracy of marker tool and needles. The system shows high potential for applicator tracking in brachytherapy.

Implementation of surgical rehearsal utilizing patient specific hydrogel kidney phantoms prior to complex renal cancer surgery: a pilot study.

INTRODUCTION: With the advancement of surgical technology, the opportunity to integrate novel surgical preparation is imperative to improve patient outcomes and enhance safety. METHODS: Patient specific perfused kidney phantoms including the tumor, parenchyma, artery, vein, and calyx were fabricated using 3D-printing and hydrogel injection molding from scans of 25 patients scheduled for robotic partial-nephrectomy (RAPN). Models are validated for anatomical accuracy, mechanical, functional properties and surrounded by the other models of relevant anatomy in a body cast for a simulated surgical rehearsal. We investigated the impact of these preoperative rehearsals preceding complex RAPN by analyzing changes in surgeons' decisions following review of both axial-imaging and following rehearsal simulation. Predictive ability of these rehearsal platforms was compared to live surgery outcomes and trifecta of cases as an outcome was calculated. RESULTS: 25 patients with complex renal tumors, average 9.8 nephrometry score and 4.9 cm mean tumor diameter were consented. Mean blood loss and WIT were 193.2 ml and 19.8 min. Two Clavien 2 complications were reported at 30-day postoperative. Trifecta was achieved in 17 (68%) of surgical cases. Surgeons' confidence in their ability to complete a partial nephrectomy and ability to predict WIT significantly increased from initial viewing the axial imaging to after the rehearsal. The correlation coefficient between the procedural clinical data collected during the rehearsals and live surgery were calculated. CONCLUSION: The application of this versatile method for creating authentic perfused kidney phantoms can result in increased confidence in surgical plan and thus improved surgical performance and outcomes.

Pre-operative lung ablation prediction using deep learning.

OBJECTIVE: Microwave lung ablation (MWA) is a minimally invasive and inexpensive alternative cancer treatment for patients who are not candidates for surgery/radiotherapy. However, a major challenge for MWA is its relatively high tumor recurrence rates, due to incomplete treatment as a result of inaccurate planning. We introduce a patient-specific, deep-learning model to accurately predict post-treatment ablation zones to aid planning and enable effective treatments. MATERIALS AND METHODS: Our IRB-approved retrospective study consisted of ablations with a single applicator/burn/vendor between 01/2015 and 01/2019. The input data included pre-procedure computerized tomography (CT), ablation power/time, and applicator position. The ground truth ablation zone was segmented from follow-up CT post-treatment. Novel deformable image registration optimized for ablation scans and an applicator-centric co-ordinate system for data analysis were applied. Our prediction model was based on the U-net architecture. The registrations were evaluated using target registration error (TRE) and predictions using Bland-Altman plots, Dice co-efficient, precision, and recall, compared against the applicator vendor's estimates. RESULTS: The data included 113 unique ablations from 72 patients (median age 57, interquartile range (IQR) (49-67); 41 women). We obtained a TRE ≤ 2 mm on 52 ablations. Our prediction had no bias from ground truth ablation volumes (p = 0.169) unlike the vendor's estimate (p < 0.001) and had smaller limits of agreement (p < 0.001). An 11% improvement was achieved in the Dice score. The ability to account for patient-specific in-vivo anatomical effects due to vessels, chest wall, heart, lung boundaries, and fissures was shown. CONCLUSIONS: We demonstrated a patient-specific deep-learning model to predict the ablation treatment effect prior to the procedure, with the potential for improved planning, achieving complete treatments, and reduce tumor recurrence. CLINICAL RELEVANCE STATEMENT: Our method addresses the current lack of reliable tools to estimate ablation extents, required for ensuring successful ablation treatments. The potential clinical implications include improved treatment planning, ensuring complete treatments, and reducing tumor recurrence.

Development of a patient-specific model of the human coronary system for percutaneous transluminal coronary angioplasty balloon catheter training and testing.

BACKGROUND: To treat stenosed coronary arteries, percutaneous transluminal coronary angioplasty (PTCA) balloon catheters must combine pushability, trackability, crossability, and rewrap behavior. The existing anatomic track model (ASTM F2394) for catheter testing lacks 3D morphology, vessel tortuosity, and compliance, making evaluating performance characteristics difficult. This study aimed to develop a three-dimensional patient-specific phantom (3DPSP) for device testing and safe training for interventional cardiologists. METHODS: A range of silicone materials with different shore hardnesses (00-30-45 A) and wall thicknesses (0.5 mm, 1 mm, 2 mm) were tested to determine compliance for creating coronary vessel phantoms. Compliance was assessed using optical coherence tomography (OCT) and compared to values in the literature. Stenosis was induced using multilayer casting and brushing methods, with gypsum added for calcification. The radial tensile properties of the samples were investigated, and the relationship between Young's modulus and compliance was determined. Various methods have been introduced to approximate the friction between silicone and real coronary vessel walls. Computerized tomography (CT) scans were used to obtain patient-specific anatomy from the femoral artery to the coronary arteries. Artery lumens were segmented from the CT scans to create dissolvable 3D-printed core models. RESULTS: A 15A shore hardness silicone yielded an experimental compliance of 12.3-22.4 m m 2 mmHg · 10 3 for stenosed tubes and 14.7-57.9 m m 2 mmHg · 10 3 for uniform tubes, aligning closely with the literature data (6.28-40.88 m m 2 mmHg · 10 3 ). The Young's modulus ranged from 43.2 to 75.5 kPa and 56.6-67.9 kPa for the uniform and calcified materials, respectively. The dependency of the compliance on the wall thickness, Young's modulus, and inner diameter could be shown. Introducing a lubricant reduced the silicone friction coefficient from 0.52 to 0.13. The 3DPSP was successfully fabricated, and comparative analyses were conducted among eight commercially available catheters. CONCLUSION: This study presents a novel method for crafting 3DPSPs with realistic mechanical and frictional properties. The proposed approach enables the creation of comprehensive and anatomically precise setups spanning the right femoral artery to the coronary arteries, highlighting the importance of such realistic environments for advancing medical device development and fostering safe training conditions.

An In Silico Model for Predicting the Efficacy of Edge-to-Edge Repair for Mitral Regurgitation.

In recent years, transcatheter edge-to-edge repair (TEER) has been widely adopted as an effective treatment for mitral regurgitation (MR). The aim of this study is to develop a personalized in silico model to predict the effect of edge-to-edge repair in advance to the procedure for each individual patient. For this purpose, we propose a combination of a valve deformation model for computing the mitral valve (MV) orifice area (MVOA) and a lumped parameter model for the hemodynamics, specifically mitral regurgitation volume (RVol). Although we cannot obtain detailed information on the three-dimensional flow field near the mitral valve, we can rapidly simulate the important medical parameters for the clinical decision support. In the present method, we construct the patient-specific pre-operative models by using the parameter optimization and then simulate the postoperative state by applying the additional clipping condition. The computed preclip MVOAs show good agreement with the clinical measurements, and the correlation coefficient takes 0.998. In addition, the MR grade in terms of RVol also has good correlation with the grade by ground truth MVOA. Finally, we try to investigate the applicability for the predicting the postclip state. The simulated valve shapes clearly show the well-known double orifice and the improvement of the MVOA, compared with the preclip state. Similarly, we confirmed the improved reverse flow and MR grade in terms of RVol. A total computational time is approximately 8 h by using general-purpose PC. These results obviously indicate that the present in silico model has good capability for the assessment of edge-to-edge repair.

First experiences of a hospital-based 3D printing facility - an analytical observational study.

PURPOSE: To identify the clinical impact and potential benefits of in-house 3D-printed objects through a questionnaire, focusing on three principal areas: patient education; interdisciplinary cooperation; preoperative planning and perioperative execution. MATERIALS AND METHODS: Questionnaires were sent from January 2021 to August 2022. Participants were directed to rate on a scale from 1 to 10. RESULTS: The response rate was 43%. The results of the rated questions are averages. 84% reported using 3D-printed objects in informing the patient about their condition/procedure. Clinician-reported improvement in patient understanding of their procedure/disease was 8.1. The importance of in-house placement was rated 9.2. 96% reported using the 3D model to confer with colleagues. Delay in treatment due to 3D printing lead-time was 1.8. The degree with which preoperative planning was altered was 6.9. The improvement in clinician perceived preoperative confidence was 8.3. The degree with which the scope of the procedure was affected, in regard to invasiveness, was 5.6, wherein a score of 5 is taken to mean unchanged. Reduction in surgical duration was rated 5.7. CONCLUSION: Clinicians report the utilization of 3D printing in surgical specialties improves procedures pre- and intraoperatively, has a potential for increasing patient engagement and insight, and in-house location of a 3D printing center results in improved interdisciplinary cooperation and allows broader access with only minimal delay in treatment due to lead-time.

The Transformative Potential of AI in Obstetrics and Gynaecology.

The transformative power of artificial intelligence (AI) is reshaping diverse domains of medicine. Recent progress, catalyzed by computing advancements, has seen commensurate adoption of AI technologies within obstetrics and gynaecology. We explore the use and potential of AI in three focus areas: predictive modelling for pregnancy complications, Deep learning-based image interpretation for precise diagnoses, and large language models enabling intelligent health care assistants. We also provide recommendations for the ethical implementation, governance of AI, and promote research into AI explainability, which are crucial for responsible AI integration and deployment. AI promises a revolutionary era of personalized health care in obstetrics and gynaecology.

Development of a complex Interdisciplinary Nurse-coordinated SELf-MAnagement (INSELMA) intervention for patients with inflammatory arthritis.

BACKGROUND: Apart from a consistent focus on treating inflammation, patients with inflammatory arthritis (IA) report a range of unmet needs. Many experience not only residual symptoms but also various other physical, psychological, and social effects. Therefore, this study aimed to develop a complex Interdisciplinary Nurse-coordinated self-management (INSELMA) intervention for patients with IA, as an add-on treatment to usual outpatient care for those with substantial disease impact. METHODS: This study followed the British Medical Research Council's updated framework for developing complex interventions. The process encompassed the following steps: (1) The evidence base was identified; (2) workshops were held, involving 38 relevant stakeholders (managers, physicians, nurses, physiotherapists, occupational therapists, social workers, psychologists from hospitals and municipalities, and two patient research partners), to discuss and further develop the preliminary ideas; (3) relevant theories were identified (i.e., self-efficacy, acceptance and commitment therapy, and health literacy); (4) the intervention was modeled and remodeled and (5) the results, describing the final INSELMA intervention and outcomes. RESULTS: The INSELMA intervention encompasses an initial biopsychosocial assessment, which is performed by a rheumatology nurse. Then, activities that the participant wishes to improve are identified and goals are set. The nurse refers the participant to a multidisciplinary team and coordinates their support and relevant services in the participant's municipality. In addition, the health professionals have the opportunity to hold two interdisciplinary conferences during the intervention period. The participant and the health professionals work to achieve the set goals during a 6-month period, which ends with a status assessment and a discussion of further needs. The INSELMA intervention aims to increase self-management, reduce the impact of IA (e.g., pain, fatigue, sleep problems, and absenteeism), and increase self-efficacy, quality of life, mental well-being, work ability, and physical activity. CONCLUSIONS: The development of the INSELMA intervention involved stakeholders from two Danish rheumatology outpatient clinics, patient research partners and municipalities. We believe that we have identified important mechanisms to increase the self-management and quality of life of people with IA and to decrease the disease impact in those who are substantially affected. The health professionals involved have developed competences in delivering the intervention and it is ready to be tested in a feasibility study.

Patient-specific guides for consistently achieving R0 bone margins after resection of primary malignant bone tumors of the pelvis.

AIMS: Primary malignant bone tumor of the pelvis is an uncommon lesion, the resection of which via freehand osteotomy is subject to inaccuracy due to its three-dimensional anatomy. Patient-Specific Guides (PSG), also called Patient-Specific Instruments (PSI) are essential to ensure surgical planning and resection adequacy. Our aim was to assess their use and effectiveness. METHODS: A monocentric retrospective study was conducted on 42 adult patients who underwent PSG-based resection of a primary malignant bone tumor of the pelvis. The primary outcome was the proportion of R0 bone margins. The secondary outcomes were the proportion of overall R0 margins, considering soft-tissue resection, the cumulative incidence of local recurrence, and the time of production for the guides. A comparison to a previous series at our institution was performed regarding histological margins. RESULTS: Using PSGs, 100% R0 safe bone margin was achieved, and 88% overall R0 margin due to soft-tissue resection being contaminated, while the comparison to the previous series showed only 80% of R0 safe bone margin. The cumulative incidences of local recurrence were 10% (95% CI: 4-20%) at one year, 15% (95% CI: 6-27%) at two years, and 19% (95% CI: 8-33%) at five years. The median overall duration of the fabrication process of the guide was 35 days (Q1-Q3: 26-47) from the first contact to the surgery date. CONCLUSIONS: Patient-Specific Guides can provide a reproducible safe bony margin.

Biomechanical study of spinal cord and nerve root in idiopathic scoliosis: based on finite element analysis.

BACKGROUND: Current research lacks comprehensive investigation into the biomechanical changes in the spinal cord and nerve roots during scoliosis correction. This study employs finite element analysis to extensively explore these biomechanical variations across different Cobb angles, providing valuable insights for clinical treatment. METHODS: A personalized finite element model, incorporating vertebrae, ligaments, spinal cord, and nerve roots, was constructed using engineering software. Forces and displacements were applied to achieve Cobb angle improvements, designating T1/2-T4/5 as the upper segment, T5/6-T8/9 as the middle segment, and T9/10-L1/2 as the lower segment. Simulations under traction, pushing, and traction + torsion conditions were conducted, and biomechanical changes in each spinal cord segment and nerve roots were analyzed. RESULTS: Throughout the scoliosis correction process, the middle spinal cord segment consistently exhibited a risk of injury under various conditions and displacements. The lower spinal cord segment showed no significant injury changes under traction + torsion conditions. In the early correction phase, the upper spinal cord segment demonstrated a risk of injury under all conditions, and the lower spinal cord segment presented a risk of injury under pushing conditions. Traction conditions posed a risk of nerve injury on both sides in the middle and lower segments. Under pushing conditions, there was a risk of nerve injury on both sides in all segments. Traction + torsion conditions implicated a risk of injury to the right nerves in the upper segment, both sides in the middle segment, and the left side in the lower segment. In the later correction stage, there was a risk of injury to the upper spinal cord segment under traction + torsion conditions, the left nerves in the middle segment under traction conditions, and the right nerves in the upper segment under pushing conditions. CONCLUSION: When the correction rate reaches 61-68%, particular attention should be given to the upper-mid spinal cord. Pushing conditions also warrant attention to the lower spinal cord and the nerve roots on both sides of the main thoracic curve. Traction conditions require attention to nerve roots bilaterally in the middle and lower segments, while traction combined with torsion conditions necessitate focus on the right-side nerve roots in the upper segment, both sides in the middle segment, and the left-side nerve roots in the lower segment.

Experimental guide wire placement for total shoulder arthroplasty in glenoid models: higher precision for patient-specific aiming guides compared to standard technique without learning curve.

BACKGROUND: Patient-specific aiming devices (PSAD) may improve precision and accuracy of glenoid component positioning in total shoulder arthroplasty, especially in degenerative glenoids. The aim of this study was to compare precision and accuracy of guide wire positioning into different glenoid models using a PSAD versus a standard guide. METHODS: Three experienced shoulder surgeons inserted 2.5 mm K-wires into polyurethane cast glenoid models of type Walch A, B and C (in total 180 models). Every surgeon placed guide wires into 10 glenoids of each type with a standard guide by DePuy Synthes in group (I) and with a PSAD in group (II). Deviation from planned version, inclination and entry point was measured, as well as investigation of a possible learning curve. RESULTS: Maximal deviation in version in B- and C-glenoids in (I) was 20.3° versus 4.8° in (II) (p < 0.001) and in inclination was 20.0° in (I) versus 3.7° in (II) (p < 0.001). For B-glenoid, more than 50% of the guide wires in (I) had a version deviation between 11.9° and 20.3° compared to ≤ 2.2° in (II) (p < 0.001). 50% of B- and C-glenoids in (I) showed a median inclination deviation of 4.6° (0.0°-20.0°; p < 0.001) versus 1.8° (0.0°-4.0°; p < 0.001) in (II). Deviation from the entry point was always less than 5.0 mm when using PSAD compared to a maximum of 7.7 mm with the standard guide and was most pronounced in type C (p < 0.001). CONCLUSION: PSAD enhance precision and accuracy of guide wire placement particularly for deformed B and C type glenoids compared to a standard guide in vitro. There was no learning curve for PSAD. However, findings of this study cannot be directly translated to the clinical reality and require further corroboration.

A Monte Carlo simulation-based decision support system for radiation oncologists in the treatment of glioblastoma multiforme.

In the present research, we have developed a model-based crisp logic function statistical classifier decision support system supplemented with treatment planning systems for radiation oncologists in the treatment of glioblastoma multiforme (GBM). This system is based on Monte Carlo radiation transport simulation and it recreates visualization of treatment environments on mathematical anthropomorphic brain (MAB) phantoms. Energy deposition within tumour tissue and normal tissues are graded by quality audit factors which ensure planned dose delivery to tumour site thereby minimising damages to healthy tissues. The proposed novel methodology predicts tumour growth response to radiation therapy from a patient-specific medicine quality audit perspective. Validation of the study was achieved by recreating thirty-eight patient-specific mathematical anthropomorphic brain phantoms of treatment environments by taking into consideration density variation and composition of brain tissues. Dose computations accomplished through water phantom, tissue-equivalent head phantoms are neither cost-effective, nor patient-specific customized and is often less accurate. The above-highlighted drawbacks can be overcome by using open-source Electron Gamma Shower (EGSnrc) software and clinical case reports for MAB phantom synthesis which would result in accurate dosimetry with due consideration to the time factors. Considerable dose deviations occur at the tumour site for environments with intraventricular glioblastoma, haematoma, abscess, trapped air and cranial flaps leading to quality factors with a lower logic value of 0. Logic value of 1 depicts higher dose deposition within healthy tissues and also leptomeninges for majority of the environments which results in radiation-induced laceration.

Assessment of stereotactic high-resolution detectors for stereotactic body radiotherapy: comparative analysis between myQA® SRS and Gafchromic EBT-XD films.

The study aimed to evaluate dosimetry systems used for stereotactic body radiotherapy (SBRT), specifically 2D array dosimetry and film dosimetry systems, for exploring their characteristics and clinical suitability. For this, high-resolution myQA SRS detectors and Gafchromic EBT-XD films were employed. Film analysis included net optical density (OD) values depending on energy, dose rate, scanner orientation, scanning side, and post-exposure growth. For myQA SRS, signal values were evaluated in terms of dose rate (400-1400 MU/min) and angular dependence (0-180° at 30° intervals) along with couch angles of 0°, 45°, and 90°. Pre-treatment verification included 32 SBRT patients for whom myQA SRS results were compared with those obtained with Gafchromic EBT-XD films. Analysis revealed less than 1% deviation in net OD for energy and dose rate dependence. Scanner orientation caused 2.5% net OD variation, with minimal differences between film front and back scan orientations (variance < 1.0%). A rapid OD rise occurred within six hours post-exposure, followed by gradual increase. The myQA SRS detector showed - 3.7% dose rate dependence (400 MU/min), while the angular dependence at 90° was - 26.7%. A correction factor effectively reduced these differences to < 1%. For myQA SRS, gamma passing rates were-93.6% (2%/1 mm), while those for EBT-XD films were-92.8%. Improved rates were observed with 3%/1 mm: for myQA SRS-97.9%, and for EBT-XD film-98.16%. In contrast, for 2%/2 mm with 10% threshold, for myQA SRS-97.7% and for EBT-XD film-98.97% were obtained. It is concluded that both myQA SRS detectors and EBT-XD films are suitable for SBRT pre-treatment verification, ensuring accuracy and reliability. However, myQA SRS detectors are preferred over EBT-XD film due to the fact that they offer real-time measurements and user-friendly features.

A patient-specific, interactive, multiuser, online mixed-reality neurosurgical training and planning system.

OBJECTIVE: Mixed-reality simulation is an emerging tool for creating anatomical models for preoperative planning. Its use in neurosurgical training (NT) has been limited because of the difficulty in real-time interactive teaching. This study describes the development of a patient-specific, interactive mixed-reality NT system. The authors took cases of intracranial tumor resection or neurovascular compression (NVC) as examples to verify the technical feasibility and efficacy of the mixed-reality NT system for residents' training and preoperative planning. METHODS: This study prospectively enrolled 40 patients who suffered from trigeminal neuralgia, hemifacial spasms, or intracranial tumors. The authors used a series of software programs to process the multimodal imaging data, followed by uploading the holographic models online. They used a HoloLens or a standard iOS device to download and display the holographic models for training. Ten neurosurgical residents with different levels of surgical experience were trained with this mixed-reality NT system. Change in surgical strategy was recorded, and a questionnaire survey was conducted to evaluate the efficacy of the mixed-reality NT system. RESULTS: The system allows the trainer and trainee to view the mixed-reality model with either a HoloLens or an iPad/iPhone simultaneously online at different locations. Interactive manipulation and instant updates were able to be achieved during training. A clinical efficacy validation test was conducted. The surgeons changed their exploration strategy in 48.3% of the NVC cases. For residents with limited experience in surgery, the exploration strategy for 75.0% of all patients with NVC was changed after the residents were trained with the mixed-reality NT system. Of the 60 responses for intracranial tumors, the trainee changed the surgical posture in 19 (31.7%) cases. The change of the location (p = 0.0338) and size (p = 0.0056) of craniotomy are significantly related to the experience of the neurosurgeons. CONCLUSIONS: The mixed-reality NT system is available for local or real-time remote neurosurgical resident training. It may effectively help neurosurgeons in patient-specific training and planning of surgery for cases of NVC and intracranial tumor. The authors expect the system to have a broader application in neurosurgery in the near future.