Enhancing adaptive proton therapy through CBCT images: Synthetic head and neck CT generation based on 3D vision transformers.

BACKGROUND: Proton therapy is a form of radiotherapy commonly used to treat various cancers. Due to its high conformality, minor variations in patient anatomy can lead to significant alterations in dose distribution, making adaptation crucial. While cone-beam computed tomography (CBCT) is a well-established technique for adaptive radiation therapy (ART), it cannot be directly used for adaptive proton therapy (APT) treatments because the stopping power ratio (SPR) cannot be estimated from CBCT images. PURPOSE: To address this limitation, Deep Learning methods have been suggested for converting pseudo-CT (pCT) images from CBCT images. In spite of convolutional neural networks (CNNs) have shown consistent improvement in pCT literature, there is still a need for further enhancements to make them suitable for clinical applications. METHODS: The authors introduce the 3D vision transformer (ViT) block, studying its performance at various stages of the proposed architectures. Additionally, they conduct a retrospective analysis of a dataset that includes 259 image pairs from 59 patients who underwent treatment for head and neck cancer. The dataset is partitioned into 80% for training, 10% for validation, and 10% for testing purposes. RESULTS: The SPR maps obtained from the pCT using the proposed method present an absolute relative error of less than 5% from those computed from the planning CT, thus improving the results of CBCT. CONCLUSIONS: We introduce an enhanced ViT3D architecture for pCT image generation from CBCT images, reducing SPR error within clinical margins for APT workflows. The new method minimizes bias compared to CT-based SPR estimation and dose calculation, signaling a promising direction for future research in this field. However, further research is needed to assess the robustness and generalizability across different medical imaging applications.

A case study of medical image software evolution and its impact in the medical imaging community.

Objective: We present the evolution of medical imaging software and its impact on the medical imaging community through the study of four open-source image analysis software platforms: 3D Slicer, FreeSurfer, FSL, and SPM. Materials and methods: We have studied the impact of these software tools over time, measured by the number of scientific citations. Additionally, we have also studied the source code evolution by measuring the lines of code and the tarball size of the stable releases and the changes in programming languages. Results and discussion: The rising number of related scientific publications confirms the popularity of these software tools in the research community, albeit some differences can be observed in the popularity of the tools. Moreover, we demonstrate that source code has evolved to modernize and optimize, at least partially thanks to the collaboration and code sharing with the user community. Furthermore, this evolution reveals an increased use of higher-level programming languages and meta-languages. Conclusions: The study of four open-source packages has revealed certain patterns in the evolution of medical imaging software and their impact on the medical image community. Further analyses and complementary metrics are suggested.

Material decomposition maps based calibration of dual energy CT scanners for proton therapy planning: a phantom study.

We introduce a new calibration method for dual energy CT (DECT) based on material decomposition (MD) maps, specifically iodine and water MD maps. The aim of this method is to provide the first DECT calibration based on MD maps. The experiments were carried out using a general electric (GE) revolution CT scanner with ultra-fast kV switching and used a density phantom by GAMMEX for calibration and evaluation. The calibration process involves several steps. First, we tested the ability of MD values to reproduce Hounsfield unit (HU) values of single energy CT (SECT) acquisitions and it was found that the errors were below 1%, validating their use for HU reproduction. Next, the different definitions of computedZvalues were compared and the robustness of the approach based on the materials' composition was confirmed. Finally, the calibration method was compared with a previous method by Bourqueet al, providing a similar level of accuracy and superior performance in terms of precision. Overall, this novel DECT calibration method offers improved accuracy and reliability in determining tissue-specific physical properties. The resulting maps can be valuable for proton therapy treatments, where precise dose calculations and accurate tissue differentiation are crucial for optimal treatment planning and delivery.

Democratization of deep learning for segmenting cartilage from MRIs of human knees: Application to data from the osteoarthritis initiative.

In this study, we aimed to democratize access to convolutional neural networks (CNN) for segmenting cartilage volumes, generating state-of-the-art results for specialized, real-world applications in hospitals and research. Segmentation of cross-sectional and/or longitudinal magnetic resonance (MR) images of articular cartilage facilitates both clinical management of joint damage/disease and fundamental research. Manual delineation of such images is a time-consuming task susceptible to high intra- and interoperator variability and prone to errors. Thus, enabling reliable and efficient analyses of MRIs of cartilage requires automated segmentation of cartilage volumes. Two main limitations arise in the development of hospital- or population-specific deep learning (DL) models for image segmentation: specialized knowledge and specialized hardware. We present a relatively easy and accessible implementation of a DL model to automatically segment MRIs of human knees with state-of-the-art accuracy. In representative examples, we trained CNN models in 6-8 h and obtained results quantitatively comparable to state-of-the-art for every anatomical structure. We established and evaluated our methods using two publicly available MRI data sets originating from the Osteoarthritis Initiative, Stryker Imorphics, and Zuse Institute Berlin (ZIB), as representative test cases. We use Google Colabfor editing and adapting the Python codes and selecting the runtime environment leveraging high-performance graphical processing units. We designed our solution for novice users to apply to any data set with relatively few adaptations requiring only basic programming skills. To facilitate the adoption of our methods, we provide a complete guideline for using our methods and software, as well as the software tools themselves. Clinical significance: We establish and detail methods that clinical personal can apply to create their own DL models without specialized knowledge of DL nor specialized hardware/infrastructure and obtain results comparable with the state-of-the-art to facilitate both clinical management of joint damage/disease and fundamental research.

Clear Cell Proliferations of the Skin: A Histopathologic Review.

ABSTRACT: Cutaneous clear cell proliferations encompass a heterogenous group of several primary cutaneous neoplasms and metastatic tumors with different histogenesis. Many of these clear cell proliferations may seem strikingly similar under the microscope resulting in challenging diagnosis. In many of these clear cell lesions, the reason for the clear or pale appearance of proliferating cells is unknown, whereas in other ones, this clear cell appearance is due to intracytoplasmic accumulation of glycogen, mucin, or lipid. Artifacts of tissue processing and degenerative phenomenon may also be responsible for the clear cell appearance of proliferating cells. Awareness of the histopathologic findings as well as histochemical and immunohistochemical techniques are crucial to the accurate diagnosis. This review details the histopathologic features of clear cell cutaneous proliferations, classifying them according their type of differentiation and paying special attention to the histopathologic differential diagnosis among them.

Ustekinumab Drug Survival in Patients with Psoriasis: A retrospective Study of Real Clinical Practice.

Background and objectives: The efficacy and safety of ustekinumab have been proved in clinical trials. In daily clinical practice, knowing the factors that determine survival differences of biological drugs allows psoriasis treatment to be optimized as a function of patient characteristics. The main objectives of this work are to understand ustekinumab drug survival in patients diagnosed with plaque psoriasis in the Hospital Universitario Central de Asturias (HUCA Dermatology Department, and to identify the predictors of drug discontinuation. Materials and Methods: A retrospective hospital-based study, including data from 148 patients who were receiving ustekinumab (Stelara®) between 1 February 2009 and 30 November 2019, were collected. Survival curves were approximated through the Kaplan-Meier estimator and compared using the log-rank test. Proportional hazard Cox regression models were used for multivariate analyses while both unadjusted and adjusted hazard ratios (HR) were used for summarizing the studied differences. Results: The average duration of the treatment before discontinuation was 47.57 months (SD 32.63 months; median 41 months). The retention rates were 82% (2 years), 66% (5 years), and 58% (8 years). Median survival was 80 months (95% confidence interval. CI 36.9 to 123.01 months). The survival study revealed statistically significant differences between patients with arthritis (log-rank test, p < 0.001) and those who had previously received biological treatment (log-rank test, p = 0.026). The five-year prevalence in patients still under treatment was 80% (those without arthritis) and 54% (arthritis patients). In the multivariate analysis, only the patients with arthritis had a lower rate of drug survival. No statistically significant differences were observed for any of the other comorbidities studied. The first and second most frequent causes of discontinuation were secondary failure and arthritis inefficacy, respectively. Conclusion: Ustekinumab is a biological drug conferring high survival in plaque psoriasis patients. Ustekinumab survival is lower in patients with arthritis.

Interpretation of motion analysis of laparoscopic instruments based on principal component analysis in box trainer settings.

BACKGROUND: Motion analysis parameters (MAPs) have been extensively validated for assessment of minimally invasive surgical skills. However, there are discrepancies on how specific MAPs, tasks, and skills match with each other, reflecting that motion analysis cannot be generalized independently of the learning outcomes of a task. Additionally, there is a lack of knowledge on the meaning of motion analysis in terms of surgical skills, making difficult the provision of meaningful, didactic feedback. In this study, new higher significance MAPs (HSMAPs) are proposed, validated, and discussed for the assessment of technical skills in box trainers, based on principal component analysis (PCA). METHODS: Motion analysis data were collected from 25 volunteers performing three box trainer tasks (peg grasping/PG, pattern cutting/PC, knot suturing/KS) using the EVA tracking system. PCA was applied on 10 MAPs for each task and hand. Principal components were trimmed to those accounting for an explained variance > 80% to define the HSMAPs. Individual contributions of MAPs to HSMAPs were obtained by loading analysis and varimax rotation. Construct validity of the new HSMAPs was carried out at two levels of experience based on number of surgeries. RESULTS: Three new HSMAPs per hand were defined for PG and PC tasks, and two per hand for KS task. PG presented validity for HSMAPs related to insecurity and economy of space. PC showed validity for HSMAPs related to cutting efficacy, peripheral unawareness, and confidence. Finally, KS presented validity for HSMAPs related with economy of space and knotting security. CONCLUSIONS: PCA-defined HSMAPs can be used for technical skills' assessment. Construct validation and expert knowledge can be combined to infer how competences are acquired in box trainer tasks. These findings can be exploited to provide residents with meaningful feedback on performance. Future works will compare the new HSMAPs with valid scoring systems such as GOALS.

Salmosan, a ß-Galactomannan-Rich Product, Protects Epithelial Barrier Function in Caco-2 Cells Infected by Salmonella enterica Serovar Enteritidis.

BACKGROUND: One promising strategy for reducing human salmonellosis induced by Salmonella Enteritidis is to supplement animal diets with natural feed additives such as mannan oligosaccharides (MOSs). OBJECTIVE: We sought to investigate the potential role of Salmosan (S-ßGM), an MOS product extremely rich in ß-galactomannan, in preventing epithelial barrier function disruption induced by S. Enteritidis colonization in an in vitro model of intestinal Caco-2 cells in culture. METHODS: Differentiated Caco-2 cells were incubated for 3 h with S. Enteritidis at a multiplicity of infection of 10 in the absence or presence of 500 µg S-ßGM/mL. Paracellular permeability (PP) was assessed by transepithelial electrical resistance (TER), d-mannitol, and fluorescein isothiocyanate-dextran (FD-4) flux. Tight junction proteins and cytoskeletal actin were also localized by confocal microscopy. Reactive oxygen species (ROS) and lipid peroxidation products were evaluated. Scanning and transmission electron microscopy were used to visualize S. Enteritidis adhesion to, and invasion of, the Caco-2 cell cultures. RESULTS: Compared with controls, TER was significantly reduced by 30%, and d-mannitol and FD-4 flux were significantly increased by 374% and 54% in S. Enteritidis-infected cultures, respectively. The presence of S-ßGM in infected cultures induced total recoveries of TER and FD-4 flux to values that did not differ from the control and a partial recovery of d-mannitol flux. These effects were confirmed by immunolocalization of actin, zonula occludens protein 1, and occludin. Similar results were obtained for Salmonella Dublin. The protection of S-ßGM on PP in infected cultures may be associated with a total recovery of ROS production to values that did not differ from the control. Moreover, S-ßGM has the capacity to agglutinate bacteria, leading to a significant reduction of 32% in intracellular S Enteritidis. CONCLUSION: The results demonstrate that S-ßGM contributes to protecting epithelial barrier function in a Caco-2 cell model disrupted by S. Enteritidis.

A method for incorporating three-dimensional residual stretches/stresses into patient-specific finite element simulations of arteries.

The existence of residual stresses in human arteries has long been shown experimentally. Researchers have also demonstrated that residual stresses have a significant effect on the distribution of physiological stresses within arterial tissues, and hence on their development, e.g., stress-modulated remodeling. Through progress in medical imaging, image analysis and finite element (FE) meshing tools it is now possible to construct in vivo patient-specific geometries and thus to study specific, clinically relevant problems in arterial mechanics via FE simulations. Classical continuum mechanics and FE methods assume that constitutive models and the corresponding simulations start from unloaded, stress-free reference configurations while the boundary-value problem of interest represents a loaded geometry and includes residual stresses. We present a pragmatic methodology to simultaneously account for both (i) the three-dimensional (3-D) residual stress distributions in the arterial tissue layers, and (ii) the equilibrium of the in vivo patient-specific geometry with the known boundary conditions. We base our methodology on analytically determined residual stress distributions (Holzapfel and Ogden, 2010, J. R. Soc. Interface 7, 787-799) and calibrate it using data on residual deformations (Holzapfel et al., 2007, Ann. Biomed. Eng. 35, 530-545). We demonstrate our methodology on three patient-specific FE simulations calibrated using experimental data. All data employed here are generated from human tissues - both the aorta and thrombus, and their respective layers - including the geometries determined from magnetic resonance images, and material properties and 3-D residual stretches determined from mechanical experiments. We study the effect of 3-D residual stresses on the distribution of physiological stresses in the aortic layers (intima, media, adventitia) and the layers of the intraluminal thrombus (luminal, medial, abluminal) by comparing three types of FE simulations: (i) conventional calculations; (ii) calculations accounting only for prestresses; (iii) calculations including both 3-D residual stresses and prestresses. Our results show that including residual stresses in patient-specific simulations of arterial tissues significantly impacts both the global (organ-level) deformations and the stress distributions within the arterial tissue (and its layers). Our method produces circumferential Cauchy stress distributions that are more uniform through the tissue thickness (i.e., smaller stress gradients in the local radial directions) compared to both the conventional and prestressing calculations. Such methods, combined with appropriate experimental data, aim at increasing the accuracy of classical FE analyses for patient-specific studies in computational biomechanics and may lead to increased clinical application of simulation tools.

Effect of a high dose of CLA in finishing pig diets on fat deposition and fatty acid composition in intramuscular fat and other fat depots.

Sixteen gilts were fed a control (4% of sunflower oil) or an experimental diet (4% conjugated linoleic acid (CLA) oil). CLA had no effect on intramuscular fat (IMF) content neither in longissimus thoracis (LT) nor in semimembranosus (SM) muscles but increased liver weight, reduced perirenal fat and tended to reduce backfat between the last 3th-4th lumbar vertebrae. Despite the fact that 9c,11t and 10t,12c CLA isomers were included in the same proportion in the diet, the 9c,11t and 9c,11c were the isomers more deposited in all tissues. Addition of CLA in the diet affected fatty acid composition in a tissue specific manner, increasing percentages of SFA in all tissues, reducing percentages of MUFA in LT and LT subcutaneous fat, and of PUFA in LT subcutaneous fat, liver and SM. The FA modification by dietary CLA in LT IMF was reflected in the different lipid fractions, SFA and MUFA mainly in the neutral lipid fraction, and PUFA in the polar fraction.