Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images.

The analysis of the psoas muscle in morphological and functional imaging has proved to be an accurate approach to assess sarcopenia, i.e. a systemic loss of skeletal muscle mass and function that may be correlated to multifactorial etiological aspects. The inclusion of sarcopenia assessment into a radiological workflow would need the implementation of computational pipelines for image processing that guarantee segmentation reliability and a significant degree of automation. The present study utilizes three-dimensional numerical schemes for psoas segmentation in low-dose X-ray computed tomography images. Specifically, here we focused on the level set methodology and compared the performances of two standard approaches, a classical evolution model and a three-dimension geodesic model, with the performances of an original first-order modification of this latter one. The results of this analysis show that these gradient-based schemes guarantee reliability with respect to manual segmentation and that the first-order scheme requires a computational burden that is significantly smaller than the one needed by the second-order approach.

Gene's expression underpinning the divergent predictive value of [18F]F-fluorodeoxyglucose and prostate-specific membrane antigen positron emission tomography in primary prostate cancer: a bioinformatic and experimental study.

BACKGROUND: Positron Emission Tomography (PET) imaging with Prostate-Specific Membrane Antigen (PSMA) and Fluorodeoxyglucose (FDG) represent promising biomarkers for risk-stratification of Prostate Cancer (PCa). We verified whether the expression of genes encoding for PSMA and enzymes regulating FDG cellular uptake are independent and additive prognosticators in PCa. METHODS: mRNA expression of genes involved in glucose metabolism and PSMA regulation obtained from primary PCa specimens were retrieved from open-source databases and analyzed using an integrative bioinformatics approach. Machine Learning (ML) techniques were used to create predictive Progression-Free Survival (PFS) models. Cellular models of primary PCa with different aggressiveness were used to compare [18F]F-PSMA-1007 and [18F]F-FDG uptake kinetics in vitro. Confocal microscopy, immunofluorescence staining, and quantification analyses were performed to assess the intracellular and cellular membrane PSMA expression. RESULTS: ML analyses identified a predictive functional network involving four glucose metabolism-related genes: ALDOB, CTH, PARP2, and SLC2A4. By contrast, FOLH1 expression (encoding for PSMA) did not provide any additive predictive value to the model. At a cellular level, the increase in proliferation rate and migratory potential by primary PCa cells was associated with enhanced FDG uptake and decreased PSMA retention (paralleled by the preferential intracellular localization). CONCLUSIONS: The overexpression of a functional network involving four glucose metabolism-related genes identifies a higher risk of disease progression since the earliest phases of PCa, in agreement with the acknowledged prognostic value of FDG PET imaging. By contrast, the prognostic value of PSMA PET imaging is independent of the expression of its encoding gene FOLH1. Instead, it is influenced by the protein docking to the cell membrane, regulating its accessibility to tracer binding.

Pre-pectoral Breast Reconstruction: Surgical and Patient-Reported Outcomes of Two-Stages vs Single-Stage Implant-Based Breast Reconstruction.

BACKGROUND: Two-stages pre-pectoral breast reconstruction may confer advantages over direct to implant (DTI) and subpectoral reconstruction in selected patients who have no indication for autologous reconstruction. The primary endpoint of the study was to evaluate and compare the incidence of capsular contracture in the pre-pectoral two-stages technique versus the direct to implant technique. Complications related to the two surgical techniques and patient satisfaction were also evaluated. METHODS: A retrospective review of 45 two stages and 45 Direct-to-implant, DTI patients was completed. Acellular dermal matrix was used in all patients. An evaluation of anthropometric and clinical parameters, surgical procedures and complications was conducted. Minimum follow-up was 12 months after placement of the definitive implant. RESULTS: There was no statistically significant difference in the rate of capsular contracture in the two groups. Rippling occurred more in DTI reconstruction. In the two-stages reconstruction, lipofilling was applied more often and there was a higher incidence of seroma. Patient satisfaction extrapolated from the Breast Q questionnaire was better for patients submitted to two-stage implant-based breast reconstruction. CONCLUSION: Dual-stage pre-pectoral reconstruction with acellular dermal matrix appears to be a good reconstructive solution in patients with relative contraindications for one-stage heterologous reconstruction with definitive prosthesis and no desire for autologous reconstruction.

Whole-Exome Sequencing and cfDNA Analysis Uncover Genetic Determinants of Melanoma Therapy Response in a Real-World Setting.

Although several studies have explored the molecular landscape of metastatic melanoma, the genetic determinants of therapy resistance are still largely unknown. Here, we aimed to determine the contribution of whole-exome sequencing and circulating free DNA (cfDNA) analysis in predicting response to therapy in a consecutive real-world cohort of 36 patients, undergoing fresh tissue biopsy and followed during treatment. Although the underpowered sample size limited statistical analysis, samples from non-responders had higher copy number variations and mutations in melanoma driver genes compared to responders in the BRAF V600+ subset. In the BRAF V600- subset, Tumor Mutational Burden (TMB) was twice that in responders vs. non-responders. Genomic layout revealed commonly known and novel potential intrinsic/acquired resistance driver gene variants. Among these, RAC1, FBXW7, GNAQ mutations, and BRAF/PTEN amplification/deletion were present in 42% and 67% of patients, respectively. Both Loss of Heterozygosity (LOH) load and tumor ploidy were inversely associated with TMB. In immunotherapy-treated patients, samples from responders showed higher TMB and lower LOH and were more frequently diploid compared to non-responders. Secondary germline testing and cfDNA analysis proved their efficacy in finding germline predisposing variants carriers (8.3%) and following dynamic changes during treatment as a surrogate of tissue biopsy, respectively.

Transfreq: A Python package for computing the theta-to-alpha transition frequency from resting state electroencephalographic data.

A classic approach to estimate individual theta-to-alpha transition frequency (TF) requires two electroencephalographic (EEG) recordings, one acquired in a resting state condition and one showing alpha desynchronisation due, for example, to task execution. This translates into long recording sessions that may be cumbersome in studies involving patients. Moreover, an incomplete desynchronisation of the alpha rhythm may compromise TF estimates. Here we present transfreq, a publicly available Python library that allows TF computation from resting state data by clustering the spectral profiles associated to the EEG channels based on their content in alpha and theta bands. A detailed overview of transfreq core algorithm and software architecture is provided. Its effectiveness and robustness across different experimental setups are demonstrated on a publicly available EEG data set and on in-house recordings, including scenarios where the classic approach fails to estimate TF. We conclude with a proof of concept of the predictive power of transfreq TF as a clinical marker. Specifically, we present a scenario where transfreq TF shows a stronger correlation with the mini mental state examination score than other widely used EEG features, including individual alpha peak and median/mean frequency. The documentation of transfreq and the codes for reproducing the analysis of the article with the open-source data set are available online at https://elisabettavallarino.github.io/transfreq/. Motivated by the results showed in this article, we believe our method will provide a robust tool for discovering markers of neurodegenerative diseases.

Longitudinal analysis of atherosclerotic plaques evolution: an 18F-NaF PET/CT study.

PURPOSE: 18F-NaF-PET/CT can detect mineral metabolism within atherosclerotic plaques. To ascertain whether their 18F-NaF uptake purports progression, this index was compared with subsequent morphologic evolution. METHODS: 71 patients underwent two consecutive 18F-NaF-PET/CTs (PET1/PET2). In PET1, non-calcified 18F-NaF hot spots were identified in the abdominal aorta. Their mean/max HU was compared with those of a non-calcified control region (CR) and with corresponding areas in PET2. A target-to-background ratio (TBR), mean density (HU), and calcium score (CS) were calculated on calcified atherosclerotic plaques in PET1 and compared with those in PET2. A VOI including the entire abdominal aorta was drawn; mean TBR and total CS were calculated on PET1 and compared with those PET2. RESULTS: Hot spots in PET1 (N = 179) had a greater HU than CR (48 ± 8 vs 37 ± 9, P < .01). Mean hot spots HU increased to 59 ± 12 in PET2 (P < .001). New calcifications appeared at the hot spots site in 73 cases (41%). Baseline atherosclerotic plaque's (N = 375) TBR was proportional to percent HU and CS increase (P < .01 for both). Aortic CS increased (P < .001); the whole-aorta TBR in PET1 correlated with the CS increase between the baseline and the second PET/CT (R = .63, P < .01). CONCLUSIONS: 18F-NaF-PET/CT depicts the early stages of plaques development and tracks their evolution over time.

First Hard X-Ray Imaging Results by Solar Orbiter STIX.

The Spectrometer/Telescope for Imaging X-rays (STIX) is one of six remote sensing instruments on-board Solar Orbiter. The telescope applies an indirect imaging technique that uses the measurement of 30 visibilities, i.e., angular Fourier components of the solar flare X-ray source. Hence, the imaging problem for STIX consists of the Fourier inversion of the data measured by the instrument. In this work, we show that the visibility amplitude and phase calibration of 24 out of 30 STIX sub-collimators has reached a satisfactory level for scientific data exploitation and that a set of imaging methods is able to provide the first hard X-ray images of solar flares from Solar Orbiter. Four visibility-based image reconstruction methods and one count-based are applied to calibrated STIX observations of six events with GOES class between C4 and M4 that occurred in May 2021. The resulting reconstructions are compared to those provided by an optimization algorithm used for fitting the amplitudes of STIX visibilities. We show that the five imaging methods produce results morphologically consistent with the ones provided by the Atmospheric Imaging Assembly on board the Solar Dynamic Observatory (SDO/AIA) in UV wavelengths. The χ 2 values and the parameters of the reconstructed sources are comparable between methods, thus confirming their robustness.

A Simple Way to Apply Moisture Chamber Eyeglasses During Oculoplastic Surgery.

Proper eyelid closure and a normal blink reflex are essential to maintain a stable tear film and a healthy corneal surface. We present a simple technique to apply moisture chamber eyeglasses after oculoplastic surgery. The Opti-Gard® protective eyewear is faster, easily applicable and well performing. It can be used with different face shape, and it does not require any additional trimming or modification. This technical note explains a very simple, economical and less time-consuming method to prevent a postoperative dry keratoconjunctivitis. It may be applied to all procedures within the field of ophthalmic surgery, including oculoplastic surgery.Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these evidence-based medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Gain and loss of function mutations in biological chemical reaction networks: a mathematical model with application to colorectal cancer cells.

This paper studies a system of Ordinary Differential Equations modeling a chemical reaction network and derives from it a simulation tool mimicking Loss of Function and Gain of Function mutations found in cancer cells. More specifically, from a theoretical perspective, our approach focuses on the determination of moiety conservation laws for the system and their relation with the corresponding stoichiometric surfaces. Then we show that Loss of Function mutations can be implemented in the model via modification of the initial conditions in the system, while Gain of Function mutations can be implemented by eliminating specific reactions. Finally, the model is utilized to examine in detail the G1-S phase of a colorectal cancer cell.

Quantitative Imaging and Radiomics in Multiple Myeloma: A Potential Opportunity?

Multiple Myeloma (MM) is the second most common type of hematological disease and, although it is rare among patients under 40 years of age, its incidence rises in elderly subjects. MM manifestations are usually identified through hyperCalcemia, Renal failure, Anaemia, and lytic Bone lesions (CRAB). In particular, the extent of the bone disease is negatively related to a decreased quality of life in patients and, in general, bone disease in MM increases both morbidity and mortality. The detection of lytic bone lesions on imaging, especially computerized tomography (CT) and Magnetic Resonance Imaging (MRI), is becoming crucial from the clinical viewpoint to separate asymptomatic from symptomatic MM patients and the detection of focal lytic lesions in these imaging data is becoming relevant even when no clinical symptoms are present. Therefore, radiology is pivotal in the staging and accurate management of patients with MM even in early phases of the disease. In this review, we describe the opportunities offered by quantitative imaging and radiomics in multiple myeloma. At the present time there is still high variability in the choice between various imaging methods to study MM patients and high variability in image interpretation with suboptimal agreement among readers even in tertiary centers. Therefore, the potential of medical imaging for patients affected by MM is still to be completely unveiled. In the coming years, new insights to study MM with medical imaging will derive from artificial intelligence (AI) and radiomics usage in different bone lesions and from the wide implementations of quantitative methods to report CT and MRI. Eventually, medical imaging data can be integrated with the patient's outcomes with the purpose of finding radiological biomarkers for predicting the prognostic flow and therapeutic response of the disease.

Interplay between spinal cord and cerebral cortex metabolism in amyotrophic lateral sclerosis.

We recently reported the potential of Hough transform in delineating spinal cord metabolism by 18F-fluorodeoxyglucose PET/CT scanning in amyotrophic lateral sclerosis. The present study aimed to verify the relationship between spinal cord and brain metabolism in 44 prospectively recruited patients affected by amyotrophic lateral sclerosis submitted to 18F-fluorodeoxyglucose brain and whole-body PET/CT. Patients were studied to highlight the presence of brain hypo- or hypermetabolism with respect to healthy controls, and multiple regression analysis was performed to evaluate the correlation between spinal cord and brain metabolism. Our results confirmed higher 18F-fluorodeoxyglucose uptake in both cervical and dorsal spinal cord in patients with amyotrophic lateral sclerosis with respect to controls. This finding was paralleled by the opposite pattern in the brain cortex that showed a generalized reduction in tracer uptake. This hypometabolism was particularly evident in wide regions of the frontal-dorsolateral cortex while it did not involve the midbrain. Bulbar and spinal disease onset was associated with similar degree of metabolic activation in the spinal cord. However, among spinal onset patients, upper limb presentation was associated with a more pronounced metabolic activation of cervical segment. Obtained data suggest a differential neuro-pathological state or temporal sequence in disease progression.

A Comparative Study of the Robustness of Frequency-Domain Connectivity Measures to Finite Data Length.

In this work we use numerical simulation to investigate how the temporal length of the data affects the reliability of the estimates of brain connectivity from EEG time-series. We assume that the neural sources follow a stable MultiVariate AutoRegressive model, and consider three connectivity metrics: imaginary part of coherency (IC), generalized partial directed coherence (gPDC) and frequency-domain granger causality (fGC). In order to assess the statistical significance of the estimated values, we use the surrogate data test by generating phase-randomized and autoregressive surrogate data. We first consider the ideal case where we know the source time courses exactly. Here we show how, expectedly, even exact knowledge of the source time courses is not sufficient to provide reliable estimates of the connectivity when the number of samples gets small; however, while gPDC and fGC tend to provide a larger number of false positives, the IC becomes less sensitive to the presence of connectivity. Then we proceed with more realistic simulations, where the source time courses are estimated using eLORETA, and the EEG signal is affected by biological noise of increasing intensity. Using the ideal case as a reference, we show that the impact of biological noise on IC estimates is qualitatively different from the impact on gPDC and fGC.

Allogeneic cell transplant expands bone marrow distribution by colonizing previously abandoned areas: an FDG PET/CT analysis.

Mechanisms of hematopoietic reconstitution after bone marrow (BM) transplantation remain largely unknown. We applied a computational quantification software application to hybrid 18F-fluorodeoxyglucose positron emission tomography (PET)/computed tomography (CT) images to assess activity and distribution of the hematopoietic system throughout the whole skeleton of recently transplanted patients. Thirty-four patients underwent PET/CT 30 days after either adult stem cell transplantation (allogeneic cell transplantation [ACT]; n = 18) or cord blood transplantation (CBT; n = 16). Our software automatically recognized compact bone volume and trabecular bone volume (IBV) in CT slices. Within IBV, coregistered PET data were extracted to identify the active BM (ABM) from the inactive tissue. Patients were compared with 34 matched controls chosen among a published normalcy database. Whole body ABM increased in ACT and CBT when compared with controls (12.4 ± 3 and 12.8 ± 6.8 vs 8.1 ± 2.6 mL/kg of ideal body weight [IBW], P < .001). In long bones, ABM increased three- and sixfold in CBT and ACT, respectively, compared with controls (0.9 ± 0.9 and 1.7 ± 2.5 vs 0.3 ± 0.3 mL/kg IBW, P < .01). These data document an unexpected distribution of transplanted BM into previously abandoned BM sites.

Expectation maximization and the retrieval of the atmospheric extinction coefficients by inversion of Raman lidar data.

We consider the problem of retrieving the aerosol extinction coefficient from Raman lidar measurements. This is an ill-posed inverse problem that needs regularization, and we propose to use the Expectation-Maximization (EM) algorithm to provide stable solutions. Indeed, EM is an iterative algorithm that imposes a positivity constraint on the solution, and provides regularization if iterations are stopped early enough. We describe the algorithm and propose a stopping criterion inspired by a statistical principle. We then discuss its properties concerning the spatial resolution. Finally, we validate the proposed approach by using both synthetic data and experimental measurements; we compare the reconstructions obtained by EM with those obtained by the Tikhonov method, by the Levenberg-Marquardt method, as well as those obtained by combining data smoothing and numerical derivation.

A PET/CT approach to spinal cord metabolism in amyotrophic lateral sclerosis.

PURPOSE: In amyotrophic lateral sclerosis, functional alterations within the brain have been intensively assessed, while progression of lower motor neuron damage has scarcely been defined. The aim of the present study was to develop a computational method to systematically evaluate spinal cord metabolism as a tool to monitor disease mechanisms. METHODS: A new computational three-dimensional method to extract the spinal cord from (18)F-FDG PET/CT images was evaluated in 30 patients with spinal onset amyotrophic lateral sclerosis and 30 controls. The algorithm identified the skeleton on the CT images by using an extension of the Hough transform and then extracted the spinal canal and the spinal cord. In these regions, (18)F-FDG standardized uptake values were measured to estimate the metabolic activity of the spinal canal and cord. Measurements were performed in the cervical and dorsal spine and normalized to the corresponding value in the liver. RESULTS: Uptake of (18)F-FDG in the spinal cord was significantly higher in patients than in controls (p < 0.05). By contrast, no significant differences were observed in spinal cord and spinal canal volumes between the two groups. (18)F-FDG uptake was completely independent of age, gender, degree of functional impairment, disease duration and riluzole treatment. Kaplan-Meier analysis showed a higher mortality rate in patients with standardized uptake values above the fifth decile at the 3-year follow-up evaluation (log-rank test, p < 0.01). The independence of this value was confirmed by multivariate Cox analysis. CONCLUSION: Our computational three-dimensional method enabled the evaluation of spinal cord metabolism and volume and might represent a potential new window onto the pathophysiology of amyotrophic lateral sclerosis.

Adult advanced chronic lymphocytic leukemia: computational analysis of whole-body CT documents a bone structure alteration.

PURPOSE: To assess the presence of alteration of bone structure and bone marrow metabolism in adult patients who were suspected of having advanced chronic lymphocytic leukemia (ACLL) by using a computational prognostic model that was based on computational analysis of positron emission tomography (PET)/computed tomography (CT) images. MATERIALS AND METHODS: In this retrospective study, all patients signed written informed consent as a requisite to undergo PET/CT examination. However, due to its observational nature, approval from the ethical committee was not deemed necessary. Twenty-two previously untreated chronic lymphocytic leukemia patients underwent PET/CT for disease progression. PET/CT images were analyzed by using dedicated software, capable of recognizing an external 2-pixel bone ring whose Hounsfield coefficient served as cutoff to recognize trabecular and compact bone. PET/CT data from 22 age- and sex-matched control subjects were used as comparison. All data are reported as means ± standard deviations. The Student t test, log-rank, or Cox proportional hazards model were used as appropriate, considering a difference with a P value of less than .05 as significant. RESULTS: Trabecular bone was expanded in ACLL patients and occupied a larger fraction of the skeleton with respect to control subjects (mean, 39% ± 5 [standard deviation] vs 31% ± 7; ie, 32 of 81 mL/kg of ideal body weight vs 27 of 86 mL/kg of ideal body weight, respectively; P < .001). After stratification according to median value, patients with a ratio of trabecular to skeletal bone volume of more than 37.3% showed an actuarial 2-year survival of 18%, compared with 82% for those with a ratio of less than 37.3% (P < .001), independent from age, sex, biological markers, and disease duration. CONCLUSION: These data suggest that computational assessment of skeletal alterations might represent a new window for prediction of the clinical course of the disease.

PCA-based synthetic sensitivity coefficients for chemical reaction network in cancer.

Chemical reaction networks are powerful tools for modeling cell signaling and its disruptions in diseases like cancer. Realistic chemical reaction networks involve hundreds of proteins and reactions, resulting in a model depending on a consistently large number of kinetic parameters. Since finely calibrating all the parameters would require an unrealistic amount of data, proper sensitivity analysis is required to identify a subset of parameters for which fine tuning is needed and thus provide a fundamental tool for the qualitative analysis of the network. We present a multidisciplinary approach for computing a set of synthetic sensitivity indices. These indices rank the kinetic parameters, based on the impact that errors in their values would have on the protein concentration profile at equilibrium. Our tests on a chemical reaction network devised for colorectal cells demonstrate the effectiveness of the considered sensitivity indices in different scenarios including in-silico drug dosage and novel therapeutic target discovery. The Matlab code for computing the synthetic sensitivity indices and the data concerning the network for colorectal cells are available at https://github.com/theMIDAgroup/CRN_sensitivity.

Artificial intelligence and prescription of antibiotic therapy: present and future.

INTRODUCTION: In the past few years, the use of artificial intelligence in healthcare has grown exponentially. Prescription of antibiotics is not exempt from its rapid diffusion, and various machine learning (ML) techniques, from logistic regression to deep neural networks and large language models, have been explored in the literature to support decisions regarding antibiotic prescription. AREAS COVERED: In this narrative review, we discuss promises and challenges of the application of ML-based clinical decision support systems (ML-CDSSs) for antibiotic prescription. A search was conducted in PubMed up to April 2024. EXPERT OPINION: Prescribing antibiotics is a complex process involving various dynamic phases. In each of these phases, the support of ML-CDSSs has shown the potential, and also the actual ability in some studies, to favorably impacting relevant clinical outcomes. Nonetheless, before widely exploiting this massive potential, there are still crucial challenges ahead that are being intensively investigated, pertaining to the transparency of training data, the definition of the sufficient degree of prediction explanations when predictions are obtained through black box models, and the legal and ethical framework for decision responsibility whenever an antibiotic prescription is supported by ML-CDSSs.

Distinct features of immune activation and exhaustion markers in people with perinatally-acquired HIV.

OBJECTIVE: The aim of this study was to characterize T cell activation, exhaustion, maturation and Treg frequencies in individuals who acquire perinatal HIV (PHIV), in individuals who acquired HIV as adult (AHIV), and in healthy controls (HC). DESIGN: This cross-sectional study included people with HIV ≥ 14 and <40 years, HIV-RNA < 50 copies/mL on antiretroviral therapy for at least 6 months, and HC. METHODS: We assessed the expression of PD-1, TIM-3, EOMES, CD38+ DR+, maturation status by CD4+ and CD8+T cells and the frequency of CD4+ and CD8+ Treg cells. Principal component analysis (PCA) and k-means cluster analysis investigated which combination of immunological parameters better associated with each group. RESULTS: 26 PHIV and 18 AHIV with median ages of 26 (8.0) and 28 (6.8) years were consecutively enrolled. PHIV showed significant higher frequency of naïve and lower frequency of terminal effector memory CD4+ and CD8+ T cells than AHIV. AHIV exhibited higher expression of exhaustion and activation markers. The statistical analysis returned two clusters with 94% of specificity and 88% of sensitivity identifying PHIV vs. AHIV. The 9 HC had a lower expression of exhaustion markers on both CD4+ and CD8+T lymphocytes than PHIV and AHIV. CONCLUSIONS: These data may exclude major alterations of lymphopoiesis in PHIV, with even lower state of immune-activation and exhaustion compared with AHIV. This suggests that recent lack of virological control, may affect immune activation and exhaustion of CD4+ and CD8+ T cells.