Citations

SignificanceCurrent clinical care following ischemic stroke provides intermittent assessments, potentially missing early detection of neurological deterioration. Optical imaging offers the potential for a continuous, portable alternative to the current combination of physical exams and radiological imaging. However, optical imaging technology has lacked the crucial combination of portability, resolution, and coverage required to assess spatially distributed brain function.AimHere, we present a proof-of-principle study that applies recent advancements in portable high-density diffuse optical tomography (HD-DOT) instrumentation and a functional connectivity analysis strategy to assess spatially distributed brain connectivity. Point-of-care brain health assessments with these tools may inform clinical care and our understanding of brain injury throughout acute stages of stroke recovery.ApproachWe measured spatially distributed cortical oxygenation with HD-DOT within the intensive care unit in N=13 patients with ischemic stroke within the first 72-h since last known normal. To assess brain function integrity, we developed a Similarity metric of functional connectivity (FC) through comparisons to FC in a healthy young adult population. To assess the sensitivity of this FC Similarity metric to disruptions caused by stroke, we compared these data with FC Similarity assessed in an older healthy cohort. We administered the NIH Stroke Scale to stroke patients to evaluate the potential of the FC Similarity metric to inform the severity of functional disruptions.ResultsThe FC Similarity metric applied to HD-DOT data in both acute stroke patients and healthy older controls exhibited a significant sensitivity to the presence of a stroke (Cohen’s d=1.5, p=1.2×10−3) and a significant relationship with the degree of neurological disruption as measured by the NIH Stroke Scale (R2=0.69, p=4.7×10−4).ConclusionsWe present a proof-of-principle for HD-DOT and the FC Similarity metric for assessing brain function during the acute stage of ischemic stroke recovery at the point-of-care.

Abstract Background The intra‐fraction motion of tumors during radiation therapy can be monitored using imaging systems based on X‐ray imaging (e.g., kV/MV radiography or CBCT) or magnetic resonance imaging (MRI). However, these techniques have limitations, including additional ionizing radiation dose and the need for complex, expensive equipment. Hence, a non‐invasive, lower‐cost motion‐tracking approach that does not add radiation would be beneficial for routine clinical applications. Purpose To study the feasibility of tracking the dynamic motion of a small gold marker in water by using Cherenkov photons produced by MV photon beams, through Monte Carlo simulations and experiments. Methods The GAMOS Monte Carlo code, which includes an optical simulation module, was used to calculate the deposited dose and Cherenkov‐light yield in a water phantom. Phase‐space files for 6, 10, 15, and 10 MV flattening filter‐free (FFF) beams served as photon sources. The simulation setup consisted of a 20 × 20 × 20 cm 3 water phantom with an 8 × 12 × 0.25 mm 3 gold planar implant at its center. Percent depth dose (PDD) and Cherenkov‐light yield were evaluated throughout the phantom and near the gold implant. For experimental validation, a 20 × 20 × 20 cm 3 glass water tank was placed on a programmable platform executing sinusoidal, sawtooth, and sharkfin motions (± 20 mm amplitude; 10‐ and 60‐s cycles). A 5 × 5 cm 2 10 MV FFF beam (2400 MU/min) irradiated the gold implant. A scientific CMOS camera (f/2.0) positioned at 80 cm from the implant captured Cherenkov images. Repeatability was quantified by the standard deviation (SD) across motion cycles. The accuracy was assessed as the absolute difference between the bright‐room reference position and the Cherenkov‐derived position. Images of the implant in sinusoidal motion were also acquired during delivery of a two‐arc brain volumetric modulated arc therapy (VMAT) plan (Arc A and Arc B). Results Monte Carlo simulations showed that Cherenkov light yield throughout the phantom closely correlated with the PDD for all beam energies. The Cherenkov light yield upstream of the gold implant increased by 6.12%, 7.16%, 9.11%, and 7.01% compared to the Cherenkov light yield without the gold implant for 6, 10 FFF, 10, and 15 MV beams, respectively. Experiments confirmed that the beam‐facing side of the gold implant appeared brighter than the opposite side, indicating enhanced backscattered electron production. Cherenkov‐based positional measurements of the periodically moving implant showed close agreement with bright‐room references. For static beams, accuracy across motion patterns was < 0.70 mm with repeatability < 0.2 mm. For the VMAT plan, the accuracies were < 0.50 mm (Arc A) and < 0.70 mm (Arc B). Conclusion The Cherenkov‐light yield was strongly correlated with the deposited dose and showed a notable enhancement around the gold implant. Cherenkov light imaging successfully tracked the dynamic motion of a gold implant in water under high‐dose rate conditions, demonstrating its potential for real‐time fiducial tracking in radiation therapy without additional radiation exposure.

Abstract Hemorrhagic shock is a common emergency that accounts for more than 10% of global mortality and up to 40% of trauma-related mortality. The Advanced Trauma Life Support (ATLS) guidelines outline resuscitation strategies in patients with massive hemorrhage based on clinical trial and observational data. Early intervention with fluids and/or blood products is recommended during resuscitation as key to maintaining vascular patency, stabilizing a patient’s blood pressure, maintaining tissue oxygenation, and limiting shock. From a transfusion perspective, there is wide heterogeneity in the quality of blood products due to donor and manufacturing variation. The optimal transfusion strategy for massive hemorrhage remains unclear. In silico models of resuscitation may offer a means to evaluate the effectiveness and safety of various resuscitation protocols. Here we describe a stochastic multicompartment model of fluid balance and resuscitation that includes (i) cardiovascular hemodynamics, (ii) body fluid compartments and capillary solute exchange, (iii) the ability to alter hemorrhage, resuscitation, and hemostasis parameters, and (iv) tissue oxygenation and capillary-alveolar gas exchange. Building upon deterministic frameworks, this stochastic model more faithfully reflects the clinical heterogeneity of bleeding patients at a level I trauma center. This allows for a proof of concept in silico trial comparing crystalloids, conventional component therapy (CCT), i.e. red cell, platelet and plasma components, to cold-stored low titer group O whole blood (LTOWB). In an in silico cohort of ATLS class III (>30% and ≤40% blood volume lost) hemorrhage, LTOWB resuscitation reduced the time spent in the critical hemostatic window (platelet count <50x109/L, INR≥2, hemoglobin (Hgb) <8 g/dL and fibrinogen <150 mg/dL) compared with CCT (90.59 vs. 147.62 minutes; p=0.04), with no difference in predicted event-free survival (t = 240 minutes; cardiac < 1.5, fluid overload > 10% or SBP > 150% of the starting SBP, or Hgb < 3.0 g/dL). In a separate cohort of ATLS class IV (>40% blood volume lost) hemorrhage, LTOWB yielded a higher predicted event-free survival (74%) versus the CCT arm (69%, p < 0.01). We demonstrate how this in silico platform can function as a digital twin for hemorrhagic trauma enabling precision transfusion strategies, and in parallel, an operational twin to support blood banks to forecast blood product demand and inform massive transfusion protocols and clinical trial design.

Abstract Background: amyotrophic lateral sclerosis is the most common adult-onset motor neuron disease, characterised by the progressive degeneration of upper and lower motor neurons in the brain and spinal cord. Despite substantial advances in the understanding of underlying disease mechanisms, effective therapies remain lacking. Methods: we generated spinal cord organoids from patient-derived induced pluripotent stem cells and matched isogenic controls to model in vitro the molecular pathology associated with the hexanucleotide repeat expansion within the C9orf72 gene. Results: C9orf72 organoids displayed delayed neuronal maturation, axonal degeneration, mitochondrial abnormalities, enhanced apoptotic signaling, and accumulation of dipeptide repeat proteins. Integrated multi-omics analyses revealed a consistent down-regulation of Netrin-1 at both the transcript and protein levels across patient-derived organoids, suggesting that its loss may contribute to impaired neuronal connectivity, compromised axonal integrity, and increased motor neuron vulnerability in C9orf72 amyotrophic lateral sclerosis. Conclusions: together, these findings establish patient-derived spinal cord organoids as a biologically relevant and in vitro model that recapitulates key cellular and molecular hallmarks of C9orf72-associated amyotrophic lateral sclerosis. This platform provides a valuable framework to deepen disease mechanisms, toward the development of new effective therapeutic strategies.

Abstract Background and Aims Clinical models incompletely capture the molecular pathways driving heart failure (HF) progression. This study evaluated whether molecular risk stratification provides incremental prognostic information beyond established clinical predictors in patients with HF. Methods A total of 2432 patients from the Global Congestive Heart Failure (G-CHF) registry with available genotyping, DNA methylation, and proteomic profiling were analysed. Three molecular scores were assessed: a composite cardiovascular polygenic risk score (PRS) from DNA sequence polymorphisms, a methylation risk score (MRS) derived from epigenome-wide associations, and a 23-protein-based score (ProteomicDeath23). Each score was tested individually and in combination with the clinical Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels for mortality prediction. Validation was performed in an HF subset of the UK Biobank (UKB). Results Over a median follow-up of 3.0 years in G-CHF, 523 patients died from any cause (7.64 per 100 person-years [PY]). In multivariable analyses, ProteomicDeath23 was the strongest independent predictor of all-cause mortality (hazard ratio [HR] per 1 standard deviation, 2.23), outperforming NT-proBNP (HR 2.00), MRSMortality (HR 1.66), PRSmetaCVD (HR 1.10), and the MAGGIC score (HR 1.70). A model combining ProteomicDeath23 with MAGGIC and NT-proBNP achieved the highest discrimination for mortality (C-index, 0.77). Addition of MRSMortality to this proteomic-clinical model resulted in only small improvements in discrimination (ΔC-index, +0.004, P = .0039), while the PRSmetaCVD provided no incremental benefit. Among patients with low NT-proBNP/MAGGIC score, mortality rates increased from 1.71 to 8.12 per 100 PY across ProteomicDeath23 tertiles. Consistent results were observed in the UKB-HF validation cohort. Conclusion A proteomic score was the strongest molecular predictor of mortality in HF. Integrating proteomic signatures with clinical risk factors significantly improved risk prediction.

ABSTRACT Airway perforation is a potentially lethal complication from tracheal or mediastinal malignancies that require complex management. Advanced thyroid cancer is known to have high morbidity, and patients with tracheal metastatic lesions are vulnerable to injury. Therapeutic management typically comprises a combination of surgical and nonoperative treatment modalities, whose adverse effects can lead to significant airway injury. We present the case of a 67‐year‐old man with papillary thyroid carcinoma who developed a tracheocutaneous fistula following proton beam therapy and chemotherapy for metastatic disease. Airway repair and recanalization were successfully achieved through a combined surgical and bronchoscopic approach.

Background Motor disturbances are common in neurologic and neurodegenerative syndromes. A standard motor speed and dexterity measure is the finger tapping test (FTT). The FTT has traditionally been administered in clinic using a mechanical FTT, limiting accessibility and early motor change quantification. This study assessed the validity of a smartphone app-based FTT, which may expand access and enable more frequent testing. Methods The cohort was diagnostically diverse, including participants with frontotemporal dementia (FTD), progressive supranuclear palsy (PSP), corticobasal syndrome, primary progressive aphasia, multiple sclerosis, and clinically unimpaired controls. Participants completed a 20-second ALLFTD Mobile App (mApp)-FTT with each hand. Tapping speed metrics were extracted. Participants completed the gold-standard mechanical FTT, a neurologist-administered finger tapping exam, the PSP Rating Scale (PSPRS) and the Unified Parkinson’s Disease Rating Scale (UPDRS). Correlations assessed mApp-FTT and mechanical FTT relationships; regressions evaluated associations with neurologist-rated finger tapping impairment, PSPRS and UPDRS, adjusting for age and sex. Results The mApp-FTT showed moderate-to-strong correlations with the mechanical FTT (dominant: r=0.63, p<0.001; non-dominant: r=0.55, p<0.001). Taps per second were associated with PSPRS motor severity (dominant hand: std. β=-0.59, 95% CI [-0.91, -0.27], p<0.001) and the UPDRS (dominant hand: std. β=-0.41, 95% CI [-0.82, 0.00], p=0.049). Flight time was modestly associated with neurologist-rated finger tapping impairment (dominant hand: std. β=0.15, 95% CI [0.00, 0.29], p=0.044). Conclusion These findings support mApp-FTT validity as a measure of motor function across neurodegenerative conditions. Validation in longitudinal and unsupervised remote settings is warranted to understand scalability and evaluate change over time.

OBJECTIVE Maximal safe resection of intra-axial brain tumors near the motor cortex is aided by intraoperative motor mapping. Here, the authors compared outcomes in patients undergoing either low-frequency bipolar stimulation (LFBS) or high-frequency monopolar stimulation (HFMS) for cortical and/or subcortical motor mapping during brain tumor resection. METHODS A retrospective analysis of patients undergoing an asleep craniotomy with motor mapping or an awake craniotomy with motor and speech mapping with a single surgeon was performed. Three cohorts were compared: 1) asleep LFBS (AsLFBS), 2) awake LFBS (AwLFBS; motor + speech mapping), and 3) asleep HFMS. HFMS mapping was not used for awake craniotomies. RESULTS A total of 284 patients who underwent 300 craniotomies with motor mapping were identified. No significant differences in permanent neurological deficits (p = 0.377) or extent of resection (EOR) of nonenhancing tumors (p = 0.453) were identified between LFBS or HFMS motor mapping cases. Both EOR (92.7% vs 83.5%, p = 0.035) and permanent neurological deficits (7.6% vs 3.3%) occurred more frequently in enhancing tumors with LFBS, although the latter was not statistically significant. HFMS was associated with higher rates of subcortical motor pathway identification (p = 0.001) and fewer total intraoperative seizures (p = 0.003) compared with LFBS. Previous resection (HR 0.46, p = 0.003) and a higher cortical threshold (HR 0.95, p = 0.023) were significantly associated with longer survival, while preoperative aphasia (HR 2.24, p = 0.022), hospital length of stay (HR 1.1, p = 0.005), an insular-based tumor (HR 3.5, p = 0.021), and a histological diagnosis of glioblastoma (HR 2.9, p = 0.001) were negative predictors. Interestingly, overall FLAIR EOR was significantly associated with a marginally decreased overall survival (HR 1.01, p = 0.011). CONCLUSIONS No significant differences in postoperative neurological deficits were found between LFBS and HFMS paradigms. HFMS may identify subcortical motor fibers more reliably while resulting in significantly fewer intraoperative seizures. Although LFBS was associated with greater EOR of contrast-enhancing tumors, it may also be associated with higher rates of postoperative deficits, perhaps reflecting less reliable identification of subcortical motor fibers.

Abstract Background Multiplexed immunofluorescence (MxIF) enables high-dimensional immune cell phenotyping and detailed characterization of the tumor immune microenvironment (TIME), but complex cyclic staining can introduce signal degradation and uncertainty in cell-level measurements. In routine practice, pathologists rely on hematoxylin and eosin (H&E) staining as the primary reference for tissue morphology and frequently cross-reference H&E to interpret MxIF findings. Methods We present a framework for aligning H&E and MxIF images at the tissue microarray (TMA) core level to support cross-modal analysis. Cell nucleus detections from each modality are used as anchor points, formulating the task as a point-set alignment problem. Coherent Point Drift (CPD) is applied for global alignment, followed by graph-matching–based refinement to improve local consistency. Evaluation on ovarian TMAs demonstrates consistent alignment performance for both restained and serial sections. We further explore the use of restained H&E as a reference for MxIF interpretation and investigate virtual H&E generation from MxIF data as a complementary approach when restained H&E is unavailable. Results The aligned images enable quantitative assessment of cross-modal feature concordance between MxIF-derived measurements and H&E morphology. The generated virtual H&E demonstrated similar cell population compared to the real H&E. Conclusions Cell-centric alignment can facilitate integrative multimodal histopathology analysis for TMA cores in spatial co-localization, cell feature validation, and virtual H&E generation.