Mapping wrist motion: 3D CT analysis after scapholunate ligament transection.

The injury of the scapholunate (SL) ligament is common in wrist traumas leading to pain and reduced wrist function. The wrist's unique joint design and possible underlying theories as the carpal row theory were subject to earlier investigations studying wrist kinematics. Nevertheless, a comprehensive understanding of how SL ligament injuries affect wrist biomechanics is still lacking. Through a quantitative analysis of carpal bone motion patterns, we evaluated the impact on wrist kinematics occurring after SL ligament injury. We conducted a study using computer tomography imaging to analyse wrist kinematics after SL ligament transection in 21 fresh-frozen anatomical specimens. The collected data were then transformed into 3D models, employing both standardized global and object coordinate systems. The study encompassed the evaluation of rotation and translation for each individual carpal bone, as well as the ulna, and all metacarpal bones in reference to the radius. The study showed a significant increase in rotation towards palmar (p < 0.01), particularly notable for the scaphoid, following transection of the SL ligament during palmar flexion. Ulnar deviation did not significantly affect rotation or translation, and radial deviation also showed no significant changes in rotation or translation. The study highlights the significance of the SL ligament in wrist kinematics, revealing that SL ligament tears lead to changes in wrist motion. While we observed significant rotational changes for the scaphoid, other carpal bones showed less pronounced alterations, emphasizing the complexity of wrist biomechanics.

The clinical potential of radiomics to predict hematoma expansion in spontaneous intracerebral hemorrhage: a narrative review.

Spontaneous intracerebral hemorrhage (sICH) is associated with significant morbidity and mortality, with subsequent hematoma expansion (HE) linked to worse neurologic outcomes. Accurate, real-time predictions of the risk of HE could enable tailoring management-including blood pressure control or surgery-based on individual patient risk. Although multiple radiographic markers of HE have been proposed based on standard imaging, their clinical utility remains limited by a reliance on subjective interpretation of often ambiguous findings and a poor overall predictive power. Radiomics refers to the quantitative analysis of medical images that can be combined with machine-learning algorithms to identify predictive features for a chosen clinical outcome with a granularity beyond human limitations. Emerging data have supported the potential utility of radiomics in the prediction of HE after sICH. In this review, we discuss the current clinical management of sICH, the impact of HE and standard imaging predictors, and finally, the current data and potential future role of radiomics in HE prediction and management of patients with sICH.

Transformers for colorectal cancer segmentation in CT imaging.

PURPOSE: Most recently transformer models became the state of the art in various medical image segmentation tasks and challenges, outperforming most of the conventional deep learning approaches. Picking up on that trend, this study aims at applying various transformer models to the highly challenging task of colorectal cancer (CRC) segmentation in CT imaging and assessing how they hold up to the current state-of-the-art convolutional neural network (CNN), the nnUnet. Furthermore, we wanted to investigate the impact of the network size on the resulting accuracies, since transformer models tend to be significantly larger than conventional network architectures. METHODS: For this purpose, six different transformer models, with specific architectural advancements and network sizes were implemented alongside the aforementioned nnUnet and were applied to the CRC segmentation task of the medical segmentation decathlon. RESULTS: The best results were achieved with the Swin-UNETR, D-Former, and VT-Unet, each transformer models, with a Dice similarity coefficient (DSC) of 0.60, 0.59 and 0.59, respectively. Therefore, the current state-of-the-art CNN, the nnUnet could be outperformed by transformer architectures regarding this task. Furthermore, a comparison with the inter-observer variability (IOV) of approx. 0.64 DSC indicates almost expert-level accuracy. The comparatively low IOV emphasizes the complexity and challenge of CRC segmentation, as well as indicating limitations regarding the achievable segmentation accuracy. CONCLUSION: As a result of this study, transformer models underline their current upward trend in producing state-of-the-art results also for the challenging task of CRC segmentation. However, with ever smaller advances in total accuracies, as demonstrated in this study by the on par performances of multiple network variants, other advantages like efficiency, low computation demands, or ease of adaption to new tasks become more and more relevant.

In-silico CT lung phantom generated from finite-element mesh.

Several lung diseases lead to alterations in regional lung mechanics, including ventilator- and radiation-induced lung injuries. Such alterations can lead to localized underventilation of the affected areas, resulting in the overdistension of the surrounding healthy regions. Thus, there has been growing interest in quantifying the dynamics of the lung parenchyma using regional biomechanical markers. Image registration through dynamic imaging has emerged as a powerful tool to assess lung parenchyma's kinematic and deformation behaviors during respiration. However, the difficulty in validating the image registration estimation of lung deformation, primarily due to the lack of ground-truth deformation data, has limited its use in clinical settings. To address this barrier, we developed a method to convert a finite-element (FE) mesh of the lung into a phantom computed tomography (CT) image, advantageously possessing ground-truth information included in the FE model. The phantom CT images generated from the FE mesh replicated the geometry of the lung and large airways that were included in the FE model. Using spatial frequency response, we investigated the effect of " imaging parameters" such as voxel size (resolution) and proximity threshold values on image quality. A series of high-quality phantom images generated from the FE model simulating the respiratory cycle will allow for the validation and evaluation of image registration-based estimations of lung deformation. In addition, the present method could be used to generate synthetic data needed to train machine-learning models to estimate kinematic biomarkers from medical images that could serve as important diagnostic tools to assess heterogeneous lung injuries.

HEAL: High-Frequency Enhanced and Attention-Guided Learning Network for Sparse-View CT Reconstruction.

X-ray computed tomography (CT) imaging technology has become an indispensable diagnostic tool in clinical examination. However, it poses a risk of ionizing radiation, making the reduction of radiation dose one of the current research hotspots in CT imaging. Sparse-view imaging, as one of the main methods for reducing radiation dose, has made significant progress in recent years. In particular, sparse-view reconstruction methods based on deep learning have shown promising results. Nevertheless, efficiently recovering image details under ultra-sparse conditions remains a challenge. To address this challenge, this paper proposes a high-frequency enhanced and attention-guided learning Network (HEAL). HEAL includes three optimization strategies to achieve detail enhancement: Firstly, we introduce a dual-domain progressive enhancement module, which leverages fidelity constraints within each domain and consistency constraints across domains to effectively narrow the solution space. Secondly, we incorporate both channel and spatial attention mechanisms to improve the network's feature-scaling process. Finally, we propose a high-frequency component enhancement regularization term that integrates residual learning with direction-weighted total variation, utilizing directional cues to effectively distinguish between noise and textures. The HEAL network is trained, validated and tested under different ultra-sparse configurations of 60 views and 30 views, demonstrating its advantages in reconstruction accuracy and detail enhancement.

Quantitative Analysis of Primary Compressive Trabeculae Distribution in the Proximal Femur of the Elderly.

OBJECTIVE: As osteoporosis progresses, the primary compressive trabeculae (PCT) in the proximal femur remains preserved and is deemed the principal load-bearing structure that links the femoral head with the femoral neck. This study aims to elucidate the distribution patterns of PCT within the proximal femur in the elderly population, and to assess its implications for the development and optimization of internal fixation devices used in hip fracture surgeries. METHODS: This is a retrospective cohort study conducted from March 2022 to April 2023. A total of 125 patients who underwent bilateral hip joint CT scans in our hospital were enrolled. CT data of the unaffected side of the hip were analyzed. Key parameters regarding the PCT distribution in the proximal femur were measured, including the femoral head's radius (R), the neck-shaft angle (NSA), the angle between the PCT-axis and the head-neck axis (α), the distance from the femoral head center to the PCT-axis (δ), and the lengths of the PCT's bottom and top boundaries (L-bottom and L-top respectively). The impact of gender differences on PCT distribution patterns was also investigated. Student's t-test or Mann-Whitney U test were used to compare continuous variables between genders. The relationship between various variables was investigated through Pearson's correlation analysis. RESULTS: PCT was the most prominent bone structure within the femoral head. The average NSA, α, and δ were 126.85 ± 5.85°, 37.33 ± 4.23°, and 0.39 ± 1.22 mm, respectively, showing no significant gender differences (p > 0.05). Pearson's correlation analysis revealed strong correlations between α and NSA (r = -0.689, p < 0.001), and R and L-top (r = 0.623, p < 0.001), with mild correlations observed between δ and NSA (r = -0.487, p < 0.001), and R and L-bottom (r = 0.427, p < 0.001). Importantly, our study establishes a method to accurately localize PCT distribution in true anteroposterior (AP) radiographs of the hip joint, facilitating precise screw placement in proximal femur fixation procedures. CONCLUSION: Our study provided unprecedented insights into the distribution patterns of PCT in the proximal femur of the elderly population. The distribution of PCT in the proximal femur is predominantly influenced by anatomical and geometric factors, such as NSA and femoral head size, rather than demographic factors like gender. These insights have crucial implications for the design of internal fixation devices and surgical planning, offering objective guidance for the placement of screws in hip fracture treatments.

Preclinical characterization of endotoxin-induced uveitis models using OCT, PET/CT and proteomics.

Uveitis is a group of inflammatory ocular pathologies. Endotoxin-Induced Uveitis (EIU) model represent a well-known model induced by administration of Lipopolysaccharide (LPS). The aim is to characterize two models of EIU through two routes of administration with novel noninvasive imaging techniques. 29 rats underwent Intraocular Pressure (IOP) measurements, Optical Coherence Tomography (OCT), proteomic analysis, and Positron Emission Tomography and Computed Tomography (PET/CT). Groups included healthy controls (C), BSS administered controls (Ci), systemically induced EIU with LPS (LPSs), and intravitreally induced EIU with LPS (LPSi) for IOP, OCT, and proteomic studies. For 18F-FDG PET/CT study, animals were divided into FDG-C, FDG-LPSs and FDG-LPSi groups and scanned using a preclinical PET/CT system. LPSi animals exhibited higher IOP post-induction compared to C and LPSs groups. LPSi showed increased cellular infiltrate, fibrotic membranes, and iris inflammation. Proinflammatory proteins were more expressed in EIU models, especially LPSi. PET/CT indicated higher eye uptake in induced models compared to FDG-C. FDG-LPSi showed higher eye uptake than FDG-LPSs but systemic uptake was higher in FDG-LPSs due to generalized inflammation. OCT is valuable for anterior segment assessment in experimental models. 18F-FDG PET/CT shows promise as a noninvasive biomarker for ocular inflammatory diseases. Intravitreal induction leads to higher ocular inflammation. These findings offer insights for future inflammatory disease research and drug studies.

Synthesis and Preclinical Evaluation of [18F]AlF-NOTA-Asp2-PEG2-Folate as a Novel Folate-Receptor-Targeted Tracer for PET Imaging.

Recently, the folate receptor (FR) has become an exciting target for the diagnosis of FR-positive malignancies. Nevertheless, suboptimal in vivo pharmacokinetic properties, particularly high uptake in the renal and hepatobiliary systems, are important limiting factors for the clinical translation of most FR-based radiotracers. In this study, we developed a novel 18F-labeled FR-targeted positron emission tomography (PET) tracer [18F]AlF-NOTA-Asp2-PEG2-Folate modified with a hydrophilic linker (-Asp2-PEG2) to optimize its pharmacokinetic properties and conducted a comprehensive preclinical assessment. The [18F]AlF-NOTA-Asp2-PEG2-Folate was manually synthesized within 30 min with a non-decay-corrected radiochemical yield of 16.3 ± 2.0% (n = 5). Among KB cells, [18F]AlF-NOTA-Asp2-PEG2-Folate exhibited high specificity and affinity for FR. PET/CT imaging and biodistribution experiments in KB tumor-bearing mice showed decent tumor uptake (1.7 ± 0.3% ID/g) and significantly decreased uptake in kidneys and liver (22.2 ± 2.1 and 0.3 ± 0.1% ID/g at 60 min p.i., respectively) of [18F]AlF-NOTA-Asp2-PEG2-Folate, compared to the known tracer [18F]AlF-NOTA-Folate (78.6 ± 5.1 and 5.3 ± 0.5 % ID/g at 90 min p.i., respectively). The favorable properties of [18F]AlF-NOTA-Asp2-PEG2-Folate, including its efficient synthesis, decent tumor uptake, relatively low renal uptake, and rapid clearance from most normal organs, portray it as a promising PET tracer for FR-positive tumors.

Submucosal Lipoma-Induced Small Bowel Intussusception: A Case Study of Surgical Intervention and Management in an Adult Female.

We present an adult patient, a 39-year-old female, with chief complaints of pain in the umbilical region. The patient was further evaluated by radiological investigations and was diagnosed with small bowel intussusception caused by submucosal lipoma as the lead point. She had undergone ileal resection and anastomosis of the affected segment. The postoperative period was uncomplicated, and the patient continued with regular oral intake. The histopathological analysis revealed it to be adipose tissue with no features of atypia. This case shows the rare presentation of small bowel intussusception due to a submucosal lipoma. It emphasizes the significance of diagnostic imaging tools for diagnosis and the need for surgery for proper administration.

Ultra-low dose hip CT-based automated measurement of volumetric bone mineral density at proximal femoral subregions.

BACKGROUND: Forty to fifty percent of women and 13%-22% of men experience an osteoporosis-related fragility fracture in their lifetimes. After the age of 50 years, the risk of hip fracture doubles in every 10 years. x-Ray based DXA is currently clinically used to diagnose osteoporosis and predict fracture risk. However, it provides only 2-D representation of bone and is associated with other technical limitations. Thus, alternative methods are needed. PURPOSE: To develop and evaluate an ultra-low dose (ULD) hip CT-based automated method for assessment of volumetric bone mineral density (vBMD) at proximal femoral subregions. METHODS: An automated method was developed to segment the proximal femur in ULD hip CT images and delineate femoral subregions. The computational pipeline consists of deep learning (DL)-based computation of femur likelihood map followed by shape model-based femur segmentation and finite element analysis-based warping of a reference subregion labeling onto individual femur shapes. Finally, vBMD is computed over each subregion in the target image using a calibration phantom scan. A total of 100 participants (50 females) were recruited from the Genetic Epidemiology of COPD (COPDGene) study, and ULD hip CT imaging, equivalent to 18 days of background radiation received by U.S. residents, was performed on each participant. Additional hip CT imaging using a clinical protocol was performed on 12 participants and repeat ULD hip CT was acquired on another five participants. ULD CT images from 80 participants were used to train the DL network; ULD CT images of the remaining 20 participants as well as clinical and repeat ULD CT images were used to evaluate the accuracy, generalizability, and reproducibility of segmentation of femoral subregions. Finally, clinical CT and repeat ULD CT images were used to evaluate accuracy and reproducibility of ULD CT-based automated measurements of femoral vBMD. RESULTS: Dice scores of accuracy (n = 20), reproducibility (n = 5), and generalizability (n = 12) of ULD CT-based automated subregion segmentation were 0.990, 0.982, and 0.977, respectively, for the femoral head and 0.941, 0.970, and 0.960, respectively, for the femoral neck. ULD CT-based regional vBMD showed Pearson and concordance correlation coefficients of 0.994 and 0.977, respectively, and a root-mean-square coefficient of variation (RMSCV) (%) of 1.39% with the clinical CT-derived reference measure. After 3-digit approximation, each of Pearson and concordance correlation coefficients as well as intraclass correlation coefficient (ICC) between baseline and repeat scans were 0.996 with RMSCV of 0.72%. Results of ULD CT-based bone analysis on 100 participants (age (mean ± SD) 73.6 ± 6.6 years) show that males have significantly greater (p < 0.01) vBMD at the femoral head and trochanteric regions than females, while females have moderately greater vBMD (p = 0.05) at the medial half of the femoral neck than males. CONCLUSION: Deep learning, combined with shape model and finite element analysis, offers an accurate, reproducible, and generalizable algorithm for automated segmentation of the proximal femur and anatomic femoral subregions using ULD hip CT images. ULD CT-based regional measures of femoral vBMD are accurate and reproducible and demonstrate regional differences between males and females.

The first-in-human preclinical evaluation of the new probe [123I]I-PSMA-7 for real-time intraoperative targeted biopsy and SPECT/CT imaging in prostate cancer.

PURPOSE: PSMA/PET has been increasingly used to detect PCa, and PSMA/PET-guided biopsy has shown promising results. However, it cannot be confirmed immediately whether the tissues are the targeted area. In this study, we aimed to develop a novel probe, [123I]I-PSMA-7. First, we hope that [123I]I-PSMA-7 can provide instant confirmation for prostate biopsy. Second, we hope it will help detect PCa. METHODS: We synthesized a high-affinity probe, [123I]I-PSMA-7, and evaluated its properties. We included ten patients with suspected PCa and divided them into two groups. The injection and biopsy were approximately 24 h apart. The activity in biopsy lesions was measured as the cpm by a γ-counter. Moreover, we enrolled 3 patients to evaluate the potential of [123I]I-PSMA-7 for detecting PCa. RESULTS: Animal experiments verified the safety, targeting and effectiveness of [123I]I-PSMA-7, and the tumor-to-muscle ratio was greatest at 24 h, which confirmed the results of this study in humans. After injection of 185MBq [123I]I-PSMA-7, 18/55 cores were positive, and the cpm was significantly greater (4345 ± 3547 vs. 714 ± 547, P < 0.001), with an AUC of 0.97 and a cutoff of 1312 (sens/spec of 94.40%/91.90%). At a lower dose, 10/55 biopsy cores were cancerous, and the cpm was 2446 ± 1622 vs. 153 ± 112 (P < 0.001). The AUC was 1, with a cutoff value of 490 (sens/spec of 100%). When the radiopharmaceuticals were added to 370 MBq, we achieved better SPECT/CT imaging. CONCLUSION: With the aid of [123I]I-PSMA-7 and via cpm-based biopsy, we can reduce the number of biopsies to a minimum operation. [123I]I-PSMA-7 PSMA SPECT/CT can also provide good imaging results. TRIAL REGISTRATION: Chinese Clinical trial registry ChiCTR2300069745, Registered 24 March 2023.

[18F]-florbetaben PET/CT is sensitive for cardiac AL amyloidosis.

Often differential diagnosis between AL and ATTR amyloidosis is difficult. Concerning ATTR, sensitive diagnostic tool, as diphosphonate scintigraphy, was validated, instead of no imaging approach is as accurate in AL. Cardiac ultrasound and circulating biomarkers may raise the clinical suspicion but biopsy remains the only option for diagnosis. We aimed to explore the sensitivity of 18F-Florbetaben PET respect to blood tests or periumbilical fat (POF), cardiac, bone marrow (BM) or other tissues biopsies in a cohort of 33 patients.

Long-term engraftment and maturation of autologous iPSC-derived cardiomyocytes in two rhesus macaques.

Cellular therapies with cardiomyocytes produced from induced pluripotent stem cells (iPSC-CMs) offer a potential route to cardiac regeneration as a treatment for chronic ischemic heart disease. Here, we report successful long-term engraftment and in vivo maturation of autologous iPSC-CMs in two rhesus macaques with small, subclinical chronic myocardial infarctions, all without immunosuppression. Longitudinal positron emission tomography imaging using the sodium/iodide symporter (NIS) reporter gene revealed stable grafts for over 6 and 12 months, with no teratoma formation. Histological analyses suggested capability of the transplanted iPSC-CMs to mature and integrate with endogenous myocardium, with no sign of immune cell infiltration or rejection. By contrast, allogeneic iPSC-CMs were rejected within 8 weeks of transplantation. This study provides the longest-term safety and maturation data to date in any large animal model, addresses concerns regarding neoantigen immunoreactivity of autologous iPSC therapies, and suggests that autologous iPSC-CMs would similarly engraft and mature in human hearts.

Multifaceted Imaging of Renal Lesions With an Emphasis on Cross-Sectional Imaging.

Introduction Renal lesions are common findings encountered in cross-sectional imaging. Ultrasonography (USG), computed tomography (CT), and magnetic resonance imaging (MRI) are available modalities for evaluating renal lesions. The Bosniak classification system aids in classifying a renal lesion into a particular category based on various imaging characteristics on contrast-enhanced CT (CECT).  Materials and methods The CT report archives were searched for the keyword 'Bosniak' lesions, and six illustrative cases were selected to be included in the review. Results Six cases under Bosniak categories I to IV were included in the review. Operative follow-ups were added in cases where patients underwent surgery. Discussion We have reviewed the imaging features of various renal lesions with cross-sectional modalities, namely CT and MRI, with special emphasis on the Bosniak classification system, including its amendments. Conclusion The Bosniak system is widely used to classify and characterize renal lesions. The authors have presented a scoping review of the features of renal lesions and the Bosniak system.

Convergence for nonconvex ADMM, with applications to CT imaging.

The alternating direction method of multipliers (ADMM) algorithm is a powerful and flexible tool for complex optimization problems of the form m i n { f ( x ) + g ( y ) : A x + B y = c } . ADMM exhibits robust empirical performance across a range of challenging settings including nonsmoothness and nonconvexity of the objective functions f and g , and provides a simple and natural approach to the inverse problem of image reconstruction for computed tomography (CT) imaging. From the theoretical point of view, existing results for convergence in the nonconvex setting generally assume smoothness in at least one of the component functions in the objective. In this work, our new theoretical results provide convergence guarantees under a restricted strong convexity assumption without requiring smoothness or differentiability, while still allowing differentiable terms to be treated approximately if needed. We validate these theoretical results empirically, with a simulated example where both f and g are nondifferentiable-and thus outside the scope of existing theory-as well as a simulated CT image reconstruction problem.

AI-Assisted Body Composition Assessment Using CT Imaging in Colorectal Cancer Patients: Predictive Capacity for Sarcopenia and Malnutrition Diagnosis.

(1) Background: The assessment of muscle mass is crucial in the nutritional evaluation of patients with colorectal cancer (CRC), as decreased muscle mass is linked to increased complications and poorer prognosis. This study aims to evaluate the utility of AI-assisted L3 CT for assessing body composition and determining low muscle mass using both the Global Leadership Initiative on Malnutrition (GLIM) criteria for malnutrition and the European Working Group on Sarcopenia in Older People (EWGSOP2) criteria for sarcopenia in CRC patients prior to surgery. Additionally, we aim to establish cutoff points for muscle mass in men and women and propose their application in these diagnostic frameworks. (2) Methods: This retrospective observational study included CRC patients assessed by the Endocrinology and Nutrition services of the Regional University Hospitals of Malaga, Virgen de la Victoria of Malaga, and Vall d'Hebrón of Barcelona from October 2018 to July 2023. A morphofunctional assessment, including anthropometry, bioimpedance analysis (BIA), and handgrip strength, was conducted to apply the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia. Body composition evaluation was performed through AI-assisted analysis of CT images at the L3 level. ROC analysis was used to determine the predictive capacity of variables derived from the CT analysis regarding the diagnosis of low muscle mass and to describe cutoff points. (3) Results: A total of 586 patients were enrolled, with a mean age of 68.4 ± 10.2 years. Using the GLIM criteria, 245 patients (41.8%) were diagnosed with malnutrition. Applying the EWGSOP2 criteria, 56 patients (9.6%) were diagnosed with sarcopenia. ROC curve analysis for the skeletal muscle index (SMI) showed a strong discriminative capacity of muscle area to detect low fat-free mass index (FFMI) (AUC = 0.82, 95% CI 0.77-0.87, p < 0.001). The identified SMI cutoff for diagnosing low FFMI was 32.75 cm2/m2 (Sn 77%, Sp 64.3%; AUC = 0.79, 95% CI 0.70-0.87, p < 0.001) in women, and 39.9 cm2/m2 (Sn 77%, Sp 72.7%; AUC = 0.85, 95% CI 0.80-0.90, p < 0.001) in men. Additionally, skeletal muscle area (SMA) showed good discriminative capacity for detecting low appendicular skeletal muscle mass (ASMM) (AUC = 0.71, 95% CI 0.65-0.76, p < 0.001). The identified SMA cutoff points for diagnosing low ASMM were 83.2 cm2 (Sn 76.7%, Sp 55.3%; AUC = 0.77, 95% CI 0.69-0.84, p < 0.001) in women and 112.6 cm2 (Sn 82.3%, Sp 58.6%; AUC = 0.79, 95% CI 0.74-0.85, p < 0.001) in men. (4) Conclusions: AI-assisted body composition assessment using CT is a valuable tool in the morphofunctional evaluation of patients with colorectal cancer prior to surgery. CT provides quantitative data on muscle mass for the application of the GLIM criteria for malnutrition and the EWGSOP2 criteria for sarcopenia, with specific cutoff points established for diagnostic use.

Chest CT Imaging Provides More Information Than Chest Radiography Alone in Determining Extent of Physiologic Impairment in Pulmonary Sarcoidosis.

BACKGROUND: Sarcoidosis staging primarily has relied on the Scadding chest radiographic system, although chest CT imaging is finding increased clinical use. RESEARCH QUESTION: Whether standardized chest CT scan assessment provides additional understanding of lung function beyond Scadding stage and demographics is unknown and the focus of this study. STUDY DESIGN AND METHODS: We used the National Heart, Lung, and Blood Institute study Genomics Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis cases of sarcoidosis (n = 351) with Scadding stage and chest CT scans obtained in a standardized manner. One chest radiologist scored all CT scans with a visual scoring system, with a subset read by another chest radiologist. We compared demographic features, Scadding stage, and CT scan findings and the correlation between these measures. Associations between spirometry results and Dlco, CT scan findings, and Scadding stage were determined using regression analysis (n = 318). Agreement between readers was evaluated using Cohen's κ value. RESULTS: CT scan features were inconsistent with Scadding stage in approximately 40% of cases. Most CT scan features assessed on visual scoring were associated negatively with lung function. Associations persisted for FEV1 and Dlco when adjusting for Scadding stage, although some CT scan feature associations with FVC became insignificant. Scadding stage was associated primarily with FEV1, and inclusion of CT scan features reduced significance in association between Scadding stage and lung function. Multivariable regression modeling to identify radiologic measures explaining lung function included Scadding stage for FEV1 and FEV1 to FVC ratio (P < .05) and marginally for Dlco (P < .15). Combinations of CT scan measures accounted for Scadding stage for FVC. Correlations among Scadding stage and CT scan features were noted. Agreement between readers was poor to moderate for presence or absence of CT scan features and poor for degree and location of abnormality. INTERPRETATION: CT scan features explained additional variability in lung function beyond Scadding stage, with some CT scan features obviating the associations between lung function and Scadding stage. Whether CT scan features, phenotypes, or endotypes could be useful for managing patients with sarcoidosis needs more study.

Cerebral [18F]AIF-FAPI-42-Based PET Imaging of Fibroblast Activation Protein for Non-invasive Quantification of Fibrosis After Ischemic Stroke.

The development of fibrosis after injury to the brain or spinal cord limits the regeneration of the central nervous system in adult mammals. However, the extent of fibrosis in the injured brain has not been systematically investigated in mammals in vivo. This study aimed to assess whether [18F]AlF-FAPI-42-based cerebral positron emission tomography (PET) can be utilized to assess the extent of fibrosis in ischemic regions of the brain in vivo. Sprague-Dawley rats underwent permanent occlusion of the right middle cerebral artery (MCAO). On days 3, 7, 14, and 21 after MCAO, the uptake of [18F]AlF-FAPI-42 in the ischemic region of the brain in the MCAO groups surpassed that in the control group (day 0). The specific expression of fibroblast activation protein-α (FAP) in ischemic regions of the brain was also confirmed in immunohistofluorescence experiments in vitro. [18F]AlF-FAPI-42 intensity correlated with the density of collagen deposition in the ischemic hemisphere (p < 0.001). [18F]AlF-FAPI-42 PET/CT imaging demonstrated a specific uptake of radioactivity in the infarcted area in an ischemic stroke patient. PET imaging by using [18F]AlF-FAPI-42 offers a promising non-invasive method for monitoring the progression of cerebral fibrosis caused by ischemic stroke and may facilitate the clinical management of stroke patients. Trial registration: chictr.org.cn ChiCTR2200059004. Registered April 22, 2022.