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Deep learning-based magnetic resonance imaging (MRI) reconstruction has shown promise in improving image quality and reducing scan time. However, its impact on diffusion-weighted imaging (DWI) and quantitative parameters such as apparent diffusion coefficient (ADC) in patients with intracranial tumors remains unclear. This study aims to investigate the impact of deep learning-based MRI reconstruction on the quality of diffusion-weighted images and the measurements of lesion ADC in patients with intracranial tumors. Additionally, it assessed the potential influence of this reconstruction method on the consistency of ADC-based quantitative analysis. This single-center, prospective intra-individual study involved 58 consecutive adults diagnosed with intracranial space-occupying lesions through imaging and/or pathology. These patients underwent brain MRI between January and May 2025, and all received standard single-b-value DWI (b=1,000 s/mm2). The raw DWI data were reconstructed using two methods: a conventional algorithm and a vendor-supplied deep learning reconstruction (DLR) algorithm based on convolutional neural networks. An experienced neuroradiologist manually placed regions of interest (ROIs) on the slice containing the lesion, including the lesion itself, the surrounding perilesional tissue, and the background. For each ROI, signal intensity (SI) and its standard deviation (SD) were measured, along with the lesion's ADC values. The image quality metrics and ADC values obtained from the two reconstruction methods were compared using paired t-tests. Compared with conventional reconstruction, DLR significantly reduced background SI (29.40&#xb1;5.05 vs. 34.95&#xb1;4.99; t=13.948, P<0.001) and background noise (14.63&#xb1;3.50 vs. 20.61&#xb1;4.17; t=14.721, P<0.001), corresponding to approximately a 30% noise reduction. Lesion SI was slightly but significantly higher with DLR (1,786.42&#xb1;878.56 vs. 1,782.41&#xb1;878.79; t=2.863, P=0.006), while SI in perilesional tissue exhibited no significant difference (P=0.259). DLR also demonstrated significantly lower lesion ADC values than conventional reconstruction [(1,247.10&#xb1;567.37)&#xd7;10-6 vs. (1,324.41&#xb1;617.97)&#xd7;10-6 mm2/s, t=2.974, P=0.004], with an average decrease of about 6%. Under a conventional single-b-value DWI protocol (b=1,000 s/mm2), deep learning-based MRI reconstruction improved image quality in patients with intracranial tumors by reducing background noise and slightly increasing lesion signal. However, it was also associated with a modest but systematic decrease in lesion ADC values, suggesting that quantitative diffusion metrics may be affected to some extent. Further validation is needed to determine the clinical significance of this ADC shift and to assess the potential utility of DLR in more demanding diffusion imaging settings.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive malignancies with limited diagnostic and prognostic markers. Neutrophil extracellular traps (NETs) have recently been implicated in cancer progression, but their clinical relevance in PDAC remains underexplored. In this preliminary study, we investigated NET levels in both peripheral blood and tumor tissues from PDAC patients (n&#xa0;=&#xa0;30) and explored their associations with clinicopathological features. We quantified NETs using a multiparametric approach that included immunohistochemistry, immunofluorescence, qRT-PCR, ELISA, and flow cytometry. Plasma NET-associated DNA was measured using the Quant-iT PicoGreen assay. Receiver operating characteristic (ROC) analysis was performed to assess the diagnostic potential of NETs. We found NET levels were significantly elevated in both tumor tissue and the circulation of PDAC patients compared with healthy controls. The levels of NETs were strikingly higher in patients with advanced tumor stages and grades. Patients' NETs showed a typical morphology with enlarged nuclei, thread-like DNA fibres, and MPO-positive granules, which was confirmed by immunofluorescence analysis. The ROC analysis demonstrated that NETs displayed promising diagnostic performance (AUC&#xa0;=&#xa0;0.852) compared to widely used conventional markers CEA and CA19-9 within the study cohort. In conclusion, our findings provide preliminary evidence that increased NETosis is associated with PDAC progression and highlight its potential as a diagnostic biomarker. Larger, independent studies are needed to validate these observations and to determine the clinical relevance of NET-associated markers in PDAC.

The rupture and demyelination of nerve fibers after spinal cord injury (SCI) are primary contributors to neurological dysfunction. The axon attraction signal pathway mediated by netrin-1 is crucial for promoting the effective regeneration and repair of nerve axons. Previous studies have proved that electroacupuncture (EA) can improve nerve function and promote nerve repair and regeneration in rats with SCI, yet its underlying mechanism remains to be elucidated. This study aims to evaluate the effects of EA on neural repair and to investigate its regulatory role in the axon guidance signaling pathway, thereby clarifying the mechanisms by which EA promotes nerve repair following SCI. Male Sprague Dawley rats were randomly assigned to the Normal group, Sham group, SCI group, and EA group, with each group further divided into subgroups based on intervention duration: 7, 14, and 28 days. Allen's method was employed to establish the SCI model. Dazhui (GV14) and Mingmen (GV4) acupoints were selected for EA intervention. Basso-Beattie-Bresnahan (BBB) score and the inclined plate test were used to evaluate the motor function of rats in each group. Morphological and structural changes in the injured spinal cord were assessed through magnetic resonance imaging (MRI). The fractional anisotropy (FA), radial diffusivity (RD), and mean diffusivity (MD) values in the injured area were measured via diffusion tensor imaging (DTI), and the morphological changes of nerve fiber bundles were analyzed via diffusion tensor tractography (DTT). The expressions of netrin-1, deleted in colorectal cancer (DCC), ras-related C3 botulinum toxin substrate 1 (Rac1) and F-actin were quantified using immunofluorescence (IF) staining, Western blot (WB) and real-time quantitative polymerase chain reaction (RT-PCR). Compared with the Sham group, the SCI group exhibited significant deficits in motor function (P<0.01), disorganized spinal cord tissue structure, a markedly increased lesion area (P<0.01), impaired integrity of nerve fiber bundles, a significant decrease in FA value (P<0.01), and significantly elevated MD and RD values (P<0.01). Moreover, the expression levels of netrin-1, DCC, Rac1, and F-actin were significantly reduced (P<0.01). EA improved the behavioral performance of rats with SCI (P<0.01). Following EA intervention, the extent of spinal cord structural damage was alleviated, with increased FA values, decreased MD and RD values (P<0.01), alongside evident repair and reconstruction of damaged fiber bundles. Additionally, EA upregulated the expression levels of netrin-1, DCC, Rac1, and F-actin (P<0.01). EA can significantly improve the motor function of rats with SCI, regulate the nerve guidance factor netrin-1 and its receptor DCC, as well as the molecular switch Rac1, thereby promoting axonal cytoskeletal remodeling and facilitating neural repair. The nerve repair effect of EA may be achieved by regulating the axon attraction signal pathway mediated by netrin-1.

Diffusion-weighted imaging (DWI) in the female pelvis is degraded by artefacts. The study aimed to evaluate the impact of deep-learning image reconstruction (DLRecon) on the image quality of multiplexed sensitivity encoding (MUSE) DWI in the female pelvis. Female patients scheduled for pelvic magnetic resonance imaging (MRI) with 2-shot MUSE DWI were prospectively recruited. A subset of patients underwent paired 4-shot MUSE DWI. Images were qualitatively reviewed by two radiologists in terms of overall image quality, artefacts, lesions conspicuity and sharpness using a 5-point scale, with and without DLRecon. Intra-observer and inter-observer agreements were evaluated. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and apparent diffusion coefficient (ADC) of normal structures and lesions were quantitatively compared between 2-shot MUSE with and without DLRecon. Statistical analyses were performed using Cohen's kappa, Wilcoxon signed-rank test and paired-sample t-test with Bonferroni correction. Among the 65 female patients evaluated, 27 malignant lesions and 32 benign lesions were detected, while no pathology was found in 6 patients. DLRecon significantly improved the image quality in all aspects evaluated compared to 2-shot MUSE without DLRecon: overall image quality, artefacts, lesions conspicuity and sharpness (N=65, P<0.001). Furthermore, there was no statistical difference in the image quality between 2-shot MUSE with DLRecon and 4-shot MUSE without DLRecon (N=42, P=0.079-0.225). Inter- and intra-observer agreements were substantial to excellent (&#x3ba;=0.664-0.815). Both SNR and CNR were increased with DLRecon (P<0.050); while no statistical difference was observed in ADC measurements in gluteus muscle (P=0.194), uterus (P=0.127) and lesions (P=0.414). DLRecon improved image quality of MUSE DWI in the female pelvis by reducing impact of artefacts, improving lesion conspicuity and image sharpness, while increasing SNR and CNR but preserving the stability of ADC quantification.

Heart failure with preserved ejection fraction (HFpEF) predominantly affects postmenopausal women, but its underlying mechanisms remain unclear. Epicardial adipose tissue (EAT), a metabolically active fat depot adjacent to the myocardium, has been implicated in HFpEF. This study aimed to evaluate the associations of EAT volume and density with HFpEF in postmenopausal women and to determine whether myocardial fibrosis mediates this relationship. In this retrospective cross-sectional study, we included 70 postmenopausal women with HFpEF and 70 age-matched controls (&#xb1;3 years) who underwent cardiac computed tomography (CT). EAT volume and density were quantified from coronary artery calcium scoring images. Myocardial extracellular volume (ECV), derived from dual-energy CT, was used to quantify myocardial fibrosis. Multivariable regression analyses and mediation analyses were performed to evaluate the associations between EAT characteristics, ECV, and HFpEF. EAT volume index, density, and ECV were significantly higher in the HFpEF group than in controls (all P<0.05). After adjustment for cardiovascular risk factors and comorbidities, higher EAT density [per 1-Hounsfield unit (HU) increase; odds ratio (OR) =1.209; 95% confidence interval (CI): 1.073-1.362; P=0.002] and ECV (per 1% increase; OR =1.306; 95% CI: 1.104-1.510; P=0.001) remained independently associated with HFpEF. ECV mediated 47.7% of the relation between EAT density and HFpEF (effect =0.188; 95% CI: 0.094-0.296; P<0.05). EAT density was independently associated with ECV in the postmenopausal population (&#x3b2; =0.39, P<0.001). EAT density is more strongly and independently associated with HFpEF in postmenopausal women than EAT volume. Myocardial fibrosis, measured as ECV, partially mediated the association between EAT density and HFpEF, supporting the concept of an EAT-myocardial fibrotic axis in the pathophysiology of HFpEF in this population.

Preoperative three-dimensional (3D) vascular reconstruction from non-contrast computed tomography (NCCT) is often hindered by limited vessel differentiation, whereas contrast-enhanced computed tomography (CECT) is contraindicated for certain patients. This study examined the use of a generative adversarial network (GAN) for synthetic CECT (Syn-CECT)-like images from NCCT, preliminarily evaluating its clinical potential to assist in perinodular vascular segmentation and 3D reconstruction. This retrospective study included 212 patients. To mitigate the spatial misalignments caused by respiratory motion, the training phase (130 patients) included paired virtual non-contrast (VNC) and true CECT images derived from spectral computed tomography (CT). A Pix2pixGAN framework integrating an attention mechanism and a 2.5-dimensional (2.5D) strategy was applied to synthesize Syn-CECT. The model was then validated on external test sets (82 patients) from two different CT vendors. A quantitative evaluation was conducted via objective image quality metrics. The vascular reconstruction performance within a 50-mm spherical region around pulmonary nodules was quantitatively assessed according to the local Dice similarity coefficient (LocalDice), fragmentation index (FragIndex), and 95th percentile Hausdorff distance (HD95), alongside subjective physician scoring. In external testing, Syn-CECT showed favorable structural compared to original NCCT as indicated by the multiscale structural similarity index measurement. For the downstream 3D vascular segmentation task, Syn-CECT yielded measurable improvements over NCCT, reflected by a moderately higher LocalDice (0.89-0.90 vs. 0.85-0.89), a lower FragIndex (3.82-5.92 vs. 4.54-8.68), and a lower HD95 (0.08 vs. 0.09-0.12) (all P values <0.01), suggesting better structural continuity and boundary alignment. In terms of subjective evaluation, Syn-CECT received more favorable median vessel visibility scores (score of 4) than did NCCT (score of 3), offering improved visual clarity for evaluating local vasculature. Using a GAN model to synthesize CECT-like images from standard NCCT scans can moderately improve the continuity and accuracy of 3D pulmonary vascular reconstructions. This image translation strategy demonstrated preliminary clinical value as an adjunctive tool for sublobar resection planning and may serve as a practical alternative for obtaining enhanced vascular anatomical details, especially for patients with contraindications to iodinated contrast media.

There is a relative scarcity of studies focusing on fat infiltration in the supraspinatus muscle using musculoskeletal ultrasound (MSK US). This study aimed to investigate the clinical application value of MSK US in assessing fat infiltration of the supraspinatus muscle in patients with supraspinatus tendon tears. We conducted a retrospective analysis of 154 patients diagnosed with supraspinatus tendon tears by arthroscopy. All patients underwent semi-quantitative grading of supraspinatus muscle fat infiltration using MSK US, complemented by shear wave elastography (SWE). Magnetic resonance imaging (MRI) served as the gold standard. Diagnostic performance metrics were calculated for MSK US in detecting fat infiltration, and Kappa consistency analysis was assessed between MSK US and MRI findings. Additionally, Spearman correlation analysis was performed to evaluate the relationship between the degree of fat infiltration quantified by MSK US and the extent of supraspinatus tendon tear as determined arthroscopically. Arthroscopic results revealed full-thickness tears in 50 patients (32.47%, 50/154), and partial tears in 104 patients (67.53%, 104/154). In terms of tear grades by arthroscopy, 22 cases were Grade I (14.29%, 22/154), 38 were Grade II (24.68%, 38/154), and 94 were Grade III (61.04%, 94/154). The SWE measurements demonstrated significantly lower shear wave velocity in the affected supraspinatus muscle (2.52&#xb1;0.56 cm/s) compared with the healthy side (3.03&#xb1;0.64 cm/s; t=7.42, P<0.001). Using MRI as a reference standard, MSK US achieved a sensitivity of 94.90%, specificity of 82.14%, positive predictive value of 90.29%, negative predictive value of 90.20%, accuracy rate of 90.26%, and an area under the receiver operating characteristic (ROC) curve of 0.89. A statistically significant positive correlation was observed between the degree of supraspinatus muscle fat infiltration assessed by MSK US and the extent of supraspinatus tendon tear determined arthroscopically (rs=0.47, P<0.001). The fat infiltration in the supraspinatus muscle, as assessed by MSK US, demonstrated moderate consistency with MRI diagnoses, underscoring its high clinical value. A strong association was observed between supraspinatus muscle fat infiltration and the severity of supraspinatus tendon tears. Specifically, higher-grade tendon tears were significantly correlated with greater degrees of fat infiltration within the supraspinatus muscle.

Contrast media-related adverse events pose serious risks, not only due to allergic reactions but also for patients with renal failure, older age, heart failure, and diabetes mellitus. Various efforts have been made to maximize vascular contrast enhancement (CE) using low-concentration contrast media. This study aimed to compare quantitative and qualitative image characteristics between vendor-agnostic and vendor-specific CE boost methods in low-concentration contrast medium settings against standard-concentration contrast medium settings. This retrospective study including 160 patients compared two concentrations of iodinated contrast media-350 mg I/mL (standard-concentration group) and 270 mg I/mL (low-concentration group) who underwent contrast-enhanced abdominal computed tomography (CT). Vendor-agnostic and vendor-specific boost methods were applied to the CT images of the low-concentration group. Quantitative [image noise, CT attenuation, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), noise power spectrum, and image sharpness] and qualitative (Likert scale rating by two radiologists) measures of image quality were evaluated in abdominal vessels and liver lesions. The present study included 80 patients in the standard-concentration and 80 patients in the low-concentration group, respectively. There were no significant differences in age (P=0.75), sex (P=0.99), and body mass index (P=0.98) between the two groups. Both vendor-agnostic and vendor-specific CE-boost methods significantly reduced image noise (P<0.001) and improved CT attenuation, SNR, and CNR in both vessels and liver lesions (all P<0.001) in the low-concentration group compared to the corresponding values in the standard-concentration group. The vendor-specific boost method was more effective in suppressing high-frequency noise (P<0.001), whereas the vendor-agnostic boost method yielded sharper images (0.31&#xb1;0.02 vs. 0.29&#xb1;0.01; P<0.001). Subjective image analysis revealed significantly higher image quality (P<0.001) for both boost methods compared with standard-concentration contrast medium groups. Although vendor-agnostic and vendor-specific CE-boost methods effectively enhanced image quality and CT attenuation in low-concentration contrast medium settings, subjective image analysis revealed lower ratings due to increased artificial appearance. The vendor-agnostic method provided superior image sharpness, whereas the vendor-specific method more effectively reduced structured noise and achieved higher subjective ratings for overall image quality, artificial suppression, and natural image appearance.

Right upper lobectomy (RUL) is the most frequently performed lobectomy for lung cancer, yet postoperative functional loss varies widely among patients. We hypothesized that thoracic morphology constrains three-dimensional (3D) repositioning of the residual lung after RUL, leading to characteristic bronchial axis deviation and rotation-like deformation, and that these geometric changes might be associated with postoperative residual-lobe expansion. We retrospectively analyzed 26 patients who underwent RUL (2016-2018), including five with middle lobe atelectasis (MLA). Paired pre- and postoperative computed tomography was used to quantify residual-lobe volumes and geometric markers (thoracic morphology, sagittal bronchial axis deviation of B4/5 and B6, and plane-based rotation-like deformation) and to test their associations with repositioning patterns and postoperative expansion. Two distinct residual-lung repositioning patterns were identified: a B6-dominant pattern, in which the superior segment (S6) ascended to occupy the postoperative apical space (Type B6), and a B4/5-dominant pattern, in which the middle lobe migrated cranially (Type B4/5). Type B6 was associated with barrel-shaped thoraces, whereas Type B4/5 was associated with flatter thoraces [thoracic height-to-anteroposterior diameter (H/AP) ratio, P=0.001; 8th-rib angle, P<0.001]. Rotation-like deformation patterns differed between the two types and supported their geometric distinction. However, neither thoracic morphology, repositioning pattern, bronchial axis deviation, nor rotation-like metrics were associated with postoperative middle-plus-lower lobe volume expansion (Type B6 vs. Type B4/5, P=0.42; H/AP ratio, P=0.28; 8th-rib angle, P=0.61; &#x394;B4/5, P=0.06; &#x394;B6, P=0.65; &#x394;Y, P=0.68; &#x394;X, P=0.69). MLA occurred in both patterns (Type B6, n=2; Type B4/5, n=3) and was associated with reduced postoperative expansion [middle + lower volume ratio (post/pre), P=0.02] but showed no distinctive geometric predictors. Thoracic morphology influences 3D residual-lung repositioning after RUL, producing characteristic geometric patterns. Nevertheless, these geometric responses alone do not explain postoperative residual-lobe expansion, highlighting the need to integrate functional determinants with geometric assessment.

Lipid-based nanoparticles are widely explored as non-viral vectors for nucleic acid delivery, where the molecular structure of cationic lipids strongly determines their performance. Five-membered heterocyclic linkers were explored as a new structural motif in cationic amphiphilic lipids for the development of promising gene delivery candidates. Novel lipids incorporating pyrrole, furan, and thiophene linkers were synthesized alongside structurally related aliphatic analogues, enabling systematic evaluation of how linker type influences physicochemical behavior and self-assembly properties. Self-assembly behavior in aqueous media was characterized by dynamic light scattering, and pDNA encapsulation efficiency was measured using the Quant-iT Pico-Green method. The resulting liposomes exhibited hydrodynamic diameters ranging from 92 to 1317 nm, while corresponding lipoplexes ranged from 302 to 1159 nm. Amphiphiles containing heterocyclic linkers demonstrated high pDNA encapsulation (>80% at optimal N/P ratios), whereas aliphatic analogues showed significantly reduced performance. These results demonstrate that linker structure strongly influences both self-assembly and nucleic acid binding properties. By evaluating structure-activity relationships, five-membered heterocycles are proposed as promising structural elements for the rational development of lipid-based gene delivery candidates.

Fractures of the fifth metatarsal bone are frequent in athletes, yet the mechanical conditions that increase stress in this region are not fully understood. Understanding how foot positioning influences local stress may help clarify potential risk factors related to sports activities. The aim of this study was to evaluate how different foot loading directions and ankle positions affect the stress, strain, and deformation of the fifth metatarsal bone using a three-dimensional (3D) computational model. A 3D model of the human foot was created from computed tomography (CT) imaging and included cortical bone, trabecular bone, and cartilage structures. Six loading conditions representing different ankle positions between forty and ninety degrees were simulated. A load equivalent to approximately three times body weight was applied to replicate impact during unilateral landing. Stress, strain, and deformation of the fifth metatarsal bone were quantified for each loading condition. The highest stress value in the fifth metatarsal bone occurred at 60&#xb0; of dorsiflexion, with a stress magnitude of 3.18 MPa, a deformation of 0.071 mm, and a strain of 1.46&#xd7;10-4. The lowest stress value occurred when the load was applied vertically at 90&#xb0;, with a stress of 0.66 MPa, a deformation of 0.009 mm, and a strain of 2.72&#xd7;10-5. The first and fifth metatarsal bones consistently showed the greatest concentration of mechanical stress across all load conditions. Changes in foot position substantially influence the mechanical response of the fifth metatarsal bone. Dorsiflexion at sixty degrees generated the highest stress values and may represent a potentially critical condition for this region during high-impact sports movements.

Currently, it is still very challenging for radiologists to visually distinguish between benign and malignant ground-glass nodules (GGNs) and predict the degree of invasiveness of GGNs directly from computed tomography (CT) images. Radiomics is a newly emerging technique that can transform digital medical images into numerous quantitative features revealing pathophysiology. The present study aimed to evaluate the predictive value of intratumoral and peritumoral CT-based radiomics and the radiomics nomogram for determining the benign or malignant status of pulmonary GGNs and the invasiveness of malignant GGNs. A total of 1,372 GGNs from 1,280 patients with preoperative CT scans were included in this retrospective study. Among these, 212 GGNs were diagnosed with inflamed or infected benign lesions, 31 with atypical adenomatous hyperplasia (AAH), 257 with adenocarcinoma in situ (AIS), 559 with minimally invasive adenocarcinoma (MIA), and 313 with invasive adenocarcinoma (IAC). Malignant GGNs were classified according to clinical management strategies, with AAH, AIS, and MIA categorized as non-invasive lesions, and IAC as an invasive lesion. Two types of regions of interest (ROIs) were annotated from the CT images: gross tumor volume (GTV) and peritumoral volume (5 and 10 mm around the tumor, PTV1 and PTV2). Radiomics models, a clinical factor model, and a combined radiomics nomogram integrating the radiomics score with independent clinical predictors were constructed and compared. For malignancy predictions, the GTV + PTV1 + PTV2 radiomics model and the PTV1 radiomics model achieved the highest performance in the training set and testing set, with areas under the curve (AUCs) of 0.840 and 0.796, respectively. The combined radiomics nomogram demonstrated excellent discrimination in both the training set and testing set, with AUCs of 0.870 and 0.817, respectively. Moreover, the DeLong test showed that in both the training and validation cohorts, the AUC values of the comprehensive nomogram were significantly different from those of the clinical factor model, GTV radiomics model, PTV2 radiomics model, and GTV + PTV1 + PTV2 radiomics models (P<0.05). For invasiveness predictions, the GTV + PTV1 + PTV2 radiomics model exhibited the highest performance in the training set and testing set, with AUCs of 0.956 and 0.954, respectively. Similarly, the combined radiomics nomogram showed excellent discriminatory performance in both the training set and testing set, with AUCs of 0.962 and 0.957, respectively. Furthermore, the DeLong test demonstrated that the AUC values of the comprehensive nomogram were significantly different from those of the clinical factor model and the PTV2 radiomics model in both cohorts (P<0.05). The radiomic signatures of both GTV and PTV1 show strong predictive capabilities for the malignancy and invasiveness of GGNs, with the PTV1 radiomics model performing comparably to, or even surpassing, that of the GTV radiomics model. The proposed nomogram demonstrated the best performance in assessing malignancy and invasiveness in patients with GGNs. It may serve as a powerful tool to assist clinicians in formulating personalized treatment strategies.

Sarcopenia is a prevalent condition associated with adverse health outcomes, necessitating accurate assessment of skeletal muscle quantity and quality. Computed tomography (CT) is the gold-standard imaging modality for evaluating trunk skeletal muscle area (TrSMA) and density (TrSMD), with opportunistic CT offering a means to assess these metrics without additional radiation exposure. However, the clinical application of CT-based sarcopenia assessment in Chinese populations is hindered by the absence of large-scale, population-specific reference values and cut-off points, particularly for both myopenia (low muscle mass) and myosteatosis (fatty infiltration). This study aims to establish sex- and age-specific percentile reference values and diagnostic cut-off points for CT-derived TrSMA and TrSMD at the L1 and L3 vertebral levels with a large cohort of community-dwelling Chinese adults. We retrospectively analyzed abdominal CT scans from 4,016 community&#x2011;dwelling Chinese adults (21-80 years) across 12 regions. TrSMA and TrSMD at L1 and L3 were segmented using OsiriX. Sex- and age-specific percentile curves were modeled using the lambda-mu-sigma (LMS) method within the generalized additive models for location, scale, and shape (GAMLSS) framework. Estimated age-related differences in TrSMA and TrSMD from ages 25 to 75 years were calculated using LMS-derived medians. Sex&#x2011;specific cut&#x2011;off points for myopenia and myosteatosis were defined in the 21- to 40-year subgroup using the mean minus two standard deviations (M&#x2011;2SD) approach. From ages 25 to 75 years, LMS-derived L1/L3-TrSMA values were lower by 0.45%/0.55% per year in men and 0.33%/0.41% per year in women; corresponding differences in L1/L3-TrSMD were 0.38%/0.35% and 0.55%/0.52% per year. More pronounced age-related decreases were observed in peri- and postmenopausal women and older men. M&#x2011;2SD cut&#x2011;offs at L1 were 96.0 cm2 and 29.8 Hounsfield Unit (HU) (men), 63.1 cm2 and 26.4 HU (women); at L3 were 122.3 cm2 and 31.7 HU (men), 75.4 cm2 and 27.5 HU (women). We provide the first CT&#x2011;based, sex&#x2011; and age&#x2011;specific reference values and cut&#x2011;points for trunk myopenia and myosteatosis in Chinese adults, facilitating standardized sarcopenia diagnosis and research.