A joint brain extraction and image quality assessment framework for fetal brain MRI slices.

Brain extraction and image quality assessment are two fundamental steps in fetal brain magnetic resonance imaging (MRI) 3D reconstruction and quantification. However, the randomness of fetal position and orientation, the variability of fetal brain morphology, maternal organs around the fetus, and the scarcity of data samples, all add excessive noise and impose a great challenge to automated brain extraction and quality assessment of fetal MRI slices. Conventionally, brain extraction and quality assessment are typically performed independently. However, both of them focus on the brain image representation, so they can be jointly optimized to ensure the network learns more effective features and avoid overfitting. To this end, we propose a novel two-stage dual-task deep learning framework with a brain localization stage and a dual-task stage for joint brain extraction and quality assessment of fetal MRI slices. Specifically, the dual-task module compactly contains a feature extraction module, a quality assessment head and a segmentation head with feature fusion for simultaneous brain extraction and quality assessment. Besides, a transformer architecture is introduced into the feature extraction module and the segmentation head. We utilize a multi-step training strategy to guarantee a stable and successful training of all modules. Finally, we validate our method by a 5-fold cross-validation and ablation study on a dataset with fetal brain MRI slices in different qualities, and perform a cross-dataset validation in addition. Experiments show that the proposed framework achieves very promising performance.

Reaction-Initiated Single-Molecule Tracking of Mass Transfer in Core-Shell Mesoporous Silica Particles.

Understanding the host-guest interactions in porous materials is of great importance in the field of separation science. Probing it at the single-molecule level uncovers the inter- and intraparticle inhomogeneity and establishes structure-property relationships for guiding the design of porous materials for better separation performance. In this work, we investigated the dynamics of host-guest interactions in core-shell mesoporous silica particles under in situ conditions by using a fluorogenic reaction-initiated single-molecule tracking (riSMT) approach. Taking advantage of the low fluorescence background, three-dimensional (3D) tracking of the dynamics of the molecules inside the mesoporous silica pore was achieved with high spatial precision. Compared to the commonly used two-dimensional (2D) tracking method, the 3D tracking results show that the diffusion coefficients of the molecules are three times larger on average. Using riSMT, we quantitatively analyzed the mass transfer of probe molecules in the mesoporous silica pore, including the fraction of adsorption versus diffusion, diffusion coefficients, and residence time. Large interparticle inhomogeneity was revealed and is expected to contribute to the peak broadening for separation application at the ensemble level. We further investigated the impact of electrostatic interaction on the mass transfer of molecules in the mesoporous silica pore and discovered that the primary effect is on the fraction rather than their diffusion rates of resorufin molecules undergoing diffusion.

Effect of bile duct resection on the prognosis of patients with hepatocellular carcinoma combined with extrahepatic bile duct tumor thrombus.

BACKGROUND: Surgical therapy is the most optimal treatment for hepatocellular carcinoma (HCC) combined with bile duct tumor thrombus (BDTT) patients. However, whether to perform bile duct resection (BDR) is still controversial. The purpose of this multicenter research is to compare the effect of BDR on the prognosis of extrahepatic BDTT patients. METHODS: We collected the data of 111 HCC patients combined with extrahepatic BDTT who underwent radical hepatectomy from June 1, 2004 to December 31, 2021. Those patients had either received hepatectomy with extrahepatic bile duct resection (BDR group) or hepatectomy without bile duct resection (NBDR group). Inverse probability of treatment weighting (IPTW) was used to reduce the potential bias between two groups and balance the influence of confounding factors in baseline data. Then compare the prognosis between the two groups of patients. Cox regression model was used for univariate and multivariate analysis to further determine the independent risk factors that influence the prognosis of HCC-BDTT patients. RESULTS: There were 38 patients in the BDR group and 73 patients in the NBDR group. Before and after IPTW, there were no statistical significance in OS, RFS and intraoperative median blood loss between the two groups (all P > 0.05). Before IPTW, the median postoperative hospital stay in the NBDR group was shorter (P = 0.046) and the grade of postoperative complications was lower than BDR group (P = 0.014). After IPTW, there was no difference in postoperative hospital stay between the two groups (P > 0.05). The complication grade in the NBDR group was still lower than that in the BDR group (P = 0.046). The univariate analysis showed that TNM stage and portal vein tumor thrombus (PVTT) were significantly correlated with OS (both P < 0.05). Preoperative AFP level, TNM stage and prognostic nutritional index (PNI) were significantly correlated with postoperative RFS (all P < 0.05). Multivariate analysis showed that tumor TNM stage was an independent risk factor for the OS rate (P = 0.014). TNM stage, PNI and AFP were independent predictors of RFS after radical hepatectomy (all P < 0.05). CONCLUSIONS: For HCC-BDTT patients, hepatocellular carcinoma resection combined with choledochotomy to remove the tumor thrombus may benefit more.

Longitudinal brain atlases of early developing cynomolgus macaques from birth to 48 months of age.

Longitudinal brain imaging atlases with densely sampled time-points and ancillary anatomical information are of fundamental importance in studying early developmental characteristics of human and non-human primate brains during infancy, which feature extremely dynamic imaging appearance, brain shape and size. However, for non-human primates, which are highly valuable animal models for understanding human brains, the existing brain atlases are mainly developed based on adults or adolescents, denoting a notable lack of temporally densely-sampled atlases covering the dynamic early brain development. To fill this critical gap, in this paper, we construct a comprehensive set of longitudinal brain atlases and associated tissue probability maps (gray matter, white matter, and cerebrospinal fluid) with totally 12 time-points from birth to 4 years of age (i.e., 1, 2, 3, 4, 5, 6, 9, 12, 18, 24, 36, and 48 months of age) based on 175 longitudinal structural MRI scans from 39 typically-developing cynomolgus macaques, by leveraging state-of-the-art computational techniques tailored for early developing brains. Furthermore, to facilitate region-based analysis using our atlases, we also provide two popular hierarchy parcellations, i.e., cortical hierarchy maps (6 levels) and subcortical hierarchy maps (6 levels), on our longitudinal macaque brain atlases. These early developing atlases, which have the densest time-points during infancy (to the best of our knowledge), will greatly facilitate the studies of macaque brain development.

Integration of radiogenomic features for early prediction of pathological complete response in patients with triple-negative breast cancer and identification of potential therapeutic targets.

BACKGROUND: We established a radiogenomic model to predict pathological complete response (pCR) in triple-negative breast cancer (TNBC) and explored the association between high-frequency mutations and drug resistance. METHODS: From April 2018 to September 2019, 112 patients who had received neoadjuvant chemotherapy were included. We randomly split the study population into training and validation sets (2:1 ratio). Contrast-enhanced magnetic resonance imaging scans were obtained at baseline and after two cycles of treatment and were used to extract quantitative radiomic features and to construct two radiomics-only models using a light gradient boosting machine. By incorporating the variant allele frequency features obtained from baseline core tissues, a radiogenomic model was constructed to predict pCR. Additionally, we explored the association between recurrent mutations and drug resistance. RESULTS: The two radiomics-only models showed similar performance with AUCs of 0.71 and 0.73 (p = 0.55). The radiogenomic model had a higher predictive ability than the radiomics-only model in the validation set (p = 0.04), with a corresponding AUC of 0.87 (0.73-0.91). Two highly frequent mutations were selected after comparing the mutation sites of pCR and non-pCR populations. The MED23 mutation p.P394H caused epirubicin resistance in vitro (p < 0.01). The expression levels of γ-H2A.X, p-ATM and p-CHK2 in MED23 p.P394H cells were significantly lower than those in wild type cells (p < 0.01). In the HR repair system, the GFP positivity rate of MED23 p.P394H cells was higher than that in wild-type cells (p < 0.01). CONCLUSIONS: The proposed radiogenomic model has the potential to accurately predict pCR in TNBC patients. Epirubicin resistance after MED23 p.P394H mutation might be affected by HR repair through regulation of the p-ATM-γ-H2A.X-p-CHK2 pathway.

DIKA-Nets: Domain-invariant knowledge-guided attention networks for brain skull stripping of early developing macaques.

As non-human primates, macaques have a close phylogenetic relationship to human beings and have been proven to be a valuable and widely used animal model in human neuroscience research. Accurate skull stripping (aka. brain extraction) of brain magnetic resonance imaging (MRI) is a crucial prerequisite in neuroimaging analysis of macaques. Most of the current skull stripping methods can achieve satisfactory results for human brains, but when applied to macaque brains, especially during early brain development, the results are often unsatisfactory. In fact, the early dynamic, regionally-heterogeneous development of macaque brains, accompanied by poor and age-related contrast between different anatomical structures, poses significant challenges for accurate skull stripping. To overcome these challenges, we propose a fully-automated framework to effectively fuse the age-specific intensity information and domain-invariant prior knowledge as important guiding information for robust skull stripping of developing macaques from 0 to 36 months of age. Specifically, we generate Signed Distance Map (SDM) and Center of Gravity Distance Map (CGDM) based on the intermediate segmentation results as guidance. Instead of using local convolution, we fuse all information using the Dual Self-Attention Module (DSAM), which can capture global spatial and channel-dependent information of feature maps. To extensively evaluate the performance, we adopt two relatively-large challenging MRI datasets from rhesus macaques and cynomolgus macaques, respectively, with a total of 361 scans from two different scanners with different imaging protocols. We perform cross-validation by using one dataset for training and the other one for testing. Our method outperforms five popular brain extraction tools and three deep-learning-based methods on cross-source MRI datasets without any transfer learning.

Single Molecule Investigation of Nanoconfinement Hydrophobicity in Heterogeneous Catalysis.

Nanoconfinement imposes physical constraints and chemical effects on reactivity in nanoporous catalyst systems. In the present study, we lay the groundwork for quantitative single-molecule measurements of the effects of chemical environment on heterogeneous catalysis in nanoconfinement. Choosing hydrophobicity as an exemplary chemical environmental factor, we compared a range of essential parameters for an oxidation reaction on platinum nanoparticles (NPs) confined in hydrophilic and hydrophobic nanopores. Single-molecule experimental measurements at the single particle level showed higher catalytic activity, stronger adsorption strength, and higher activation energy in hydrophobic nanopores than those in hydrophilic nanopores. Interestingly, different dissociation kinetic behaviors of the product molecules in the two types of nanopores were deduced from the single-molecule imaging data.

CircRNAFisher: a systematic computational approach for de novo circular RNA identification.

Circular RNAs (circRNAs) are emerging species of mRNA splicing products with largely unknown functions. Although several computational pipelines for circRNA identification have been developed, these methods strictly rely on uniquely mapped reads overlapping back-splice junctions (BSJs) and lack approaches to model the statistical significance of the identified circRNAs. Here, we reported a systematic computational approach to identify circRNAs by simultaneously utilizing BSJ overlapping reads and discordant BSJ spanning reads to identify circRNAs. Moreover, we developed a novel procedure to estimate the P-values of the identified circRNAs. A computational cross-validation and experimental validations demonstrated that our method performed favorably compared to existing circRNA detection tools. We created a standalone tool, CircRNAFisher, to implement the method, which might be valuable to computational and experimental scientists studying circRNAs.

Alteration of tumor suppressor BMP5 in sporadic colorectal cancer: a genomic and transcriptomic profiling based study.

BACKGROUND: Although the genetic spectrum of human colorectal cancer (CRC) is mainly characterized by APC, KRAS and TP53 mutations, driver genes in tumor initiation have not been conclusively demonstrated. In this study, we aimed to identify novel markers for CRC. METHODS: We performed exome analysis of sporadic colorectal cancer (sCRC) coding regions to screen loss of function (LoF) mutation genes, and carried out systems-level approaches to confirm top rank gene in this study. RESULTS: We identified loss of BMP5 is an early event in CRC. Deep sequencing identified BMP5 was mutated in 7.7% (8/104) of sCRC samples, with 37.5% truncating mutation frequency. Notably, BMP5 negative expression and its prognostic value is uniquely significant in sCRC but not in other tumor types. Furthermore, BMP5 expression was positively correlated with E-cadherin in CRC patients and its dysregulation play a vital role in epithelial-mesenchymal transition (EMT), thus triggering tumor initiation and development. RNA sequencing identified, independent of BMP/Smads pathway, BMP5 signaled though Jak-Stat pathways to inhibit the activation of oncogene EPSTI1. CONCLUSIONS: Our result support a novel concept that the importance of BMP5 in sCRC. The tumor suppressor role of BMP5 highlights its crucial role in CRC initiation and development.

Sub-4 nm PtZn Intermetallic Nanoparticles for Enhanced Mass and Specific Activities in Catalytic Electrooxidation Reaction.

Atomically ordered intermetallic nanoparticles (iNPs) have sparked considerable interest in fuel cell applications by virtue of their exceptional electronic and structural properties. However, the synthesis of small iNPs in a controllable manner remains a formidable challenge because of the high temperature generally required in the formation of intermetallic phases. Here we report a general method for the synthesis of PtZn iNPs (3.2 ± 0.4 nm) on multiwalled carbon nanotubes (MWNT) via a facile and capping agent free strategy using a sacrificial mesoporous silica (mSiO2) shell. The as-prepared PtZn iNPs exhibited ca. 10 times higher mass activity in both acidic and basic solution toward the methanol oxidation reaction (MOR) compared to larger PtZn iNPs synthesized on MWNT without the mSiO2 shell. Density functional theory (DFT) calculations predict that PtZn systems go through a "non-CO" pathway for MOR because of the stabilization of the OH* intermediate by Zn atoms, while a pure Pt system forms highly stable COH* and CO* intermediates, leading to catalyst deactivation. Experimental studies on the origin of the backward oxidation peak of MOR coincide well with DFT predictions. Moreover, the calculations demonstrate that MOR on smaller PtZn iNPs is energetically more favorable than larger iNPs, due to their high density of corner sites and lower-lying energetic pathway. Therefore, smaller PtZn iNPs not only increase the number but also enhance the activity of the active sites in MOR compared with larger ones. This work opens a new avenue for the synthesis of small iNPs with more undercoordinated and enhanced active sites for fuel cell applications.

Metal-Organic-Framework-Derived Carbons: Applications as Solid-Base Catalyst and Support for Pd Nanoparticles in Tandem Catalysis.

The facile pyrolysis of a bipyridyl metal-organic framework, MOF-253, produces N-doped porous carbons (Cz-MOF-253), which exhibit excellent catalytic activity in the Knoevenagel condensation reaction and outperform other nitrogen-containing MOF-derived carbons. More importantly, by virtue of their high Lewis basicity and porous nature, Cz-MOF-253-supported Pd nanoparticles (Pd/Cz-MOF-253-800) show excellent performance in a one-pot sequential Knoevenagel condensation-hydrogenation reaction.

Silica-Encapsulated Pt-Sn Intermetallic Nanoparticles: A Robust Catalytic Platform for Parahydrogen-Induced Polarization of Gases and Liquids.

Recently, a facile method for the synthesis of size-monodisperse Pt, Pt3 Sn, and PtSn intermetallic nanoparticles (iNPs) that are confined within a thermally robust mesoporous silica (mSiO2 ) shell was introduced. These nanomaterials offer improved selectivity, activity, and stability for large-scale catalytic applications. Here we present the first study of parahydrogen-induced polarization NMR on these Pt-Sn catalysts. A 3000-fold increase in the pairwise selectivity, relative to the monometallic Pt, was observed using the PtSn@mSiO2 catalyst. The results are explained by the elimination of the three-fold Pt sites on the Pt(111) surface. Furthermore, Pt-Sn iNPs are shown to be a robust catalytic platform for parahydrogen-induced polarization for in vivo magnetic resonance imaging.

Cooperative Multifunctional Catalysts for Nitrone Synthesis: Platinum Nanoclusters in Amine-Functionalized Metal-Organic Frameworks.

Nitrones are key intermediates in organic synthesis and the pharmaceutical industry. The heterogeneous synthesis of nitrones with multifunctional catalysts is extremely attractive but rarely explored. Herein, we report ultrasmall platinum nanoclusters (PtNCs) encapsulated in amine-functionalized Zr metal-organic framework (MOF), UiO-66-NH2 (Pt@UiO-66-NH2 ) as a multifunctional catalyst in the one-pot tandem synthesis of nitrones. By virtue of the cooperative interplay among the selective hydrogenation activity provided by the ultrasmall PtNCs and Lewis acidity/basicity/nanoconfinement endowed by UiO-66-NH2 , Pt@UiO-66-NH2 exhibits remarkable activity and selectivity, in comparison to Pt/carbon, Pt@UiO-66, and Pd@UiO-66-NH2 . Pt@UiO-66-NH2 also outperforms Pt nanoparticles supported on the external surface of the same MOF (Pt/UiO-66-NH2 ). To our knowledge, this work demonstrates the first examples of one-pot synthesis of nitrones using recyclable multifunctional heterogeneous catalysts.

In-Office Hyaluronate Injection Laryngoplasty as Palliative Treatment for Unilateral Vocal Fold Paralysis.

BACKGROUND: Voice and swallowing impairments can impact on both quality of life and survival. Unilateral vocal fold paralysis (UVFP) as a result of distant metastasis can cause breathy voice and aspiration. The purpose of this study is to develop and evaluate a less invasive and effective alternative therapy for UVFP. METHODS: This was a retrospective review of prospectively enrolled patients at a tertiary referral center in Taiwan. Among a cohort of 177 patients who received intracordal hyaluronate injections, 2 had UVFP from distant metastasis and met the inclusion criteria. Vocal cord motion was recorded by videostroboscopy, and the normalized glottal gap area was measured. Voice quality, defined by speech language pathologists, and swallowing status were compared, and immediate complications after the injection were investigated. RESULTS: Two patients with UVFP with M1 lesions (both lung) accepted the procedure. The glottal gap area was significantly improved 1 month after in-office hyaluronate injection. Voice quality and aspiration were also improved. No immediate complications were noted in either patient. CONCLUSIONS: In-office intracordal hyaluronate injection is a safe and effective treatment for UVFP, providing a palliative method to help maintain the patient's voice and quality of life.

Geometry-assisted three-dimensional superlocalization imaging of single-molecule catalysis on modular multilayer nanocatalysts.

To establish the structure-catalytic property relationships of heterogeneous catalysts, a detailed characterization of the three-dimensional (3D) distribution of active sites on a single catalyst is essential. Single-particle catalysis of a modular multilayer catalytic platform that consists of a solid silica core, a mesoporous silica shell, and uniformly distributed Pt nanoparticles sandwiched in between these layers is presented. The first 3D high-resolution super-localization imaging of single fluorescent molecules produced at active sites on the core-shell model nanocatalysts is demonstrated. The 3D mapping is aided by the well-defined geometry and a correlation study in scanning electron microscopy and total internal reflection fluorescence and scattering microscopy. This approach can be generalized to study other nano- and mesoscale structures.

A Novel Preparation Method of Composite Bolted T-Joint with High Bending Performance Based on the Prepreg-RTM Co-Curing Process.

A co-curing resin system consisting of 9368 epoxy resin for prepreg and 6808 epoxy resin for resin transfer molding (RTM) was developed. A corresponding preparation method for a novel polymer composite bolted T-joint with internal skeleton and external skin was proposed based on the prepreg-RTM co-curing process, and novel T-joints were fabricated. A series of conventional configuration T-joints based on the RTM process and T-joints made of 2A12 aluminum alloy were prepared simultaneously. Bending performances were studied on these T-joints experimentally. The results indicate that 9368 epoxy resin and 6808 epoxy resin exhibit good compatibility in rheological and thermophysical properties. The novel T-joints prepared with the prepreg-RTM co-curing process show no obvious fiber local winding or resin-rich regions inside, and the interface quality between the internal skeleton and the external skin is excellent. The main failure modes of the novel T-joint under bending load include the separation of the skin and skeleton and the fracture along the thickness on the base panel; the skeleton carries the main bending load, but there is still load transfer between external skin and internal skeleton through their interface. The internal damages of the novel T-joint are highly consistent with surface damages observed visually, facilitating the detection and timely discovery of damages. The initial stiffness, damage initiation load, and ultimate load of the novel T-joint are 1.65 times, 5.89 times, and 3.45 times that of the conventional T-joint, respectively. When considering the influence of the density, the relative initial stiffness and relative ultimate load of the novel T-joint are 1.44 times and 2.07 times that of the aluminum alloy T-joint, respectively.

PETS-Nets: Joint Pose Estimation and Tissue Segmentation of Fetal Brains Using Anatomy-Guided Networks.

Fetal Magnetic Resonance Imaging (MRI) is challenged by fetal movements and maternal breathing. Although fast MRI sequences allow artifact free acquisition of individual 2D slices, motion frequently occurs in the acquisition of spatially adjacent slices. Motion correction for each slice is thus critical for the reconstruction of 3D fetal brain MRI. In this paper, we propose a novel multi-task learning framework that adopts a coarse-to-fine strategy to jointly learn the pose estimation parameters for motion correction and tissue segmentation map of each slice in fetal MRI. Particularly, we design a regression-based segmentation loss as a deep supervision to learn anatomically more meaningful features for pose estimation and segmentation. In the coarse stage, a U-Net-like network learns the features shared for both tasks. In the refinement stage, to fully utilize the anatomical information, signed distance maps constructed from the coarse segmentation are introduced to guide the feature learning for both tasks. Finally, iterative incorporation of the signed distance maps further improves the performance of both regression and segmentation progressively. Experimental results of cross-validation across two different fetal datasets acquired with different scanners and imaging protocols demonstrate the effectiveness of the proposed method in reducing the pose estimation error and obtaining superior tissue segmentation results simultaneously, compared with state-of-the-art methods.

Quantification of 3-Dimensional Confluence-Atrial Morphology in Supracardiac Total Anomalous Pulmonary Venous Connection.

Background: Pulmonary vein stenosis (PVS) continues to be a major complication after surgical repair of total anomalous pulmonary venous connection (TAPVC). Recent studies suggest that the morphology of pulmonary venous confluence and the left atrium (LA) is associated with PVS. However, there are limited data on the prognostic value of integrating quantitative confluence-atrial morphology into risk stratification. Objectives: This study sought to evaluate the prognostic impact of novel imaging metrics derived from 3-dimensional (3D) computed tomography angiography (CTA) modeling on postsurgical PVS (PPVS) in the supracardiac TAPVC (sTAPVC) setting. Methods: Patients undergoing sTAPVC repair in 2017 to 2022 from 3 centers were retrospectively reviewed. Study investigators developed 3D CTA modeled geometric features to quantify confluence-atrial morphology that were analyzed with regard to PPVS. Results: Of the 162 patients (median age 61 days; 55% having preoperative pulmonary venous obstruction [prePVO]) included, 47 (29%) with PPVS at a median of 1.5 months ([quartile 1-quartile 3: 1.5-3.0 months]). In the univariable analysis, the indexed total volume of the LA and confluence (iTVLC) and the ratio of the corresponding confluence length to the mean distance between the LA and confluence (CCL/mDBLC ratio) were significantly associated with PPVS. In a multivariable model adjusting for prePVO and age, the iTVLC and CCL/mDBLC ratio independently predicted PPVS (HR: 1.15; 95% CI: 1.06-1.25; and HR: 1.20; 95% CI: 1.08-1.35, respectively, all P < 0.01). Specifically, an iTVLC ≥20 cm3/m2 and a CCL/mDBLC ratio ≥7.7 were significantly associated with a reduced risk of PPVS. Conclusions: Quantification of 3D confluence-atrial morphology appears to offer a deeper and better metric to predict PPVS in patients with sTAPVC.

Genetic interactions reveal distinct biological and therapeutic implications in breast cancer.

Co-occurrence and mutual exclusivity of genomic alterations may reflect the existence of genetic interactions, potentially shaping distinct biological phenotypes and impacting therapeutic response in breast cancer. However, our understanding of them remains limited. Herein, we investigate a large-scale multi-omics cohort (n = 873) and a real-world clinical sequencing cohort (n = 4,405) including several clinical trials with detailed treatment outcomes and perform functional validation in patient-derived organoids, tumor fragments, and in vivo models. Through this comprehensive approach, we construct a network comprising co-alterations and mutually exclusive events and characterize their therapeutic potential and underlying biological basis. Notably, we identify associations between TP53mut-AURKAamp and endocrine therapy resistance, germline BRCA1mut-MYCamp and improved sensitivity to PARP inhibitors, and TP53mut-MYBamp and immunotherapy resistance. Furthermore, we reveal that precision treatment strategies informed by co-alterations hold promise to improve patient outcomes. Our study highlights the significance of genetic interactions in guiding genome-informed treatment decisions beyond single driver alterations.

The clinical application of 68Ga-PSMA PET/CT and regulating mechanism of PSMA expression in patients with brain metastases of lung cancer.

Brain metastases (BMs) of lung cancer are common malignant intracranial tumours associated with severe neurological symptoms and an abysmal prognosis. Prostate-specific membrane antigen (PSMA) has been reported to express significantly in a variety of solid tumours. However, the clinical applications of 68Ga-PSMA PET/CT and the mechanism of PSMA expression in patients with BMs of lung cancer have rarely been reported. Experiments with 68Ga-PSMA PET/CT and immunohistochemical staining were conducted to evaluate the expression of PSMA from seven patients with BMs of lung cancer who accepted surgical treatment in Fudan University Shanghai Cancer Center between October 2020 and October 2021. The mechanism of PSMA expression in BMs of lung cancer was explored by using single-cell RNA sequencing. The median maximum standardized uptake value (SUVmax) in BMs was higher than that in primary lung cancer (8.6 ± 2.8 vs. 3.6 ± 1.3, P < 0.01). The mean SUVmax in BMs was 1.76-fold higher than that in the liver, which indicated the potential of PSMA radioligand therapy (PSMA-RLT) for BMs. BMs showed intense PSMA staining, while normal lung tissue had no PSMA staining and there was only faint primary lung cancer staining by immunohistochemistry (IHC). Single-cell RNA sequencing (scRNA-seq) analysis found that PSMA was mainly expressed in oligodendrocytes of BMs, whereas it was expressed at lower levels in solid cells of lung cancer. PSMA expression in oligodendrocytes might be regulated by the factors ATF3 and NR4A1, which were associated with ER stress.