Hepatic perivascular epithelioid cell tumor resembling hepatic adenoma and hepatocellular carcinoma on preoperative imaging: a case report.

Perivascular epithelioid cell tumor (PEComa), an uncommon mesenchymal neoplasm, arises from specialized perivascular epithelioid cells exhibiting distinct features of smooth muscle and melanocytic differentiation with unpredictable behavior. PEComa tends to occur more commonly in the uterus and kidneys; its occurrence in the liver is exceedingly rare. We presented a case of a 29-year-old woman with hepatic PEComa and evaluated the tumor with MRI, integrated 18F-fluorodeoxyglucose (FDG), and 68Ga-fibroblast activation protein inhibitor (FAPI) PET/CT scans at presentation. The patient had a history of intermittent utilization of oral contraceptive drugs for several years. An abdominal ultrasound in a physical examination from an outside institution revealed a mass in the liver. A contrast-enhanced abdominal MRI revealed restricted diffusion on diffusion-weighted imaging (DWI) and rapid contrast enhancement and washout patterns in the hepatic lesion, suggesting hepatic adenoma (HA) or hepatocellular carcinoma (HCC). Further assessment was carried out using 18F-FDG and 68Ga-FAPI PET/CT scans. The hepatic lesion was non-FDG avid, whereas increased tracer uptake was observed on the 68Ga-FAPI PET/CT. Subsequently, laparoscopic partial resection of liver segment V was performed. Immunohistochemical analyses demonstrated positive staining for HMB45, Melan-A, and SMA while showing negative results for AFP, glypican-3, hepatocyte, and arginase-1. The results were indicative of a hepatic PEComa diagnosis based on these findings. We also review the current literature on the clinical characteristics, pathological features, and challenges in the diagnosis of hepatic PEComa.

The remodeling of metabolic brain pattern in patients with extracranial diffuse large B-cell lymphoma.

BACKGROUND: Owing to the advances in diagnosis and therapy, survival or remission rates for lymphoma have improved prominently. Apart from the lymphoma- and chemotherapy-related somatic symptom burden, increasing attention has been drawn to the health-related quality of life. The application of 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) has been routinely recommended for the staging and response assessment of FDG-avid lymphoma. However, up till now, only a few researches have investigated the brain metabolic impairments in patients with pre-treatment lymphoma. The determination of the lymphoma-related metabolic brain pattern would facilitate exploring the tailored therapeutic regimen to alleviate not only the physiological, but also the psychological symptoms. In this retrospective study, we aimed to establish the diffuse large B-cell lymphoma-related pattern (DLBCLRP) of metabolic brain network and investigate the correlations between DLBCLRP and several indexes of the staging and response assessment. RESULTS: The established DLBCLRP was characterized by the increased metabolic activity in bilateral cerebellum, brainstem, thalamus, striatum, hippocampus, amygdala, parahippocampal gyrus and right middle temporal gyrus and by the decreased metabolic activity in bilateral occipital lobe, parietal lobe, anterior cingulate gyrus, midcingulate cortex and medial frontal gyrus. Significant difference in the baseline expression of DLBCLRP was found among complete metabolic response (CMR), partial metabolic response (PMR) and progressive metabolic disease (PMD) groups (P < 0.01). DLBCLRP expressions were also significantly or tended to be positively correlated with international prognostic index (IPI) (rs = 0.306, P < 0.05), lg(total metabolic tumor volume, TMTV) (r = 0.298, P < 0.05) and lg(total lesion glycolysis, TLG) (r = 0.233, P = 0.064). Though no significant correlation of DLBCLRP expression was found with Ann Arbor staging or tumor SUVmax (P > 0.05), the post-treatment declines of DLBCLRP expression were significantly positively correlated with Ann Arbor staging (rs = 0.284, P < 0.05) and IPI (rs = 0.297, P < 0.05). CONCLUSIONS: The proposed DLBCLRP would lay the foundation for further investigating the cerebral dysfunction related to DLBCL itself and/or treatments. Besides, the expression of DLBCLRP was associated with the tumor burden of lymphoma, implying a potential biomarker for prognosis.

Prognostic Value of SSTR-derived Volumetric Parameters from a Hybrid Standardized Uptake Value Thresholding Method in Patients with 68Ga-DOTATATE-avid Stage IV Neuroendocrine Neoplasms: A preliminary study.

INTRODUCTION: The ability of PET/CT imaging to delineate neuroendocrine neoplasms (NENs) and predict prognosis in affected patients is often compromised by substantial uptake heterogeneity. We hereby proposed a hybrid standardized uptake value (SUV) thresholding algorithm to extract volumetric parameters from somatostatin receptor (SSTR) PET/CT imaging, and investigate their prognostic performance in patients with 68Ga-DOTATATE-avid stage IV NENs. METHODS: For 38 retrospectively enrolled patients, we used either fixed SUV thresholding of normal liver parenchyma (method A), 41% of the SUVmax for each lesion (method B), or a hybrid method (method A for liver metastases; fixed SUV threshold of normal bone for bone metastases; method B for primary tumors and other metastases) to quantify the whole-body SSTR-expressing tumor volume (SRETVwb) and total lesion SSTR expression (TLSREwb). Patient survival was also recorded and analyzed. RESULTS: PET/CT images revealed heterogeneous uptake of 68Ga-DOTATATE at primary and metastatic sites. Progression-free (PFS) and overall survival (OS) were negatively correlated with the extent of liver or bone metastases (P < 0.05), but not significantly correlated with tumor grade or 18F-FDG PET/CT positivity. By the hybrid method, PFS was significantly shorter in patients with high SRETVwb, and OS was significantly shorter in those with high SRETVwb and TLSREwb (P < 0.05). However, when derived from method A or method B, neither SRETVwb nor TLSREwb could predict patient outcomes. CONCLUSION: Compared with other methods used in 68Ga-DOTATATE-avid stage IV NENs, our hybrid SUV thresholding method demonstrated robustness, with greater precision, reliability, and prognostic power.

Inhibition of Poly(ADP-ribose) Polymerase Sensitizes [177Lu]Lu-DOTAGA.(SA.FAPi)2-Mediated Radiotherapy in Triple-Negative Breast Cancer.

Fibroblast activation protein (FAP) is highly expressed in many tumor types and constitutes a promising target for tumor-specific delivery of therapeutic radionuclides. [177Lu]Lu-DOTAGA.(SA.FAPi)2 is a novel radiopharmaceutical based on a novel bidentate inhibitor of FAP that is excreted more slowly than its monomeric counterparts. Still, the efficacy of radiotherapy is mitigated by cascades of DNA damage repair signaling in tumor cells including those via Poly(ADP-ribose) polymerase (PARP). We hereby aimed to evaluate the efficacy of [177Lu]Lu-DOTAGA.(SA.FAPi)2 in combination with a PARP inhibitor, Olaparib, in the 4T1 murine triple negative breast cancer (TNBC) model. The therapeutic efficacy was visualized using 18F-FDG and [68Ga]Ga-FAPI-04 positron emission imaging/computer tomography (PET/CT). Our results demonstrated that Olaparib suppressed BALB/3T3 fibroblasts in vitro and sensitized the efficacy of [177Lu]Lu-DOTAGA.(SA.FAPi)2 in mice bearing 4T1 tumors via enhancement of DNA damage. Treatment-associated toxicity was tolerable with only mild leukopenia. Therefore, the combination of [177Lu]Lu-DOTAGA.(SA.FAPi)2 and Olaparib is a feasible treatment against TNBC.

Age-matched control or age-specific template, which is essential for voxel-wise analysis of cerebral metabolism abnormality in pediatric patients with epilepsy?

The aim of this study was to explore the influences of age-matched control and/or age-specific template on voxel-wise analysis of brain 18 F-fluorodeoxyglucose positron emission tomography (18 F-FDG PET) data in pediatric epilepsy patients. We, retrospectively, included 538 pediatric (196 females; age range of 12 months to 18 years) and 35 adult subjects (18 females; age range of 20-50 years) without any cerebral pathology as pediatric and adult control group, respectively, as well as 109 pediatric patients with drug-resistant epilepsy (38 females; age range of 13 months to 18 years) as epilepsy group. Statistical parametric mapping (SPM) analysis for 18 F-FDG PET data of each epilepsy patients was performed in four types of procedures, by using age-matched controls with age-specific template, age-matched controls with adult template, adult controls with age-specific template or adult controls with adult template. The numbers of brain regions affected by artifacts among these four types of SPM analysis procedures were further compared. Any template being adopted, the artifacts were significantly less in SPM analysis procedures using age-matched controls than those using adult controls in each age range (p < .001 in each comparison), except in the age range of 15-18 (p > .05 in each comparison). No significant difference was found in artifacts, when compared procedures using the identical control group with different templates (p = 1.000 in each comparison). In conclusion, the age stratification for age-matched control should be divided as many layers as possible for the SPM analysis of brain 18 F-FDG PET images, especially in pediatric patients ≤14-year-old, while age-specific template is not mandatory.

ISA-Net: Improved spatial attention network for PET-CT tumor segmentation.

BACKGROUND AND OBJECTIVE: Achieving accurate and automated tumor segmentation plays an important role in both clinical practice and radiomics research. Segmentation in medicine is now often performed manually by experts, which is a laborious, expensive and error-prone task. Manual annotation relies heavily on the experience and knowledge of these experts. In addition, there is much intra- and interobserver variation. Therefore, it is of great significance to develop a method that can automatically segment tumor target regions. METHODS: In this paper, we propose a deep learning segmentation method based on multimodal positron emission tomography-computed tomography (PET-CT), which combines the high sensitivity of PET and the precise anatomical information of CT. We design an improved spatial attention network(ISA-Net) to increase the accuracy of PET or CT in detecting tumors, which uses multi-scale convolution operation to extract feature information and can highlight the tumor region location information and suppress the non-tumor region location information. In addition, our network uses dual-channel inputs in the coding stage and fuses them in the decoding stage, which can take advantage of the differences and complementarities between PET and CT. RESULTS: We validated the proposed ISA-Net method on two clinical datasets, a soft tissue sarcoma(STS) and a head and neck tumor(HECKTOR) dataset, and compared with other attention methods for tumor segmentation. The DSC score of 0.8378 on STS dataset and 0.8076 on HECKTOR dataset show that ISA-Net method achieves better segmentation performance and has better generalization. CONCLUSIONS: The method proposed in this paper is based on multi-modal medical image tumor segmentation, which can effectively utilize the difference and complementarity of different modes. The method can also be applied to other multi-modal data or single-modal data by proper adjustment.

Lateralization of the crossed cerebellar diaschisis-associated metabolic connectivities in cortico-ponto-cerebellar and cortico-rubral pathways.

This study aimed to explore the glucose metabolic profile of extrapyramidal system in patients with crossed cerebellar diaschisis (CCD). Furthermore, the metabolic connectivities in cortico-ponto-cerebellar and cortico-rubral pathways associated with CCD were also investigated. A total of 130 CCD positive (CCD+) and 424 CCD negative (CCD-) patients with unilateral cerebral hemisphere hypometabolism on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) were enrolled. Besides, the control group consisted of 56 subjects without any brain structural and metabolic abnormalities. Apart from the "autocorrelation", metabolic connectivity pattern of right or left affected cerebellar hemisphere involved unilateral (left or right, respectively) caudate, pallidum, putamen, thalamus and red nucleus, in CCD+ patients with left or right supratentorial lesions, respectively (Puncorrected < 0.001, cluster size > 200). CCD+ group had significantly lower asymmetry index (AI) in cortico-ponto-cerebellar pathway (including ipsilateral cerebral white matter, ipsilateral pons, contralateral cerebellum white matter and contralateral cerebellum exterior cortex) and cortico-rubral pathway (including ipsilateral caudate, thalamus proper, pallidum, putamen, ventral diencephalon and red nucleus) than those of both CCD- and control groups (all P < 0.05). AI in contralateral cerebellum exterior cortex was significantly positively correlated with that in ipsilateral caudate, putamen, pallidum, thalamus proper, ventral diencephalon, red nucleus and pons among CCD+ group (all P < 0.01), but only with that in ipsilateral caudate and putamen among CCD- group (both P < 0.001). These results provide additional insight into the involvement of both cortico-ponto-cerebellar and cortico-rubral pathways in the presence of CCD, underlining the need for further investigation about the role of their aberrant metabolic connectivities in the associated symptoms of CCD.

Eliminating CT radiation for clinical PET examination using deep learning.

Clinical PET/CT examinations rely on CT modality for anatomical localization and attenuation correction of the PET data. However, the use of CT significantly increases the risk of ionizing radiation exposure for patients. We propose a deep learning framework to learn the relationship mapping between attenuation corrected (AC) PET and non-attenuation corrected (NAC) PET images to estimate PET attenuation maps and generate pseudo-CT images for medical observation. In this study, 5760, 1608 and 1351 pairs of transverse PET-CT slices were used as the training, validation, and testing sets, respectively, to implement the proposed framework. A pix2pix model was adopted to predict AC PET images from NAC PET images, which allowed the calculation of PET attenuation maps (µ-maps). The same model was then applied to generate realistic CT images from the calculated µ-maps. The quality of predicted AC PET and CT was assessed using normalized root mean square error (NRMSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) and Pearson correlation coefficient (PCC). Relative to true AC PET, the synthetic AC PET achieved superior quantitative performances with 2.20 ± 1.17% NRMSE, 34.03 ± 4.73 dB PSNR, 97.90 ± 1.22% SSIM and 98.45 ± 1.31% PCC. The synthetic CT and synthetic AC PET images were deemed acceptable by radiologists who rated the images, as they provided sufficient anatomical and functional information, respectively. This work demonstrates that the proposed deep learning framework is a promising method in clinical applications, such as radiotherapy and low-dose imaging.

Voxel-based analysis of the metabolic asymmetrical and network patterns in hypermetabolism-associated crossed cerebellar diaschisis.

Crossed cerebellar diaschisis (CCD) has been widely investigated in patients with supratentorial hypometabolism, however, the available evidence about the metabolic feature of CCD in patients with contralateral supratentorial hypermetabolism is lacking. This study aimed to assess the metabolic asymmetrical profile, network pattern and predisposing factors for the hypermetabolism-associated CCD, by using voxel-based asymmetry index (AI) and brain network analyses. Seventy CCD positive (CCD+) and 99 CCD negative (CCD-) patients with unilateral supratentorial hypermetabolism were introduced. Among different brain regions with AImax or AImin, striatum & thalamus was accompanied by the highest positive rate of CCD (85.7% or 70.1%, respectively). CCD+ group had significantly greater AImax (median [IQR], 0.62 [0.44-0.84] vs. 0.47 [0.35-0.61]), supratentorial hypermetabolic volume (1183.5 [399.3-3026.8] vs. 386.0 [152.0-1193.0]) and hypometabolic volume (37796.5 [24741.8-53278.0] vs. 3337.0 [1020.0-17193.0]), and lower AImin (-0.85 [-1.05--0.73] vs. -0.49 [-0.68--0.35]) compared with CCD- group (all P < 0.001). Logistic regression analysis manifested that patients with AImin located at striatum & thalamus were 16.4 times more likely to present CCD than those at frontal lobe (OR = 16.393; 95% CI, 4.463-60.207; P < 0.001), and the occurrence of CCD was also associated with AImax (OR = 49.594; 95% CI, 5.519-445.653; P < 0.001) and AImin (OR = 3.133 × 10-4, 95% CI, 1.693 × 10-5-5.799 × 10-3, P < 0.001). Brain network analysis indicated that the relative hypermetabolism in the contralateral supplementary motor cortex (SMC) and precuneus gyrus were constant in the CCD related patterns. These results demonstrated that the greater AImax, lower AImin and AImin located at striatum & thalamus should be predisposing factors for CCD in patients with unilateral supratentorial hypermetabolism. Relative increased activities in the contralateral SMC and precuneus gyrus might be attributed to a compensatory mechanism for the abnormal brain network related to CCD.

Time point-independent tumor positivity of 68Ga-PSMA-PET/CT pre- and post-biopsy in high-risk prostate cancer.

OBJECTIVE: Prostate-specific membrane antigen (PSMA)-PET/CT imaging has gained increasing clinical importance for the detection and staging of high-risk primary prostate cancer (PCa). However, it is unclear whether the routine practice of prostate biopsy obscures the image finding of PSMA-PET/CT. This study aimed to compare the tumor positivity rate of PSMA-PET/CT performed pre- (PSMA-PET/CTpre) and post-biopsy (PSMA-PET/CTpost) in high-risk PCa patients. PATIENTS AND METHODS: We matched 58 PSMA-PET/CTpost with 58 PSMA-PET/CTpre studies for primary detection of high-risk PCa according to clinical characteristics. Three subgroups of PSMA-PET/CTpost were defined by the intervals after biopsy (≤ 1 week, 1 ~ 2 weeks, and 2 ~ 5 weeks). Tumor positivity rates were determined, and SUVmax of primary tumors were compared separately for the two main groups and the related subgroups. Malignant prostate tissues from 20 of these patients were examined by immunohistochemical analysis of PSMA. In addition, the values of PSMA-PET/CTpre and PSMA-PET/CTpost in assessing seminal vesicle invasion (SVI) were evaluated in patients who underwent radical prostatectomy. RESULTS: All the primary tumors were positive on PSMA-PET/CTpost and PSMA-PET/CTpre imaging, resulting in a patient-based positivity rates of 100% (58/58) in both groups. All examined IHC results (20/20) confirmed the high-level expression of PSMA. SUVmax of primary tumors did not differ between the two main groups (16.1, IQR 9.8-26.6 vs. 16.5, IQR 11.0-26.7, p > 0.05). Subgroup analysis of PSMA-PET/CTpost (≤ 1 week, 1 ~ 2 weeks, and 2 ~ 5 weeks) also showed no significant difference in tumor SUVmax (15.8, IQR 9.5-22.2; 17.8, IQR 9.8-29.2; and 15.4, IQR 10.1-30.3. p > 0.05). PSMA-PET/CTpost and PSMA-PET/CTpre exhibited similar value in SVI detection as well. CONCLUSIONS: The tumor positivity rate was consistently high for PSMA-PET/CT pre- and post-biopsy. A prior biopsy does not seem to affect the tumor positivity rate of PSMA-PET/CT in high-risk PCa.

Positive FAPI PET/CT in a Bilateral Mammary Angiosarcoma Patient With Less Impressive FDG PET/CT Images.

ABSTRACT: Bilateral primary angiosarcoma of the breast is an extremely rare disease. We describe a case with bilateral angiosarcoma of the breast well visualized on 68Ga-FAPI PET/CT in a 30-year-old woman with a history of right breast-conserving surgery. However, the lesions are less impressive on 18F-FDG PET/CT. No additional findings including lymph node and distant metastases were noted. The patient underwent bilateral mastectomy, and histopathology revealed well-differentiated angiosarcoma that involved bilateral breast parenchyma and the left nipple. Our case illustrates that 68Ga-FAPI PET/CT can be more sensitive in detecting well-differentiated angiosarcoma of the breast.

A Novel Approach Using FDG-PET/CT-Based Radiomics to Assess Tumor Immune Phenotypes in Patients With Non-Small Cell Lung Cancer.

PURPOSE: Tumor microenvironment immune types (TMITs) are closely related to the efficacy of immunotherapy. We aimed to assess the predictive ability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT)-based radiomics of TMITs in treatment-naive patients with non-small cell lung cancer (NSCLC). METHODS: A retrospective analysis was performed in 103 patients with NSCLC who underwent 18F-FDG PET/CT scans. The patients were randomly assigned into a training set (n = 71) and a validation set (n = 32). Tumor specimens were analyzed by immunohistochemistry for the expression of programmed death-ligand 1 (PD-L1), programmed death-1 (PD-1), and CD8+ tumor-infiltrating lymphocytes (TILs) and categorized into four TMITs according to their expression of PD-L1 and CD8+ TILs. LIFEx package was used to extract radiomic features. The optimal features were selected using the least absolute shrinkage and selection operator (LASSO) algorithm, and a radiomics signature score (rad-score) was developed. We constructed a combined model based on the clinical variables and radiomics signature and compared the predictive performance of models using receiver operating characteristic (ROC) curves. RESULTS: Four radiomic features (GLRLM_LRHGE, GLZLM_SZE, SUVmax, NGLDM_Contrast) were selected to build the rad-score. The rad-score showed a significant ability to discriminate between TMITs in both sets (p < 0.001, p < 0.019), with an area under the ROC curve (AUC) of 0.800 [95% CI (0.688-0.885)] in the training set and that of 0.794 [95% CI (0.615-0.916)] in the validation set, while the AUC values of clinical variables were 0.738 and 0.699, respectively. When clinical variables and radiomics signature were combined, the complex model showed better performance in predicting TMIT-I tumors, with the AUC values increased to 0.838 [95% CI (0.731-0.914)] in the training set and 0.811 [95% CI (0.634-0.927)] in the validation set. CONCLUSION: The FDG-PET/CT-based radiomic features showed good performance in predicting TMIT-I tumors in NSCLC, providing a promising approach for the choice of immunotherapy in a clinical setting.

Comparison of 18F-FDG, 68Ga-FAPI, and 68Ga-DOTATATE PET/CT in a Patient With Pancreatic Neuroendocrine Tumor.

ABSTRACT: We present image findings of 18F-FDG, 68Ga-FAPI, and 68Ga-DOTATATE PET/CT in a 35-year-old woman with multiple metastases of pancreatic neuroendocrine tumor. The images of PET/CTs using 3 different tracers all showed multiple foci of increased activities in the liver and pancreas body, in which 68Ga-FAPI PET/CT displayed the highest tumor-to-liver ratios. However, 68Ga-DOTATATE PET/CT detected more small metastatic lymph node and bone metastases, which were missed by both FDG and FAPI PET/CT.

Correlation Between Dual-Time-Point FDG PET and Tumor Microenvironment Immune Types in Non-Small Cell Lung Cancer.

PURPOSE: Dual-time-point 18F-fluorodeoxyglucose positron emission tomography (DTP 18F-FDG PET), which reflects the dynamics of tumor glucose metabolism, may also provide a novel approach to the characterization of both cancer cells and immune cells within the tumor immune microenvironment (TIME). We investigated the correlations between the metabolic parameters (MPs) of DTP 18F-FDG PET images and the tumor microenvironment immune types (TMITs) in patients with non-small cell lung cancer (NSCLC). METHODS: A retrospective analysis was performed in 91 patients with NSCLC who underwent preoperative DTP 18F-FDG PET/CT scans. MPs in the early scan (eSUVmax, eSUVmean, eMTV, eTLG) and delayed scan (dSUVmax, dSUVmean, dMTV, dTLG) were calculated, respectively. The change in MPs (ΔSUVmax, ΔSUVmean, ΔMTV, ΔTLG) between the two time points were calculated. Tumor specimens were analyzed by immunohistochemistry for PD-1/PD-L1 expression and CD8+ tumor-infiltrating lymphocytes (TILs). TIME was classified into four immune types (TMIT I ~ IV) according to the expression of PD-L1 and CD8+ TILs. Correlations between MPs with TMITs and the immune-related biomarkers were analyzed. A composite metabolic signature (Meta-Sig) and a combined model of Meta-Sig and clinical factors were constructed to predict patients with TMIT I tumors. RESULTS: eSUVmax, eSUVmean, dSUVmax, dSUVmean, ΔSUVmax, ΔSUVmean, and ΔTLG were significantly higher in PD-L1 positive patients (p = 0.0007, 0.0006, < 0.0001, < 0.0001, 0.0002, 0.0002, 0.0247, respectively), and in TMIT-I tumors (p = 0.0001, < 0.0001, < 0.0001, < 0.0001, 0.0009, 0.0009, 0.0144, respectively). Compared to stand-alone MP, the Meta-Sig and combined model displayed better performance for assessing TMIT-I tumors (Meta-sig: AUC = 0.818, sensitivity = 86.36%, specificity = 73.91%; Model: AUC = 0.869, sensitivity = 77.27%, specificity = 82.61%). CONCLUSION: High glucose metabolism on DTP 18F-FDG PET correlated with the TMIT-I tumors, and the Meta-Sig and combined model based on clinical and metabolic information could improve the performance of identifying the patients who may respond to immunotherapy.

Bone Fragment Co-transplantation Alongside Bone Marrow Aspirate Infusion Protects Kidney Transplant Recipients.

Integration of non-vascularized bone grafting and bone marrow aspirate infusion in transplantation may provide clinical benefit. Here we have incorporated bone fragment co-transplantation and bone marrow aspirate infusion (BF-BM) into living kidney transplantation (LKT). Twenty LKT recipients receiving bone fragments and bone marrow aspirates donated from their corresponding donors were enrolled into a retrospective study. A contemporaneous control group was formed of 38 out of 128 conventional LKT recipients, selected using propensity score matching by a 1:2 Greedy algorithm. Ultrasonography, contrast-enhanced ultrasonography (US/CEUS) and SPECT/CT showed that the co-transplanted bone fragments remained viable for 6 months, subsequently shrank, and finally degenerated 10 months post-transplantation. BF-BM resulted in earlier kidney recovery and more robust long-term kidney function. Throughout 5 years of follow-up, BF-BM had regulatory effects on dendritic cells (DCs), T helper (Th1/Th2) cells and regulatory T cells (Tregs). Both alloantigen-specific lymphocyte proliferation and panel reactive antibody levels were negative in all recipients with or without BF-BM. In addition, the BF-BM group experienced few complications during the 5-year follow-up (as did the donors)-this was not different from the controls. In conclusion, BF-BM is safe and benefits recipients by protecting the kidney and regulating the immune response.

LCPR-Net: low-count PET image reconstruction using the domain transform and cycle-consistent generative adversarial networks.

BACKGROUND: Reducing the radiation tracer dose and scanning time during positron emission tomography (PET) imaging can reduce the cost of the tracer, reduce motion artifacts, and increase the efficiency of the scanner. However, the reconstructed images to be noisy. It is very important to reconstruct high-quality images with low-count (LC) data. Therefore, we propose a deep learning method called LCPR-Net, which is used for directly reconstructing full-count (FC) PET images from corresponding LC sinogram data. METHODS: Based on the framework of a generative adversarial network (GAN), we enforce a cyclic consistency constraint on the least-squares loss to establish a nonlinear end-to-end mapping process from LC sinograms to FC images. In this process, we merge a convolutional neural network (CNN) and a residual network for feature extraction and image reconstruction. In addition, the domain transform (DT) operation sends a priori information to the cycle-consistent GAN (CycleGAN) network, avoiding the need for a large amount of computational resources to learn this transformation. RESULTS: The main advantages of this method are as follows. First, the network can use LC sinogram data as input to directly reconstruct an FC PET image. The reconstruction speed is faster than that provided by model-based iterative reconstruction. Second, reconstruction based on the CycleGAN framework improves the quality of the reconstructed image. CONCLUSIONS: Compared with other state-of-the-art methods, the quantitative and qualitative evaluation results show that the proposed method is accurate and effective for FC PET image reconstruction.

Primary Inferior Vena Cava Leiomyosarcoma With Hepatic Metastases on FDG PET/CT.

ABSTRACT: Leiomyosarcomas originating from the inferior vena cava are very rare malignant tumors with an extremely poor prognosis. We report FDG PET/CT findings of pathology-proven hepatic metastases from leiomyosarcoma originating from the inferior vena cava in a young woman whose initial presentation was worsening abdominal and chest pain.

The development of a Glypican-3-specific binding peptide using in vivo and in vitro two-step phage display screening for the PET imaging of hepatocellular carcinoma.

Glypican-3 (GPC3) is a diagnostic biomarker for hepatocellular carcinoma (HCC). Although numerous designs targeting GPC3 have been reported, the HCC diagnostic agents with specific tumor accumulation and low background, particularly in normal liver tissue, are still in need. Peptides have attracted considerable attention as an imaging probe due to their low immunogenicity, short in vivo circulation time, and acceptable production cost. Herein, a two-step phage display screening approach was performed against GPC3-high expression tumor xenografts in vivo, followed by human recombinant GPC3 protein in vitro. A GPC3-specific binding peptide, named TJ12P2, with the sequence of Ser-Asn-Asp-Arg-Pro-Pro-Asn-Ile-Leu-Gln-Lys-Arg (SNDRPPNILQKR) was identified. The apparent Kd value between TJ12P2 and the GPC3 protein was measured as 158.2 ± 26.25 nM. After 18F labeling, 18F-AlF-NOTA-TJ12P2 was found accumulated in the tumors by positron emission tomography (PET) imaging in two HCC subcutaneous tumor models (HepG2 and SMMC-7721) with high GPC3 expression. Static PET imaging revealed that 18F-AlF-NOTA-TJ12P2 accumulation in the HepG2 and SMMC-7721 tumors reached 1.825 ± 0.296 %ID g-1 and 1.575 ± 0.520 %ID g-1, with tumor-to-muscle ratios of 4.14 ± 0.50 and 4.25 ± 0.25, respectively, at 30 min post-injection (p.i.). Much less accumulation (0.533 ± 0.078 %ID g-1) of the 18F-AlF-NOTA-TJ12P2 was found in the control PC3 tumors with low GPC3 expression. More importantly, no obvious normal liver uptake of TJ12P2 was observed in the abovementioned animal models. As a result, a novel peptide targeting GPC3, TJ12P2, with strong affinity and specificity was identified using a two-step phage display screening technique in the present study. The 18F-AlF-NOTA-TJ12P2 may be a promising PET imaging probe with translational potential for accurate HCC diagnosis.

Obtaining PET/CT images from non-attenuation corrected PET images in a single PET system using Wasserstein generative adversarial networks.

Positron emission tomography (PET) imaging plays an indispensable role in early disease detection and postoperative patient staging diagnosis. However, PET imaging requires not only additional computed tomography (CT) imaging to provide detailed anatomical information but also attenuation correction (AC) maps calculated from CT images for precise PET quantification, which inevitably demands that patients undergo additional doses of ionizing radiation. To reduce the radiation dose and simultaneously obtain high-quality PET/CT images, in this work, we present an alternative based on deep learning that can estimate synthetic attenuation corrected PET (sAC PET) and synthetic CT (sCT) images from non-attenuation corrected PET (NAC PET) scans for whole-body PET/CT imaging. Our model consists of two stages: the first stage removes noise and artefacts in the NAC PET images to generate sAC PET images, and the second stage synthesizes CT images from the sAC PET images obtained in the first stage. Both stages employ the same deep Wasserstein generative adversarial network and identical loss functions, which encourage the proposed model to generate more realistic and satisfying output images. To evaluate the performance of the proposed algorithm, we conducted a comprehensive study on a total of 45 sets of paired PET/CT images of clinical patients. The final experimental results demonstrated that both the generated sAC PET and sCT images showed great similarity to true AC PET and true CT images based on both qualitative and quantitative analyses. These results also indicate that in the future, our proposed algorithm has tremendous potential for reducing the need for additional anatomic imaging in hybrid PET/CT systems or the need for lengthy MR sequence acquisition in hybrid PET/MRI systems.