RESUMO
In recent decades, researchers worldwide have directed their efforts toward enhancing the quality of PET imaging. The detection sensitivity and image resolution of conventional PET scanners with a short axial field of view have been constrained, leading to a suboptimal signal-to-noise ratio. The advent of long-axial-field-of-view PET scanners, exemplified by the uEXPLORER system, marked a significant advancement. Total-body PET imaging possesses an extensive scan range of 194 cm and an ultrahigh detection sensitivity, and it has emerged as a promising avenue for improving image quality while reducing the administered radioactivity dose and shortening acquisition times. In this review, we elucidate the application of the uEXPLORER system at the Sun Yat-sen University Cancer Center, including the disease distribution, patient selection workflow, scanning protocol, and several enhanced clinical applications, along with encountered challenges. We anticipate that this review will provide insights into routine clinical practice and ultimately improve patient care.
Assuntos
Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Imagem Corporal Total , Humanos , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada/métodos , Imagem Corporal Total/métodos , Neoplasias/diagnóstico por imagem , Centros de Atenção Terciária , Institutos de Câncer , Processamento de Imagem Assistida por Computador/métodosRESUMO
OBJECTIVES: Total-body PET/CT scanners with long axial fields of view have enabled unprecedented image quality and quantitative accuracy. However, the ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Therefore, we attempted to generate CT-free attenuation-corrected (CTF-AC) total-body PET images through deep learning. METHODS: Based on total-body PET data from 122 subjects (29 females and 93 males), a well-established cycle-consistent generative adversarial network (Cycle-GAN) was employed to generate CTF-AC total-body PET images directly while introducing site structures as prior information. Statistical analyses, including Pearson correlation coefficient (PCC) and t-tests, were utilized for the correlation measurements. RESULTS: The generated CTF-AC total-body PET images closely resembled real AC PET images, showing reduced noise and good contrast in different tissue structures. The obtained peak signal-to-noise ratio and structural similarity index measure values were 36.92 ± 5.49 dB (p < 0.01) and 0.980 ± 0.041 (p < 0.01), respectively. Furthermore, the standardized uptake value (SUV) distribution was consistent with that of real AC PET images. CONCLUSION: Our approach could directly generate CTF-AC total-body PET images, greatly reducing the radiation risk to patients from redundant anatomical examinations. Moreover, the model was validated based on a multidose-level NAC-AC PET dataset, demonstrating the potential of our method for low-dose PET attenuation correction. In future work, we will attempt to validate the proposed method with total-body PET/CT systems in more clinical practices. CLINICAL RELEVANCE STATEMENT: The ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Our CT-free PET attenuation correction method would be beneficial for a wide range of patient populations, especially for pediatric examinations and patients who need multiple scans or who require long-term follow-up. KEY POINTS: ⢠CT is the main source of radiation in PET/CT imaging, especially for total-body PET/CT devices, and reduced radiopharmaceutical doses make the radiation burden from CT more obvious. ⢠The CT-free PET attenuation correction method would be beneficial for patients who need multiple scans or long-term follow-up by reducing additional radiation from redundant anatomical examinations. ⢠The proposed method could directly generate CT-free attenuation-corrected (CTF-AC) total-body PET images, which is beneficial for PET/MRI or PET-only devices lacking CT image poses.
RESUMO
PIWI-interacting RNAs (piRNAs) are a class of small noncoding RNA molecules that specifically bind to piwi protein family members to exert regulatory functions in germ cells. Recent studies have found that piRNAs, as tissue-specific molecules, both play oncogenic and tumor suppressive roles in cancer progression, including cancer cell proliferation, metastasis, chemoresistance and stemness. Additionally, the atypical manifestation of piRNAs and PIWI proteins in various malignancies presents a promising strategy for the identification of novel biomarkers and therapeutic targets in the diagnosis and management of tumors. Nonetheless, the precise functions of piRNAs in cancer progression and their underlying mechanisms have yet to be fully comprehended. This review aims to examine current research on the biogenesis and functions of piRNA and its burgeoning importance in cancer progression, thereby offering novel perspectives on the potential utilization of piRNAs and piwi proteins in the management and treatment of advanced cancer.
Assuntos
Neoplasias , Pequeno RNA não Traduzido , Humanos , Proteínas Argonautas/genética , Proteínas Argonautas/metabolismo , Neoplasias/metabolismo , RNA de Interação com Piwi , RNA Interferente Pequeno/genética , RNA Interferente Pequeno/metabolismoRESUMO
BACKGROUND: Glioma is characterized by a high recurrence rate, while the results of the traditional imaging methods (including magnetic resonance imaging, MRI) to distinguish recurrence from treatment-related changes (TRCs) are poor. Prostate-specific membrane antigen (PSMA) (US10815200B2, Deutsches Krebsforschungszentrum, German Cancer Research Center) is a type II transmembrane glycoprotein overexpressed in glioma vascular endothelium, and it is a promising target for imaging and therapy. OBJECTIVE: The study aimed to assess the performance of PSMA positron emission tomography/ magnetic resonance (PET/MR) for diagnosing recurrence and predicting prognosis in glioma patients. MATERIALS AND METHODS: Patients suspected of glioma recurrence who underwent 18F-PSMA-1007 PET/MR were prospectively enrolled. Eight metabolic parameters and fifteen texture features of the lesion were extracted from PSMA PET/MR. The ability of PSMA PET/MR to diagnose glioma recurrence was investigated and compared with conventional MRI. The diagnostic agreement was assessed using Cohen κ scores and the predictive parameters of PSMA PET/MR were obtained. Kaplan-Meier method and Cox proportional hazard model were used to analyze recurrence- free survival (RFS) and overall survival (OS). Finally, the expression of PSMA was analyzed by immunohistochemistry (IHC). RESULTS: Nineteen patients with a mean age of 48.11±15.72 were assessed. The maximum tumorto- parotid ratio (TPRmax) and texture features extracted from PET and T1-weighted contrast enhancement (T1-CE) MR showed differences between recurrence and TRCs (all p <0.05). PSMA PET/MR and conventional MRI exhibited comparable power in diagnosing recurrence with specificity and PPV of 100%. The interobserver concordance was fair between the two modalities (κ = 0.542, p = 0.072). The optimal cutoffs of metabolic parameters, including standardized uptake value (SUV, SUVmax, SUVmean, and SUVpeak) and TPRmax for predicting recurrence were 3.35, 1.73, 1.99, and 0.17 respectively, with the area under the curve (AUC) ranging from 0.767 to 0.817 (all p <0.05). In grade 4 glioblastoma (GBM) patients, SUVmax, SUVmean, SUVpeak, TBRmax, TBRmean, and TPRmax showed improved performance of AUC (0.833-0.867, p <0.05). Patients with SUVmax, SUVmean, or SUVpeak more than the cutoff value had significantly shorter RFS (all p <0.05). In addition, patients with SUVmean, SUVpeak, or TPRmax more than the cutoff value had significantly shorter OS (all p <0.05). PSMA expression of glioma vascular endothelium was observed in ten (10/11, 90.9%) patients with moderate-to-high levels in all GBM cases (n = 6/6, 100%). CONCLUSION: This primitive study shows multiparameter PSMA PET/MR to be useful in identifying glioma (especially GBM) recurrence by providing excellent tumor background comparison, tumor heterogeneity, recurrence prediction and prognosis information, although it did not improve the diagnostic performance compared to conventional MRI. Further and larger studies are required to define its potential clinical application in this setting.