Spurious Uptake on 68Ga–Prostate-Specific Membrane Antigen PET/CT Due to Ankylosing Spondylitis; A Rare Pitfall in Imaging of Biochemical Recurrence of Prostate Cancer

Heaney, Roisin; Johnston, Ciarán; Nasoodi, Afshin

doi:10.1097/rlu.0000000000003616

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…Ankylosing spondylitis (AS) is an immune-mediated chronic in ammatory disease primarily affecting the spine and sacroiliac joints [1,2]. The most prevalent symptoms of AS include back pain and progressive spinal ankylosis [3,4]. AS can result in joint injury and fusion of the major sacroiliac joints, and in severe cases, it may lead to the formation of bamboo ridges in spondylosis [5,6].…”

Section: Introductionmentioning

confidence: 99%

Identification of Key Genes Related to Ankylosing Spondylitis Using WGCNA and Bioinformatics Analysis

Liang²,

Wu³

2023

Preprint

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Objective: Ankylosing spondylitis (AS) is a chronic inflammatory disease characterized by the inflammation of the spine and sacroiliac joints. Understanding the underlying immune cells and key genes associated with AS is crucial for unraveling its pathogenesis. In this study, we employed weighted gene co-expression network analysis (WGCNA) to identify immune cells and key genes involved in AS. The GSE11886 dataset, obtained from the GEO database, was utilized for the analysis of differentially expressed genes (DEGs). Subsequently, the WGCNA package was applied to screen for key modules and genes that correlated with clinical characteristics of AS. The intersection of DEGs obtained from the analysis and genes within the blue module led to the identification of key genes, which were further subjected to correlation analysis. Our findings revealed a total of 279 DEGs, including 123 up-regulated and 156 down-regulated genes, as determined by a volcano map. Additionally, WGCNA analysis unveiled a key module strongly associated with AS. Within this module, we identified 22 key genes, namely CLIC3, LY75, TNFAIP3, TNFAIP6, STAT1, GBP1, TNFSF13B, CD69, IFITM1, WLS, CNRIP1, LY86, ICAM4, NMRK2, DNASE2B, AMDHD1, TUBB2A, DEXI, TPD52L1, ASRGL1, CECR6, and FAM213B. The discovery of these modules and key genes provides a theoretical foundation for further exploration of the mechanisms underlying the development and progression of AS.

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Section: Introductionmentioning

confidence: 99%

Identification of Key Genes Related to Ankylosing Spondylitis Using WGCNA and Bioinformatics Analysis

Liang²,

Wu³

2023

Preprint

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“…[5][6][7] Regarding bone lesions, intense uptake has been found in other malignant tumors such as myeloma, 8 plasmacytoma, 9 osteosarcoma, 10 Ewing sarcoma, 11 and bone metastases from other cancers. 12,13 Furthermore, many benign bone lesions show intense uptakes such as fibrous dysplasia, 14 Paget's disease, 15 spondylitis, 16 vertebral hemangioma, 17 or healing fractures. 18 Thus, although high bone uptakes have been observed in up to 40% of patients with PCa relapse, studies have warned about the lack of histological confirmation of malignancy and the risk of false-positive lesions.…”

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confidence: 99%

Bone Uptake in Prostate Cancer Patients

et al. 2022

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Purpose: 68 Gallium-labeled prostate-specific membrane antigen-11 (PSMA) PET/CT is the new reference to identify relapse during biochemical recurrence of prostate cancer (PCa). However, this method lacks specificity for bone foci. This study aimed to report the prevalence of PCa bone metastases and to assess the diagnostic performances of PSMA reporting and data systems (RADS), clinical, biological, and imaging features for identification. Patients and Methods: A multicentric retrospective cohort of consecutive patients with biochemical recurrence after local treatment was analyzed. Clinical and biological features at initial staging and during recurrence were retrieved from medical reports. The metastatic status of each bone uptake on PSMA PET/CT was determined according to histopathology, comparisons with concomitant and previous conventional imaging, prostate-specific antigen kinetic, and follow-up. Two nuclear medicine physicians assessed PSMA-RADS, anatomic location, radiological patterns, SUV max , and the presence of other molecular lesions. Univariate and multivariate analyses were conducted to identify independent predictors of PCa metastases. Results: In the eligible population, 98/298 patients (32.9%) showed bone uptake on PSMA PET/CT. In patients with a final diagnosis, 28/81 lesions (34.6%) were metastases. PSMA-RADS-4 or 5 showed sensitivity of 79%, specificity of 94%, and accuracy of 89%. PSMA-RADS had a significantly higher area under the receiver operating characteristic curve than the initial reading in clinical practice (0.91 vs 0.83, P = 0.0074). Initial Gleason score ≥8, age ≤71 years at recurrence, and SUV max >6.21 were independent predictors of PCa metastases in multivariate logistic regression ( P = 0.0314, 0.0179, and 0.0003, respectively). Conclusions: Most bone uptakes at PSMA PET/CT were benign lesions. PSMA-RADS, patients and tumor characteristics, and SUV max could help identify PCa bone metastases.

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Spurious Uptake on 68Ga–Prostate-Specific Membrane Antigen PET/CT Due to Ankylosing Spondylitis; A Rare Pitfall in Imaging of Biochemical Recurrence of Prostate Cancer

Cited by 2 publications

References 13 publications

Identification of Key Genes Related to Ankylosing Spondylitis Using WGCNA and Bioinformatics Analysis

Identification of Key Genes Related to Ankylosing Spondylitis Using WGCNA and Bioinformatics Analysis

Bone Uptake in Prostate Cancer Patients

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