68Ga-PSMA PET/CT False-Positive Tracer Uptake in Paget Disease

Abstract Radical radiation therapy for oligorecurrent prostate cancer is considered to improve both overall and disease-specific survival. Therefore, accurate diagnosis by imaging is important when considering the indications for radiation therapy. We present a case of marginal recurrence of bone metastases from castration-resistant prostate cancer previously treated with radical radiation therapy, which could not be detected by bone single photon emission computed tomography/computed tomography (SPECT/CT) but could be diagnosed by 68Ga-prostate-specific membrane antigen positron emission tomography/computed tomography (68Ga-PSMA PET/CT). Bone SPECT/CT showed false-positive tracer uptake in the lesion previously irradiated. 68Ga-PSMA PET/CT scan showed no abnormal uptake in the previously irradiated lesion, but showed intense uptake in the newly developed metastasis near the irradiated site. 68Ga-PSMA PET/CT scan may be able to diagnose marginal recurrence after radiation therapy more accurately than bone SPECT/CT.

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68Ga/64Cu PSMA Bio-Distribution in Prostate Cancer Patients: Potential Pitfalls for Different Tracers

Current Radiopharmaceuticals ◽

10.2174/1874471012666190515090755 ◽

2019 ◽

Vol 12 (3) ◽

pp. 238-246 ◽

Cited By ~ 2

Author(s):

Ferdinando Calabria ◽

Robert Pichler ◽

Mario Leporace ◽

Johannes Wolfsgruber ◽

Pierluigi Coscarelli ◽

...

Keyword(s):

Prostate Cancer ◽

Cancer Patients ◽

False Positive ◽

Transmembrane Protein ◽

Diagnostic Pitfall ◽

Psma Pet ◽

Pet Ct ◽

Resolution Imaging ◽

Glutamate Carboxypeptidase ◽

Diagnostic Pitfalls

Background:68Ga-PSMA is a widely useful PET/CT tracer for prostate cancer imaging. Being a transmembrane protein acting as a glutamate carboxypeptidase enzyme, PSMA is highly expressed in prostate cancer cells. PSMA can also be labeled with 64Cu, offering a longer half-life and different resolution imaging. Several studies documented bio-distribution and pitfalls of 68Ga-PSMA as well as of 64Cu- PSMA. No data are reported on differences between these two variants of PSMA. Our aim was to evaluate physiological distribution of these two tracers and to analyze false positive cases.Methods:We examined tracer bio-distribution in prostate cancer patients with negative 68Ga-PSMA PET/CT (n=20) and negative 64Ga-PSMA PET/CT (n=10). A diagnostic pitfall for each tracer was documented.Results:Bio-distribution of both tracers was similar, with some differences due to renal excretion of 68Ga- PSMA and biliary excretion of 64Cu-PSMA. 68Ga-PSMA uptake was observed in sarcoidosis while 64Cu- PSMA uptake was recorded in pneumonitis.Discussion:Both tracers may present similar bio-distribution in the human body, with similar uptake in exocrine glands and high intestinal uptake. Similarly to other tracers, false positive cases cannot be excluded in clinical practice.Conclusion:The knowledge of difference in bio-distribution between two tracers may help in interpretation of PET data. Diagnostic pitfalls can be documented, due to the possibility of PSMA uptake in inflammation. Our results are preliminary to future studies comparing diagnostic accuracies of 68Ga-PSMA and 64Cu-PSMA.

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Gastrointestinal Stromal Tumor Showing Intense Tracer Uptake on PSMA PET/CT

Clinical Nuclear Medicine ◽

10.1097/rlu.0000000000001491 ◽

2017 ◽

Vol 42 (3) ◽

pp. 200-202 ◽

Cited By ~ 16

Author(s):

Benjamin Noto ◽

Matthias Weckesser ◽

Boris Buerke ◽

Michaela Pixberg ◽

Nemanja Avramovic

Keyword(s):

Gastrointestinal Stromal Tumor ◽

Tracer Uptake ◽

Stromal Tumor ◽

Psma Pet ◽

Pet Ct

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Evaluating a Machine Learning Tool for the Classification of Pathological Uptake in Whole-Body PSMA-PET-CT Scans

Tomography ◽

10.3390/tomography7030027 ◽

2021 ◽

Vol 7 (3) ◽

pp. 301-312

Author(s):

Annette Erle ◽

Sobhan Moazemi ◽

Susanne Lütje ◽

Markus Essler ◽

Thomas Schultz ◽

...

Keyword(s):

Machine Learning ◽

Area Under The Curve ◽

Ground Truth ◽

Tracer Uptake ◽

Whole Body ◽

Clinical Environment ◽

Physiological Uptake ◽

Psma Pet ◽

Pet Ct ◽

Unseen Data

The importance of machine learning (ML) in the clinical environment increases constantly. Differentiation of pathological from physiological tracer-uptake in positron emission tomography/computed tomography (PET/CT) images is considered time-consuming and attention intensive, hence crucial for diagnosis and treatment planning. This study aimed at comparing and validating supervised ML algorithms to classify pathological uptake in prostate cancer (PC) patients based on prostate-specific membrane antigen (PSMA)-PET/CT. Retrospective analysis of 68Ga-PSMA-PET/CTs of 72 PC patients resulted in a total of 77 radiomics features from 2452 manually delineated hotspots for training and labeled pathological (1629) or physiological (823) as ground truth (GT). As the held-out test dataset, 331 hotspots (path.:128, phys.: 203) were delineated in 15 other patients. Three ML classifiers were trained and ranked to assess classification performance. As a result, a high overall average performance (area under the curve (AUC) of 0.98) was achieved, especially to detect pathological uptake (0.97 mean sensitivity). However, there is still room for improvement to detect physiological uptake (0.82 mean specificity), especially for glands. The ML algorithm applied to manually delineated lesions predicts hotspot labels with high accuracy on unseen data and may be an important tool to assist in clinical diagnosis.

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Schwannoma: A rare cause of false-positive 68Ga-PSMA PET/CT uptake in the evaluation of metastatic prostate cancer

Urology Case Reports ◽

10.1016/j.eucr.2021.101974 ◽

2021 ◽

pp. 101974

Author(s):

Rodrigo J.C. Gualberto ◽

Matheus Nister ◽

Pedro R. de Castro ◽

Paulo B.O. Arantes

Keyword(s):

Prostate Cancer ◽

False Positive ◽

Metastatic Prostate Cancer ◽

Psma Pet ◽

Pet Ct

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Automated analysis of PSMA-PET/CT studies using convolutional neural networks

10.1101/2021.03.03.21252818 ◽

2021 ◽

Author(s):

Lars Edenbrandt ◽

Pablo Borrelli ◽

Johannes Ulen ◽

Olof Enqvist ◽

Elin Tragardh

Keyword(s):

Lymph Nodes ◽

Bone Metastases ◽

Prostate Gland ◽

Automated Analysis ◽

Tracer Uptake ◽

Sign Test ◽

Visual Interpretation ◽

Psma Pet ◽

Pet Ct ◽

Ct Studies

Purpose: Prostate-specific membrane antigen (PSMA) PET/CT has shown to be more sensitive and accurate than conventional imaging. Visual interpretation of the images causes both intra- and inter-reader disagreement and there is therefore a need for objective methods to analyze the images. The aim of this study was to develop an artificial intelligence (AI) tool for PSMA PET/CT and to evaluate the influence of the tool on inter-reader variability. Approach: We have recently trained AI tools to automatically segment organs, detect tumors, and quantify volume and tracer uptake of tumors in PET/CT. The primary prostate gland tumor, bone metastases, and lymph nodes were analyzed in patients with prostate cancer. These studies were based on non-PSMA targeting PET tracers. In this study an AI tool for PSMA PET/CT was developed based on our previous AI tools. Letting three physicians analyze ten PSMA PET/CT studies first without support from the AI tool and at a second occasion with the support of the AI tool assessed the influence of the tool. A two-sided sign test was used to analyze the number of cases with increased and decreased variability with support of the AI tool. Results: The range between the physicians in prostate tumor total lesion uptake (TLU) decreased for all ten patients with AI support (p=0.002) and decreased in bone metastases TLU for nine patients and increased in one patient (p=0.01). Regarding the number of detected lymph nodes the physicians agreed in on average 72% of the lesions without AI support and this number decreased to 65% with AI support. Conclusions: Physicians supported by an AI tool for automated analysis of PSMA-PET/CT studies showed significantly less inter-reader variability in the quantification of primary prostate tumors and bone metastases than when performing a completely manual analysis. A similar effect was not found for lymph node lesions. The tool may facilitate comparisons of studies from different centers, pooling data within multicenter trials and performing meta-analysis. We invite researchers to apply and evaluate our AI tool for their PSMA PET/CT studies. The AI tool is therefore available upon reasonable request for research purposes at www.recomia.org.

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The effect of androgen deprivation therapy on 68GA-PSMA-tracer uptake in nonmetastatic prostate cancer patients.

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.6_suppl.22 ◽

2020 ◽

Vol 38 (6_suppl) ◽

pp. 22-22

Author(s):

Onal Cem ◽

Ozan Cem Guler ◽

Nese Torun ◽

Mehmet Reyhan ◽

Ali Fuat Yapar

Keyword(s):

Prostate Cancer ◽

Cancer Patients ◽

Tracer Uptake ◽

Androgen Deprivation ◽

Post Treatment ◽

Ct Scans ◽

Baseline Serum ◽

Psma Pet ◽

Pet Ct ◽

Psa Response

22 Background: To evaluate the effect of neoadjuvant androgen deprivation treatment (ADT) on prostate specific membrane antigen (PSMA) tracer uptake demonstrated in 68Ga-PSMA-positron emission tomography (PET/CT) in non-metastatic hormone-naïve prostate cancer patients. Methods: The clinical data of 108 prostate cancer patients who received neoadjuvant ADT were retrospectively analyzed. All patients had a baseline 68Ga-PSMA-PET/CT scan and a second scan was delivered median of 2.9 months after initiation of ADT. Patients with clinical and radiological evidence of distant metastasis were excluded from the study. The maximum standardized uptake value (SUVmax) of primary tumor (SUVp) and metastatic lymph nodes (SUVln) as well as PSA response were assessed between pre- and post-ADT 68Ga-PSMA-PET/CT scans. Results: The median SUVp and SUVln were 14.0 (range, 4.9 – 78.4) and 13.2 (range, 3.6 – 64.5), respectively. There was a significant moderate correlation between baseline serum PSA and SUVp (Spearman = 0.513, p<0.001). There were significant decreases in post-treatment serum PSA, SUVp, and SUVp. A decrease in SUVp was seen in 91 patients (84%) with a median value of 66% (range, 5% – 100%), while 17 patients (16%) had no change in or an increase in PSMA tracer uptake with a median value of 24% (range, 0% – 198%). Patients with Gleason score (GS) of 7 had significantly higher metabolic response rates compared to other patients. The disease progression was significantly higher only in patients with GS > 7 disease compared to GS 7 disease. The PSA response to ADT was lowest in patients with ISUP high-grade tumors. A total of 16 patients (15%) had progressive disease, and in 9 patients (8%), radiotherapy decisions were modified according to post-treatment 68Ga-PSMA-PET/CT scans. Conclusions: The current study includes the largest number of patients analyzed to date and demonstrates that ADT causes a significant decrease in serum PSA values and SUVp and SUVln. The authors demonstrate that 68Ga-PSMA-PET/CT may be used as a quantitative imaging modality after neoadjuvant ADT in hormone-naïve non-metastatic PC patients.

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