Dataset Information

A dual tracer (68)Ga-DOTANOC PET/CT and (18)F-FDG PET/CT pilot study for detection of cardiac sarcoidosis.

ABSTRACT: BACKGROUND:Cardiac sarcoidosis (CS) is a potentially fatal condition lacking a single test with acceptable diagnostic accuracy. (18)F-FDG PET/CT has emerged as a promising imaging modality, but is challenged by physiological myocardial glucose uptake. An alternative tracer, (68)Ga-DOTANOC, binds to somatostatin receptors on inflammatory cells in sarcoid granulomas. We therefore aimed to conduct a proof-of-concept study using (68)Ga-DOTANOC to diagnose CS. In addition, we compared diagnostic accuracy and inter-observer variability of (68)Ga-DOTANOC vs. (18)F-FDG PET/CT. METHODS:Nineteen patients (seven female) with suspected CS were prospectively recruited and dual tracer scanned within 7 days. PET images were reviewed by four expert readers for signs of CS and compared to the reference standard (Japanese ministry of Health and Welfare CS criteria). RESULTS:CS was diagnosed in 3/19 patients. By consensus, 11/19 (18)F-FDG scans and 0/19 (68)Ga-DOTANOC scans were rated as inconclusive. The sensitivity of (18)F-FDG PET for diagnosing CS was 33 %, specificity was 88 %, PPV was 33 %, NPV was 88 %, and diagnostic accuracy was 79 %. For (68)Ga-DOTANOC, accuracy was 100 %. Inter-observer agreement was poor for (18)F-FDG PET (Fleiss' combined kappa 0.27, NS) and significantly better for (68)Ga-DOTANOC (Fleiss' combined kappa 0.46, p?=?0.001). CONCLUSIONS:Despite prolonged pre-scan fasting, a large proportion of (18)F-FDG PET/CT images were rated as inconclusive, resulting in low agreement among reviewers and correspondingly poor diagnostic accuracy. By contrast, (68)Ga-DOTANOC PET/CT had excellent diagnostic accuracy with the caveat that inter-observer variability was still significant. Nevertheless, (68)Ga-DOTANOC PET/CT looks very promising as an alternative CS PET tracer. TRIAL REGISTRATION:Current Controlled Trials NCT01729169 .

SUBMITTER: Gormsen LC

PROVIDER: S-EPMC4912521 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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A dual tracer (68)Ga-DOTANOC PET/CT and (18)F-FDG PET/CT pilot study for detection of cardiac sarcoidosis.

Gormsen Lars C LC Gormsen Lars C LC Haraldsen Ate A Kramer Stine S Dias Andre H AH Kim Won Yong WY Borghammer Per P

EJNMMI research 20160617 1

<h4>Background</h4>Cardiac sarcoidosis (CS) is a potentially fatal condition lacking a single test with acceptable diagnostic accuracy. (18)F-FDG PET/CT has emerged as a promising imaging modality, but is challenged by physiological myocardial glucose uptake. An alternative tracer, (68)Ga-DOTANOC, binds to somatostatin receptors on inflammatory cells in sarcoid granulomas. We therefore aimed to conduct a proof-of-concept study using (68)Ga-DOTANOC to diagnose CS. In addition, we compared diagnos ...[more]

PMID: 27316444

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Project description:Somatostatin receptors are overexpressed in GEP-NETs and can be visualized in vivo by radiolabeled somatostatin-analogs. During the last decades, conventional scintigraphy using 111In-DTPA-Octreotide (often named somatostatin receptor scintigraphy or SRS) was considered as the gold standard nuclear imaging technique in the evaluation of GEP-NETs. However, SRS may be suboptimal in this clinical setting because of the low intrinsic resolution of the technique and its selectivity for SST2 only. Its overall sensitivity is estimated to 60-70% (per lesion analysis), even when using the most recent SPECT-CT cameras. MRI have also a higher sensitivity than CT and SRS for the detection of liver metastases from GEP-NETs. In recent years, positron emission tomography (PET) imaging, a high resolution and sensitive technology, has gained an increasing role in oncology. It has also been evaluated in GEP-NETs with somatostatin agonists (SSTa) radiolabelled with Gallium-68 [68Ga], a positron emitter with very promising results. Its diagnostic sensitivity is clearly superior to SRS and many European centers have already replaced SRS by [68Ga]-PET-SSTa. Currently, three different [68Ga]-coupled peptides can be used in trials: DOTA-TOC, DOTA-TATE and DOTA-NOC with excellent affinities for SST2 (IC50: 2.5; 0.2 and 1.9 nM, respectively). Sensitivities of DOTA-TOC and DOTA-TATE PET/CT are quite similar. [68Ga]-DOTANOC which also binds to SST5 was recently found to detect significantly more lesions than the SST2-specific radiotracer [68Ga]-DOTATATE in patients with GEP-NETs but this requires further evaluation. It is therefore important to determine the interest of [68Ga]-DOTANOC combined with the standard diagnosis strategy in GEP-NETs and evaluate medicoeconomic impact of adding [68Ga]-DOTANOC in the work-up of patients. The investigators hypothesis is that [68Ga]-DOTANOC will modify the management in at least 20% of patients in a more adapted way according to the 2012 ENETS guidelines in comparison to the decision based on the standard imaging work up (multiphasic WB CT, liver MRI and SRS). 110 patients will be included prospectively in 5 different French experienced centers (Marseille, Bordeaux, Toulouse, Paris, Clermond-Ferrand).

Project description:PurposeIn PSMA-ligand PET/CT imaging, standardized evaluation frameworks and image-derived parameters are increasingly used to support prostate cancer staging. Clinical applicability remains challenging wherever manual measurements of numerous suspected lesions are required. Deep learning methods are promising for automated image analysis, typically requiring extensive expert-annotated image datasets to reach sufficient accuracy. We developed a deep learning method to support image-based staging, investigating the use of training information from two radiotracers.MethodsIn 173 subjects imaged with 68Ga-PSMA-11 PET/CT, divided into development (121) and test (52) sets, we trained and evaluated a convolutional neural network to both classify sites of elevated tracer uptake as nonsuspicious or suspicious for cancer and assign them an anatomical location. We evaluated training strategies to leverage information from a larger dataset of 18F-FDG PET/CT images and expert annotations, including transfer learning and combined training encoding the tracer type as input to the network. We assessed the agreement between the N and M stage assigned based on the network annotations and expert annotations, according to the PROMISE miTNM framework.ResultsIn the development set, including 18F-FDG training data improved classification performance in four-fold cross validation. In the test set, compared to expert assessment, training with 18F-FDG data and the development set yielded 80.4% average precision [confidence interval (CI): 71.1-87.8] for identification of suspicious uptake sites, 77% (CI: 70.0-83.4) accuracy for anatomical location classification of suspicious findings, 81% agreement for identification of regional lymph node involvement, and 77% agreement for identification of metastatic stage.ConclusionThe evaluated algorithm showed good agreement with expert assessment for identification and anatomical location classification of suspicious uptake sites in whole-body 68Ga-PSMA-11 PET/CT. With restricted PSMA-ligand data available, the use of training examples from a different radiotracer improved performance. The investigated methods are promising for enabling efficient assessment of cancer stage and tumor burden.

Dataset Information

A dual tracer (68)Ga-DOTANOC PET/CT and (18)F-FDG PET/CT pilot study for detection of cardiac sarcoidosis.

Publications

A dual tracer (68)Ga-DOTANOC PET/CT and (18)F-FDG PET/CT pilot study for detection of cardiac sarcoidosis.

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