Combined PET and MRI for the masses Rischpler, Christoph; Seifert, Robert
Journal of nuclear cardiology,
August 2022, Volume:
29, Issue:
4
Journal Article
The use of cardiac PET, and in particular of quantitative myocardial perfusion PET, has been growing during the last years, because scanners are becoming widely available and because several studies ...have convincingly demonstrated the advantages of this imaging approach. Therefore, there is a need of determining the procedural modalities for performing high-quality studies and obtaining from this demanding technique the most in terms of both measurement reliability and clinical data. Although the field is rapidly evolving, with progresses in hardware and software, and the near perspective of new tracers, the EANM Cardiovascular Committee found it reasonable and useful to expose in an updated text the state of the art of quantitative myocardial perfusion PET, in order to establish an effective use of this modality and to help implementing it on a wider basis. Together with the many steps necessary for the correct execution of quantitative measurements, the importance of a multiparametric approach and of a comprehensive and clinically useful report have been stressed.
In daily clinical practice, clinicians integrate available data to ascertain the diagnostic and prognostic probability of a disease or clinical outcome for their patients. For patients with suspected ...or known cardiovascular disease, several anatomical and functional imaging techniques are commonly performed to aid this endeavor, including coronary computed tomography angiography (CCTA) and nuclear cardiology imaging. Continuous improvement in positron emission tomography (PET), single-photon emission computed tomography (SPECT), and CT hardware and software has resulted in improved diagnostic performance and wide implementation of these imaging techniques in daily clinical practice. However, the human ability to interpret, quantify, and integrate these data sets is limited. The identification of novel markers and application of machine learning (ML) algorithms, including deep learning (DL) to cardiovascular imaging techniques will further improve diagnosis and prognostication for patients with cardiovascular diseases. The goal of this position paper of the European Association of Nuclear Medicine (EANM) and the European Association of Cardiovascular Imaging (EACVI) is to provide an overview of the general concepts behind modern machine learning-based artificial intelligence, highlights currently prefered methods, practices, and computational models, and proposes new strategies to support the clinical application of ML in the field of cardiovascular imaging using nuclear cardiology (hybrid) and CT techniques.
PET/CT and other combined scanners have in the past decade rapidly emerged as important research tools and are proving to be invaluable for improved diagnostics in routine nuclear medicine. The ...design of hybrid PET/MR scanners presented a formidable technical challenge, and only recently were these instruments introduced to the market. Initial expectations of the performance of these scanners have been high, notably because of the potential for superior tissue contrast inherent in the MR modality, as well as the potential for multiparametric functional imaging in conjunction with PET. However, the additional value and potential clinical role that these new systems might bring to the cardiac field have yet to be documented. This review presents a comparative summary of the existing applications for PET and MR in the field of cardiology and suggests potential cardiac applications exploiting unique properties of the newly introduced combined instrumentation.
Fabry disease (FD) is an X-linked lysosomal storage disorder caused by absence or deficient activity of α-galactosidase A (α-Gal A) due to mutations in the α-galactosidase A gene (GLA), leading to ...progressive accumulation of globotriaosylceramide (Gb3) in tissues and organs including heart, kidney, the eyes, vascular endothelium, the nervous system and the skin. Cardiac involvement is leading to fatal complications and reduced life expectancy. FD is treatable with disease-specific treatment (enzyme replacement therapy (ERT) or with chaperone therapy). Therefore, the early diagnosis of FD is crucial for reducing the morbidity and mortality. Screening of high-risk populations (eg, patients with unexplained left ventricular hypertrophy (LVH), young patients with unexplained stroke, and patients with unexplained renal failure proteinuria or microalbuminuria) yields good results. The diagnostic algorithm is gender-specific. Initially, the measurement of α-Gal A activity is recommended in males, and optionally in females. In males with non-diagnostic residual activity (5– 10%) activity, genetic testing is afterwards done for confirming the diagnosis. In fact, diagnosis of FD is not possible without genetic testing for both males and females. Globotriaosysphingosine (lyso-Gb3) for identification of atypical FD variants and high- sensitive troponin T (hsTNT) for identification of cardiac involvement are also important diagnostic biomarkers. The aim of this review was to provide an update on diagnosis and screening of patients with FD.
Background
Manual quantification of the metabolic tumor volume (MTV) from whole-body
18
F-FDG PET/CT is time consuming and therefore usually not applied in clinical routine. It has been shown that ...neural networks might assist nuclear medicine physicians in such quantification tasks. However, little is known if such neural networks have to be designed for a specific type of cancer or whether they can be applied to various cancers. Therefore, the aim of this study was to evaluate the accuracy of a neural network in a cancer that was not used for its training.
Methods
Fifty consecutive breast cancer patients that underwent
18
F-FDG PET/CT were included in this retrospective analysis. The PET-Assisted Reporting System (PARS) prototype that uses a neural network trained on lymphoma and lung cancer
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F-FDG PET/CT data had to detect pathological foci and determine their anatomical location. Consensus reads of two nuclear medicine physicians together with follow-up data served as diagnostic reference standard; 1072
18
F-FDG avid foci were manually segmented. The accuracy of the neural network was evaluated with regard to lesion detection, anatomical position determination, and total tumor volume quantification.
Results
If PERCIST measurable foci were regarded, the neural network displayed high per patient sensitivity and specificity in detecting suspicious
18
F-FDG foci (92%; CI = 79–97% and 98%; CI = 94–99%). If all FDG-avid foci were regarded, the sensitivity degraded (39%; CI = 30–50%). The localization accuracy was high for body part (98%; CI = 95–99%), region (88%; CI = 84–90%), and subregion (79%; CI = 74–84%). There was a high correlation of AI derived and manually segmented MTV (
R
2
= 0.91;
p
< 0.001). AI-derived whole-body MTV (HR = 1.275; CI = 1.208–1.713;
p
< 0.001) was a significant prognosticator for overall survival. AI-derived lymph node MTV (HR = 1.190; CI = 1.022–1.384;
p
= 0.025) and liver MTV (HR = 1.149; CI = 1.001–1.318;
p
= 0.048) were predictive for overall survival in a multivariate analysis.
Conclusion
Although trained on lymphoma and lung cancer, PARS showed good accuracy in the detection of PERCIST measurable lesions. Therefore, the neural network seems not prone to the clever Hans effect. However, the network has poor accuracy if all manually segmented lesions were used as reference standard. Both the whole body and organ-wise MTV were significant prognosticators of overall survival in advanced breast cancer.
With this document, we provide a standard for PET/(diagnostic) CT imaging procedures in cardiovascular diseases that are inflammatory, infective, infiltrative, or associated with dysfunctional ...innervation (4Is). This standard should be applied in clinical practice and integrated in clinical (multicenter) trials for optimal procedural standardization. A major focus is put on procedures using
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FFDG, but 4Is PET radiopharmaceuticals beyond
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FFDG are also described in this document. Whilst these novel tracers are currently mainly applied in early clinical trials, some multicenter trials are underway and we foresee in the near future their use in clinical care and inclusion in the clinical guidelines. Finally, PET/MR applications in 4Is cardiovascular diseases are also briefly described. Diagnosis and management of 4Is-related cardiovascular diseases are generally complex and often require a multidisciplinary approach by a team of experts. The new standards described herein should be applied when using PET/CT and PET/MR, within a multimodality imaging framework both in clinical practice and in clinical trials for 4Is cardiovascular indications.
Transthyretin (ATTR) amyloidosis is responsible for the majority of cardiac amyloidosis (CA) cases and can be reliably diagnosed with bone scintigraphy and the visual Perugini score. We aimed to ...implement a quantification method of cardiac amyloid deposits in patients with suspected cardiac amyloidosis and to compare performance to visual scoring.
136 patients received 99mTc-DPD-bone scintigraphy including SPECT/CT of the thorax in case of suspicion of cardiac amyloidosis. Imaging phantom studies were performed to determine the scaling factor for standardized uptake value (SUV) quantification from SPECT/CT. Myocardial tracer uptake was quantified in a whole heart volume of interest.
Forty-five patients were diagnosed with CA. A strong relationship between cardiac SUVmax and Perugini score was found (Spearman r 0.75, p < 0.0001). Additionally, tracer uptake in bone decreased with increasing cardiac SUVmax and Perugini score (p < 0.0001). ROC analysis revealed good performance of the SUVmax for the detection of ATTR-CA with AUC of 0.96 ± 0.02 (p < 0.0001) with sensitivity 98.7% and specificity 87.2%.
We demonstrate an accessible and accurate quantitative SPECT approach in CA. Quantitative assessment of the cardiac tracer uptake may improve diagnostic accuracy and risk classification. This method may enable monitoring and assessment of therapy response in patients with ATTR amyloidosis.
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