Systematic Review and Metanalysis on the Role of Prostate-Specific Membrane Antigen Positron Emission Tomography/Magnetic Resonance Imaging for Intraprostatic Tumour Assessment.

The present systematic review and meta-analysis are focused on the diagnostic accuracy of PSMA PET/MRI in primary prostate cancer assessment. A literature search was conducted on the PubMed database using the terms "PSMA" AND "prostate cancer" or "prostate" AND "PET/MRI" or "PET MRI" or "PET-MRI" or "PET-MR" AND "primary" or "staging." Ten articles were eligible for analysis after applying the exclusion criteria. PET/MRI showed better diagnostic accuracy in detecting primary PCa compared to multiparametric (mp) MRI and PET alone. The pooled sensitivity and specificity of 68Ga-PSMA PET/MRI at the per-patient level were 0.976 (CI: 0.943-0.991) and 0.739 (CI: 0.437-0.912); respectively. PSMA PET/MRI has good sensitivity in detecting primary PCa, especially in patients with PIRADS 3 PCa.

Predictors of PSMA PET Positivity: Analysis in a Selected Cohort of Biochemical Recurrence Prostate Cancer Patients after Radical Prostatectomy.

Localized prostate cancer (PCa) can be treated with radical prostatectomy (RP). Up to 30% of patients undergoing this procedure experience biochemical recurrence (BCR), namely the rise in serum prostate-specific antigen (PSA) levels during the post-surgical follow-up, requiring further treatments and with the risk of severe disease progression. Currently, the most accurate imaging technique to confirm, detect, and locate disease relapses in BCR patients is prostate-specific membrane antigen (PSMA)-targeted PET, as recommended by international clinical guidelines. The aim of the study was to investigate potential clinical and pathological predictors of PSMA PET positivity, validated by clinical and instrumental follow-up or histopathological data. In this study, a selected cohort of BCR patients after RP and no other PCa-related therapy who underwent either PSMA PET/CT or PSMA PET/MRI has been analysed. Among the considered predictors, both pathological staging after RP equal or higher than pT3a and higher PSA levels at the time of the scan were significantly correlated with PSMA PET positivity on multivariate logistic regression analysis. As expected, PSMA PET confirmed its role as an accurate imaging technique in the setting of BCR in PCa. These findings may inform appropriate and tailored patient selection and scan timing to optimize and fully exploit this powerful diagnostic tool.

Preliminary Findings of the Role of FAPi in Prostate Cancer Theranostics.

Prostate cancer (PCa) is the most frequently diagnosed cancer worldwide and the second most common cause of cancer-related deaths among men. Progress in molecular imaging has magnified its clinical management; however, an unmet clinical need involves the identification of new imaging biomarkers that complement the gold standard of prostate-specific membrane antigen (PSMA) positron emission tomography (PET) in cases of clinically significant PCa that do not express PSMA. Fibroblast activation protein (FAP) is a type II transmembrane serine overexpressed in many solid cancers that can be imaged through quinoline-based PET tracers derived from an FAP inhibitor (FAPi). Preliminary results of FAPi application in PCa (in PSMA-negative lesions, and in comparison with fluorodeoxyglucose-FDG) are now available in the literature. FAP-targeting ligands for PCa are not limited to detection, but could also include therapeutic applications. In this preliminary review, we provide an overview of the clinical applications of FAPi ligands in PCa, summarising the main results and highlighting contemporary strengths and limitations.

[68Ga]DOTATOC PET/CT Radiomics to Predict the Response in GEP-NETs Undergoing [177Lu]DOTATOC PRRT: The "Theragnomics" Concept.

Despite impressive results, almost 30% of NET do not respond to PRRT and no well-established criteria are suitable to predict response. Therefore, we assessed the predictive value of radiomics [68Ga]DOTATOC PET/CT images pre-PRRT in metastatic GEP NET. We retrospectively analyzed the predictive value of radiomics in 324 SSTR-2-positive lesions from 38 metastatic GEP-NET patients (nine G1, 27 G2, and two G3) who underwent restaging [68Ga]DOTATOC PET/CT before complete PRRT with [177Lu]DOTATOC. Clinical, laboratory, and radiological follow-up data were collected for at least six months after the last cycle. Through LifeX, we extracted 65 PET features for each lesion. Grading, PRRT number of cycles, and cumulative activity, pre- and post-PRRT CgA values were also considered as additional clinical features. [68Ga]DOTATOC PET/CT follow-up with the same scanner for each patient determined the disease status (progression vs. response in terms of stability/reduction/disappearance) for each lesion. All features (PET and clinical) were also correlated with follow-up data in a per-site analysis (liver, lymph nodes, and bone), and for features significantly associated with response, the Δradiomics for each lesion was assessed on follow-up [68Ga]DOTATOC PET/CT performed until nine months post-PRRT. A statistical system based on the point-biserial correlation and logistic regression analysis was used for the reduction and selection of the features. Discriminant analysis was used, instead, to obtain the predictive model using the k-fold strategy to split data into training and validation sets. From the reduction and selection process, HISTO_Skewness and HISTO_Kurtosis were able to predict response with an area under the receiver operating characteristics curve (AUC ROC), sensitivity, and specificity of 0.745, 80.6%, 67.2% and 0.722, 61.2%, 75.9%, respectively. Moreover, a combination of three features (HISTO_Skewness; HISTO_Kurtosis, and Grading) did not improve the AUC significantly with 0.744. SUVmax, however, could not predict the response to PRRT (p = 0.49, AUC 0.523). The presented preliminary "theragnomics" model proved to be superior to conventional quantitative parameters to predict the response of GEP-NET lesions in patients treated with complete [177Lu]DOTATOC PRRT, regardless of the lesion site.

Diagnosis of cardiac amyloid transthyretin (ATTR) amyloidosis by early (soft tissue) phase [99mTc]Tc-DPD whole body scan: comparison with late (bone) phase imaging.

OBJECTIVES: Although expert consensus recommendations suggest 2-3 h as the time interval between bone-seeking radiotracers injection and acquisition, it has been reported that images obtained early after [99mTc]Tc-HMDP administration are sufficient to diagnose cardiac amyloidosis. We evaluated the diagnostic performance of [99mTc]Tc-DPD early phase whole body scan with respect to late phase imaging. METHODS: We qualitatively and semiquantitatively reviewed [99mTc]Tc-DPD imaging of 53 patients referred for suspect cardiac amyloidosis. Findings of early and late phase images were compared with SPECT results (considered the standard-of-reference) determining sensitivity and specificity for visual analysis of each phase imaging and for each semiquantitative index. RESULTS: SPECT imaging was negative for cardiac accumulation in 25 patients and positive in 28. Visual analysis of early phase whole body scan had an extremely significant capability to predict SPECT results; nevertheless, complete agreement was not reached. Visual analysis of late phase imaging showed slightly better results. Semiquantitative analysis of early phase images, namely heart to mediastinum ratio, performed better than semiquantitative analysis of late phase images. CONCLUSION: Visual analysis of [99mTc]Tc-DPD early phase whole body scan is promising in diagnosing cardiac amyloidosis; further studies are needed to confirm our results in different clinical scenarios. KEY POINTS: • Visual analysis of early phase planar imaging using [99mTc]Tc-DPD is accurate to diagnose cardiac amyloidosis and may be satisfactory at least in frail patients with high cardiac burden of amyloid fibrils.

The role of 18F-Fluorodeoxyglucose PET/CT in restaging patients with small cell lung cancer: a systematic review.

AIM: 18F-Fluorodeoxyglucose (FDG) PET imaging may play an important role in the restaging of patients with small-cell lung cancer (SCLC),, nevertheless, a systematic review of literature was still missing in this setting. The aim of this review was to summarize the evidence on literature regarding the utility of 18F-FDG PET imaging in restaging patients with SCLC. METHODS: A literature search was performed to retrieve original studies using 18F-FDG PET or 18F-FDG PET/computed tomography (CT) in a minimum of 10 patients with SCLC at restaging. RESULTS: The selected literature (17 studies) was discussed in four sections: detection rate, impact on management, prediction of prognosis and evaluation of the response to therapy. According to the literature, PET imaging may result in discordance with conventional imaging, mainly contrast-enhanced CT (ceCT), and detect additional lesions in a certain proportion of cases, leading to upstaging or downstaging. A variable level of disagreement between PET and conventional imaging has been reported also in the evaluation of response to therapy. A positive PET study is associated with shorter survival, especially in the presence of distant metastases. According to some studies, semiquantitative parameters are also inversely associated with overall survival and progression-free survival. Although the retrieved articles proved the utility of 18F-FDG PET imaging in each clinical setting, literature is still limited. CONCLUSIONS: This review encourages the use of 18F-FDG PET imaging, especially in conjunction with ceCT in recurrent SCLC patients. Further level I evidence is needed to further assess the diagnostic and prognostic capability of 18F-FDG PET/ceCT findings in SCLC.

Artificial Neural Networks in Cardiovascular Diseases and its Potential for Clinical Application in Molecular Imaging.

In medical imaging, Artificial Intelligence is described as the ability of a system to properly interpret and learn from external data, acquiring knowledge to achieve specific goals and tasks through flexible adaptation. The number of possible applications of Artificial Intelligence is also huge in clinical medicine and cardiovascular diseases. To describe for the first time in literature, the main results of articles about Artificial Intelligence potential for clinical applications in molecular imaging techniques, and to describe its advancements in cardiovascular diseases assessed with nuclear medicine imaging modalities. A comprehensive search strategy was used based on SCOPUS and PubMed databases. From all studies published in English, we selected the most relevant articles that evaluated the technological insights of AI in nuclear cardiology applications. Artificial Intelligence may improve patient care in many different fields, from the semi-automatization of the medical work, through the technical aspect of image preparation, interpretation, the calculation of additional factors based on data obtained during scanning, to the prognostic prediction and risk-- group selection. Myocardial implementation of Artificial Intelligence algorithms in nuclear cardiology can improve and facilitate the diagnostic and predictive process, and global patient care. Building large databases containing clinical and image data is a first but essential step to create and train automated diagnostic/prognostic models able to help the clinicians to make unbiased and faster decisions for precision healthcare.