Purpose: Chemotherapy-induced cardiotoxicity is one of the main complications during and after cancer treatment. While echocardiography is the most used technique in clinical practice to evaluate left ventricular (LV) dysfunction, a multimodal approach is preferred for the early detection of anthracycline-induced cardiotoxicity. In this paper, an image processing tool allowing the qualitative and quantitative analysis of myocardial metabolic activity by [¹⁸F]fluorodeoxyglucose (FDG) positron emission tomography computed tomography (PET/CT) images, acquired routinely during and after cancer treatment, is presented. Methods: The methodology is based on cardiac single photon emission computed tomography image processing protocols used in clinical practice. LV polar maps are created, and quantitative regional values are calculated. The tool was validated in a study group of 24 patients with Hodgkin or non-Hodgkin lymphoma (HL and NHL, respectively) treated with anthracyclines. Staging, interim and end-of-treatment [¹⁸F]FDG PET/CT images were acquired and the presented tool was used to extract the quantitative metrics of LV metabolic activity. Results: Results show an overall increase of metabolic activity in the interim PET image acquired while on treatment compared to staging PET, which then decreased in the end-of-treatment scan. Positive correlation coefficients between staging and interim scans, and negative correlation coefficients between interim and end-of-treatment scans also support this finding. Metabolic changes occur predominantly in the septal region. Conclusion: The proposed methodology and presented software solution provides the capability to assess quantitatively myocardial metabolism acquired by routine [¹⁸F]FDG PET/CT scanning during cancer treatment for evaluating anthracycline-induced cardiotoxicity. The [¹⁸F]FDG PET/CT septal-lateral uptake ratio is proposed as a new quantitative measure of myocardial metabolism.

Cardiotoxicity refers to the damage induced by antineoplastic treatments, leading to various cardiovascular conditions. [¹⁸F]FDG PET radiomics analysis could provide relevant information on early onset changes occurring in cardiac metabolism of chemotherapy-induced cardiotoxicity. Patients’ sociodemographic data, cardiovascular risk factors, laboratory parameters, and left ventricle [¹⁸F]FDG PET radiomic features are analyzed. The H_Rad index for the quantification of the heterogeneity of the metabolic uptake patterns is proposed. Statistical analysis is performed by separating patients according to the diagnosis of cancer therapy-related cardiac dysfunction (CTRCD). Baseline, intermediate, and end-of-treatment scans are evaluated as separate groups. Overall, CTRCD+ patients show lower overall mean standardized uptake values (SUV_mean) compared to CTRCD− patients, with statistically significant differences between groups only observed in the intermediate PET study (p = 0.025). A total of 34 radiomic features show statistically significant differences between the CTRCD+ and CTRCD− groups in the intermediate imaging studies. In the CTRCD− group, greater overall heterogeneity of metabolic uptake is observed in the intermediate PET image compared to the CTRCD+ groups (p = 0.025). The assessment of CTRCD through [¹⁸F]FDG PET radiomics analysis could be a potential tool for the identification of a predisposition to the later development of cardiac complications after cardiotoxic treatment.

Purpose: Due to the high morbidity and mortality of infective endocarditis (IE), medical imaging techniques are combined to ensure a correct diagnosis. [¹⁸F]FDG PET/CT has demonstrated the ability to improve diagnostic accuracy compared with the conventional modified Duke criteria in patients with suspected IE, especially those with prosthetic valve infective endocarditis (PVIE). The aim of this study is to provide an adjunctive diagnostic tool to improve the diagnostic accuracy in cardiovascular infections, specifically PVIE. Methods: A segmentation tool to extract quantitative measures of [¹⁸F]FDG PET/CT image studies of prosthetic heart valve regions was developed and validated in 20 cases of suspected PVIE, of which 9 were confirmed. For that, Valvular Heterogeneity Index (VHI) and Ring-to-Center Ratio (RCR) were defined. Results: Results show an overall increase in the metabolic uptake of the prosthetic valve ring in the studies with confirmed PVIE diagnosis (SUV_max from 1.70 to 3.20; SUV_mean from 0.86 to 1.50). The VHI and RCR showed areas under the curve of 0.727 and 0.808 in the receiver operating characteristics curve analyses, respectively, for PVIE diagnosis. Mann–Whitney U tests showed statistically significant differences between groups for RCR (p = 0.02). Visual analyses and clinical reports were concordant with the extracted quantitative metrics. Conclusion: The proposed new method and presented software solution (CASSIA) provide the capability to assess quantitatively myocardial metabolism along the prosthetic valve region in routine [¹⁸F]FDG PET/CT scans for evaluating heart valve infectious processes. VHI and RCR are proposed as new potential adjunctive measures for PVIE diagnosis.

Evidence is emerging about the value of textural features as powerful outcome predictors in cancer lesions. The aim of this study is to evaluate the potential of [¹⁸F]FDG PET/CT conventional and textural parameters as survival predictors in patients with stage III and IV oropharyngeal cancer. The database includes 39 patients. Segmentation of the primary lesions was performed. A total of 48 features were extracted, comprising conventional parameters and textural features. A 2-year follow-up period to analyze the Overall Survival (OS) and Relapse-Free Survival (RFS) rates was defined. Kaplan–Meier and Cox proportional hazards regression analyses were computed. Higher TLG (p = 0.001) and Surface (p = 0.001) are significantly related to better OS in Cox regression analysis after multiple-testing correction. Higher GLZLM_ZLNU (p = 0.001) is significantly related to greater relapse rates in RFS Kaplan–Meier analysis after multiple-testing correction. Quantitative [¹⁸F]FDG PET/CT image features, especially the TLG, have been confirmed as predictors of OS and RFS. Textural features, such as GLZLM_ZLNU, demonstrated a potential predictive value for the OS and RFS of the patients. RFS analysis suggest stabilization of patients adhering to the treatment, showing no relapse events after 20 months of follow-up. [¹⁸F]FDG PET/CT is a useful tool for predicting prognosis after chemoradiation therapy of oropharyngeal cancer patients.

Although there have been crucial advancements in the diagnostic and treatment approaches, the mortality rate of infective endocarditis is still an ongoing challenge in clinical practice. [¹⁸F]FDG PET/CT imaging has recently proven its potential role in the early identification of prosthetic valve endocarditis (PVE). Due to radiomics’ rising applicability, recent studies exhibit promising outcomes in the clinical setting. The aim of the present study is the evaluation of potential radiomic-based biomarkers of non-attenuation-corrected (NAC) [¹⁸F]FDG PET images for the diagnosis of PVE. An adequate pre-processing and segmentation of the prosthetic ring metabolic activity were performed. A reproducibility analysis prior to the image-based biomarkers’ identification was conducted in terms of the intraclass correlation coefficient (ICC) derived from the variations in the radiomic extraction configurations (bin number and voxel size). After the reliability analysis, statistical analysis was performed by means of the Mann–Whitney U Test to study the differences between the PVE groups. Only p values < 0.05 after the Benjamini Hochberg correction procedure for multiple comparisons were considered statistically significant. Eight ML classification models for PVE classification based on radiomic features were evaluated. Overall, 45.2% and 95.7% of the radiomic features showed a consistency ICC above 0.82, demonstrating great reproducibility against variations in the bin number and interpolation thickness, respectively. Variations in interpolation thickness demonstrated great reproducibility in absolute agreement with 80.0% robust features, proving a non-dependency relationship with radiomic values. In the present study, the utility of potential radiomic-based biomarkers in the diagnosis of PVE in NAC [¹⁸F]FDG PET/CT images has been evaluated. Future studies will be required to validate the use of this technology as a valuable tool to support the current PVE diagnostic criteria.