Value of Dynamic Contrast-Enhanced MRI for Grade Group Prediction in Prostate Cancer: A Radiomics Pilot Study.

RATIONALE AND OBJECTIVES: To determine the role of dynamic contrast-enhanced (DCE) MRI-radiomics in predicting the International Society of Urological Pathology Grade Group (ISUP-GG) in therapy-naïve prostate cancer (PCa) patients. MATERIALS AND METHODS: In this ethics review board-approved retrospective study on two prospective clinical trials between 2017 and 2020, 73 men with suspected/confirmed PCa were included. All participants underwent multiparametric MRI. On MRI, dominant lesions (per PI-RADS) were identified. DCE-MRI radiomic features were extracted from the segmented volumes following the image biomarker standardisation initiative (IBSI) guidelines through 14 time points. Histopathology evaluation on the cognitive-fusion targeted biopsies was set as the reference standard. Univariate regression was done to evaluate potential predictors across all calculated features. Random forest imputation was used for multivariate modelling. RESULTS: 73 index lesions were reviewed. Histopathology revealed 28, 16, 13 and 16 lesions with ISUP-GG-Negative/1/2, ISUP-GG-3, ISUP-GG-4 and ISUP-GG-5, respectively. From the extracted features, total lesion enhancement (TLE), minimum enhancement intensity and Grey-Level Run Length Matrix (GLRLM) were the most significantly different parameters among ISUP-GGs (Neg/1/2 vs 3/4 vs 5). 16 features with significant cross-sectional associations with ISUP-GGs entered the multivariate analysis. The final DCE partitioning model used only four features (lesion sphericity, TLE, GLRLM and Grey-Level Zone Length Matrix). For the binarized diagnosis (ISUP-GG≤2 vs ISUP-GG>2), the accuracy reached 81%. CONCLUSION: DCE-MRI radiomics might be used as a non-invasive tool for aiding pathological grade group prediction in therapy-naïve PCa patients, potentially adding complementary information to PI-RADS for supporting tailored diagnostic pathways and treatment planning.

Predictive [18F]-FDG PET/CT-Based Radiogenomics Modelling of Driver Gene Mutations in Non-small Cell Lung Cancer.

RATIONALE AND OBJECTIVES: To investigate whether [18F]-FDG PET/CT-derived radiomics may correlate with driver gene mutations in non-small cell lung cancer (NSCLC) patients. MATERIALS AND METHODS: In this IRB-approved retrospective study, 203 patients with surgically treated NSCLC who underwent subsequent genomic analysis of the primary tumour at our institution between December 2004 and January 2014 were identified. Of those, 128 patients (mean age 62.4 ± 10.8 years; range: 35-84) received preoperative [18F]-FDG PET/CT as part of their initial staging and thus were included in the study. PET and CT image segmentation and feature extraction were performed semi-automatically with an open-source software platform (LIFEx, Version 6.30, lifexsoft.org). Molecular profiles using different next-generation sequencing (NGS) panels were collected from a web-based resource (cBioPortal.ca for Cancer genomics). Two statistical models were then built to evaluate the predictive ability of [18F]-FDG PET/CT-derived radiomics features for driver gene mutations in NSCLC. RESULTS: More than half (68/128, 53%) of all tumour samples harboured three or more gene mutations. Overall, 55% of tumour samples demonstrated a mutation in TP53, 26% of samples had alterations in KRAS and 17% in EGFR. Extensive statistical analysis resulted in moderate to good predictive ability. The highest Youden Index for TP53 was achieved using combined PET/CT features (0.70), for KRAS using PET features only (0.57) and for EGFR using CT features only (0.60). CONCLUSION: Our study demonstrated a moderate to good correlation between radiomics features and driver gene mutations in NSCLC, indicating increased predictive ability of genomic profiles using combined [18F]-FDG PET/CT-derived radiomics features.

Current Applications of PET/MR: Part II: Clinical Applications II.

Due to the major improvements in the hardware and image reconstruction algorithms, positron emission tomography/magnetic resonance imaging (PET/MR) is now a reliable state-of-the-art hybrid modality in medical practice. Currently, it can provide a broad range of advantages in preclinical and clinical imaging compared to single-modality imaging. In the second part of this review, we discussed the further clinical applications of PET/MR. In the chest, PET/MR has particular potential in the oncology setting, especially when utilizing ultrashort/zero echo time MR sequences. Furthermore, cardiac PET/MR can provide reliable information in evaluating myocardial inflammation, cardiac amyloidosis, myocardial perfusion, myocardial viability, atherosclerotic plaque, and cardiac masses. In gastrointestinal and hepato-pancreato-biliary malignancies, PET/MR is able to precisely detect metastases to the liver, being superior over the other imaging modalities. In genitourinary and gynaecology applications, PET/MR is a comprehensive diagnostic method, especially in prostate, endometrial, and cervical cancers. Its simultaneous acquisition has been shown to outperform other imaging techniques for the detection of pelvic nodal metastases and is also a reliable modality in radiation planning. Lastly, in haematologic malignancies, PET/MR can significantly enhance lymphoma diagnosis, particularly in detecting extra-nodal involvement. It can also comprehensively assess treatment-induced changes. Furthermore, PET/MR may soon become a routine in multiple myeloma management, being a one-stop shop for evaluating bone, bone marrow, and soft tissues.

Gastro-Esophageal Cancer: Can Radiomic Parameters from Baseline 18F-FDG-PET/CT Predict the Development of Distant Metastatic Disease?

We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to 2019 were evaluated retrospectively. Overall, 243 GEC patients (mean age = 64) were enrolled. Clinical, histopathology, and sarcopenia data were obtained, and primary tumor radiomics features were extracted. For classification (early-stage vs. advanced disease), the association of the studied parameters was evaluated. Various clinical and radiomics models were developed and assessed. Accuracy and area under the curve (AUC) were calculated. For OS prediction, univariable and multivariable Cox analyses were performed. The best model included PET/CT radiomics features, clinical data, and sarcopenia score (accuracy = 80%; AUC = 88%). For OS prediction, various clinical, CT, and PET features entered the multivariable analysis. Three clinical factors (advanced disease, age ≥ 70 and ECOG ≥ 2), along with one CT-derived and one PET-derived radiomics feature, retained their significance. Overall, 18F-FDG PET/CT radiomics seems to have a potential added value in identifying GEC patients with advanced disease and may enhance the performance of baseline clinical parameters. These features may also have a prognostic value for OS, improving the decision-making for GEC patients.

Eye-Related Adverse Events After I-131 Radioiodine Therapy: A Systematic Review of the Current Literature.

OBJECTIVE: Although I-131 is relatively safe, there is limited focus on probable eye-related side effects after radioactive iodine (RAI) therapy. Thus, we aimed to provide evidence for the adverse outcomes of I-131, exclusively in patients with thyroid cancer. METHODS: A systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was designed to examine the ocular complications of RAI therapy. Databases including PubMed, Scopus, and Web of Science were searched until October 2023 with specific thyroid neoplasms, ophthalmology and iodine terms. After thorough screening and review, relevant data were extracted. RESULTS: The database search yielded 3434 articles, which resulted in the final 28 eligible studies. These studies investigated ophthalmic symptoms following RAI therapy, classifying them as obstructive diseases (for example, nasolacrimal duct obstruction; median incidence rate: 6.8%), inflammatory symptoms (median incidence rate: 13%), and cataracts (median incidence rate: 2.5 and 5%). The most common time interval between RAI therapy and the onset of symptoms was within the first 12 months and then declined in the preceding years. A strong positive correlation was observed between higher I-131 doses of more than 100 to 150 mCi (3.7-5.55 GBq) and the risk of symptom development. Ages older than 45 also showed a significant association with nasolacrimal duct obstruction. CONCLUSION: The risk of ophthalmic complications is associated with various factors, including the administration of high I-131 doses, age of more than 45 years, and time to event within the first 12 months. Considering these conditions may help enhance patient care and prevent adverse outcomes that may limit patients' quality of life.

Comparison of Multiparametric MRI and the Combination of PSMA Plus MRI for the Intraprostatic Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis.

PURPOSE: The aim of this study was to perform a head-to-head comparison of multiparametric MRI (mpMRI) and the combination of prostate-specific membrane antigen (PSMA) PET plus MRI (PSMA + MRI) for detecting intraprostatic clinically significant prostate cancer (csPCa). PATIENTS AND METHODS: Relevant databases were searched through November 2023. Only studies directly comparing mpMRI and PSMA + MRI (PET/MRI or PET/CT + mpMRI) were included. A meta-analysis with a random-effects model was used to estimate pooled sensitivity, specificity, and area under the curve for each approach. RESULTS: A total of 19 studies were included. On a patient-level analysis, PSMA + MRI had higher sensitivity (9 studies) than mpMRI for csPCa detection (96% [95% confidence interval (CI): 92%, 98%] vs 89% [95% CI: 81%, 94%]; P = 0.04). The patient-level specificity (4 studies) of PSMA + MRI was 55% (95% CI: 31%-76%) compared with 50% (95% CI: 44%-57%) of mpMRI ( P = 0.67). Region-level sensitivity (10 studies) was 85% (95% CI: 74%-92%) for PSMA + MRI and 71% (95% CI: 58%-82%) for mpMRI ( P = 0.09), whereas specificity (4 studies) was 87% (95% CI: 76%-94%) and 90% (95% CI: 82%-95%), respectively ( P = 0.59). Lesion-level sensitivity and specificity were similar between modalities with pooled data from less than 4 studies. CONCLUSIONS: PSMA + MRI had superior pooled sensitivity and similar specificity for the detection of csPCa compared with mpMRI in this meta-analysis of head-to-head studies.

A Systematic Review and Meta-Analysis on the Diagnostic and Prognostic Values of 18F-FDG PET in Uveal Melanoma and Its Hepatic Metastasis.

In this systematic review and meta-analysis (PRISMA-compliant), we tried to investigate diagnostic and prognostic values of 18F-FDG PET in uveal melanoma. A systematic search was conducted on the main medical literature databases to include studies that evaluated 18F-FDG PET as the imaging modality to evaluate patients with uveal melanoma. Overall, 27 studies were included. Twelve had data about the detection rate of 18F-FDG PET in primary intra-ocular tumours. The pooled sensitivity was 45% (95%CI: 41-50%). Furthermore, studies showed that the larger the primary tumour, the higher its uptake. Among the included studies, 13 assessed 18F-FDG PET in detecting metastasis. The pooled sensitivity and specificity were 96% (95%CI: 81-99%) and 100% (95%CI: 94-100%), respectively. Regarding liver metastasis, they were 95% (95%CI: 79-99%) and 100% (95%CI: 91-100%), respectively. Noteworthy, the level of 18F-FDG uptake was a strong predictor of patient survival. Lastly, 18F-FDG PET could characterise lesions from the histopathology perspective, distinguishing high-risk from low-risk diseases. Overall, although not reliable in detecting primary intra-ocular tumours, 18F-FDG PET is highly accurate for diagnosing metastatic uveal melanomas. It can also be a highly valuable modality in terms of patient prognostication. Thus, 18F-FDG PET can be recommended in patients diagnosed with uveal melanoma to enhance decision-making and patient management.

The [18F]F-FDG PET/CT Radiomics Classifier of Histologic Subtypes and Anatomical Disease Origins across Various Malignancies: A Proof-of-Principle Study.

We aimed to investigate whether [18F]F-FDG-PET/CT-derived radiomics can classify histologic subtypes and determine the anatomical origin of various malignancies. In this IRB-approved retrospective study, 391 patients (age = 66.7 ± 11.2) with pulmonary (n = 142), gastroesophageal (n = 128) and head and neck (n = 121) malignancies were included. Image segmentation and feature extraction were performed semi-automatically. Two models (all possible subset regression [APS] and recursive partitioning) were employed to predict histology (squamous cell carcinoma [SCC; n = 219] vs. adenocarcinoma [AC; n = 172]), the anatomical origin, and histology plus anatomical origin. The recursive partitioning algorithm outperformed APS to determine histology (sensitivity 0.90 vs. 0.73; specificity 0.77 vs. 0.65). The recursive partitioning algorithm also revealed good predictive ability regarding anatomical origin. Particularly, pulmonary malignancies were identified with high accuracy (sensitivity 0.93; specificity 0.98). Finally, a model for the synchronous prediction of histology and anatomical disease origin resulted in high accuracy in determining gastroesophageal AC (sensitivity 0.88; specificity 0.92), pulmonary AC (sensitivity 0.89; specificity 0.88) and head and neck SCC (sensitivity 0.91; specificity 0.92). Adding PET-features was associated with marginal incremental value for both the prediction of histology and origin in the APS model. Overall, our study demonstrated a good predictive ability to determine patients' histology and anatomical origin using [18F]F-FDG-PET/CT-derived radiomics features, mainly from CT.

Current Applications of PET/MR: Part I: Technical Basics and Preclinical/Clinical Applications.

Positron emission tomography/magnetic resonance (PET/MR) imaging has gone through major hardware improvements in recent years, making it a reliable state-of-the-art hybrid modality in clinical practice. At the same time, image reconstruction, attenuation correction, and motion correction algorithms have significantly evolved to provide high-quality images. Part I of the current review discusses technical basics, pre-clinical applications, and clinical applications of PET/MR in radiation oncology and head and neck imaging. PET/MR offers a broad range of advantages in preclinical and clinical imaging. In the preclinic, small and large animal-dedicated devices were developed, making PET/MR capable of delivering new insight into animal models in diseases and facilitating the development of methods that inform clinical PET/MR. Regarding PET/MR's clinical applications in radiation medicine, PET and MR already play crucial roles in the radiotherapy process. Their combination is particularly significant as it can provide molecular and morphological characteristics that are not achievable with other modalities. In addition, the integration of PET/MR information for therapy planning with linear accelerators is expected to provide potentially unique biomarkers for treatment guidance. Furthermore, in clinical applications in the head and neck region, it has been shown that PET/MR can be an accurate modality in head and neck malignancies for staging and resectability assessment. Also, it can play a crucial role in diagnosing residual or recurrent diseases, reliably distinguishing from oedema and fibrosis. PET/MR can furthermore help with tumour characterization and patient prognostication. Lastly, in head and neck carcinoma of unknown origin, PET/MR, with its diagnostic potential, may obviate multiple imaging sessions in the near future.

Diagnostic performance of deep learning models versus radiologists in COVID-19 pneumonia: A systematic review and meta-analysis.

PURPOSE: Although several studies have compared the performance of deep learning (DL) models and radiologists for the diagnosis of COVID-19 pneumonia on CT of the chest, these results have not been collectively evaluated. We performed a meta-analysis of original articles comparing the performance of DL models versus radiologists in detecting COVID-19 pneumonia. METHODS: A systematic search was conducted on the three main medical literature databases, Scopus, Web of Science, and PubMed, for articles published as of February 1st, 2023. We included original scientific articles that compared DL models trained to detect COVID-19 pneumonia on CT to radiologists. Meta-analysis was performed to determine DL versus radiologist performance in terms of model sensitivity and specificity, taking into account inter and intra-study heterogeneity. RESULTS: Twenty-two articles met the inclusion criteria. Based on the meta-analytic calculations, DL models had significantly higher pooled sensitivity (0.933 vs. 0.829, p < 0.001) compared to radiologists with similar pooled specificity (0.905 vs. 0.897, p = 0.746). In the differentiation of COVID-19 versus community-acquired pneumonia, the DL models had significantly higher sensitivity compared to radiologists (0.915 vs. 0.836, p = 0.001). CONCLUSIONS: DL models have high performance for screening of COVID-19 pneumonia on chest CT, offering the possibility of these models for augmenting radiologists in clinical practice.

Pre-treatment 68 Ga-PSMA-11 PET/CT Prognostic Value in Predicting Response to 177Lu-PSMA-I&T Therapy and Patient Survival.

PURPOSE: To assess the prognostic value of pre-treatment [68Ga]Ga-PSMA-11 PET/CT and other baseline clinical characteristics in predicting prostate cancer (PCa) patients response to [177Lu]Lu-PSMA (PSMA-I&T), as well as patient survival. PROCEDURES: In this retrospective study, 81 patients who received [177Lu]Lu-PSMA-I&T between October 2018 and January 2023 were reviewed. Eligible patients had metastatic castration-resistant PCa, underwent pre-treatment [68Ga]Ga-PSMA-11 PET/CT, and had serum prostate-specific antigen (PSA) levels available. On PET/CT images, SUVmax, SULmax, SUVpeak, and SULpeak of the most-avid tumoral lesion, as well as SUVmean of the parotid gland (P-SUVmean) and liver (L-SUVmean), were measured. Also, whole-body PSMA tumour volume (PSMA-TV) and total lesion PSMA (TL-PSMA) were calculated. To interpret treatment response after [177Lu]Lu-PSMA-I&T, a composite of PSA values and [68Ga]Ga-PSMA-11 PET/CT findings were considered. The outcomes were dichotomised into progressive versus controlled (stable disease or partial response) disease. Then, the association of baseline parameters with patient response was evaluated. Also, survival analyses were performed to assess baseline parameters in predicting overall survival. RESULTS: Sixty patients (age:73 ± 8, PSA:185 ± 371) were included. Patients received at least one cycle of [177Lu]Lu-PSMA therapy (median = 4). Overall, half of the patients showed disease progression. In the progressive versus controlled disease evaluation, the highest SULmax, as well as SUVmax and SULmax to both backgrounds (L-SUVmean and P-SUVmean), were significantly correlated with the outcome (p-values < 0.05). In the multivariate analysis, only SULmax to the L-SUVmean remained significant (p-value = 0.038). The best cut-off was 8 (AUC = 0.71). With a median follow-up of 360 days, 11 mortal events were documented. In the multivariate survival analysis, only SULmax to P-SUVmean (cut-off = 2.4; p-value = 0.043) retained significance (hazard ratio = 4.0). CONCLUSIONS: A greater level of PSMA uptake, specifically higher tumour-to-background uptake in the hottest lesion, may hold substantial prognostic significance, considering both [177Lu]Lu-PSMA-I&T response and patient survival. These ratios may have the potential to be used for PCa patient selection for radioligand therapy.

Application of Artificial Intelligence in Oncologic Molecular PET-Imaging: A Narrative Review on Beyond [18F]F-FDG Tracers Part II. [18F]F-FLT, [18F]F-FET, [11C]C-MET and Other Less-Commonly Used Radiotracers.

Following the previous part of the narrative review on artificial intelligence (AI) applications in positron emission tomography (PET) using tracers rather than 18F-fluorodeoxyglucose ([18F]F-FDG), in this part we review the impact of PET-derived radiomics data on the diagnostic performance of other PET radiotracers, 18F-O-(2-fluoroethyl)-L-tyrosine ([18F]F-FET), 18F-Fluorothymidine ([18F]F-FLT) and 11C-Methionine ([11C]C-MET). [18F]F-FET-PET, using an artificial amino acid taken up into upregulated tumoral cells, showed potential in lesion detection and tumor characterization, especially with its ability to reflect glioma heterogeneity. [18F]F-FET-PET-derived textural features appeared to have the potential to reveal considerable information for accurate delineation for guiding biopsy and treatment, differentiate between low-grade and high-grade glioma and related wild-type genotypes, and distinguish pseudoprogression from true progression. In addition, models built using clinical parameters and [18F]F-FET-PET-derived radiomics features showed acceptable results for survival stratification of glioblastoma patients. [18F]F-FLT-PET-based characteristics also showed potential in evaluating glioma patients, correlating with Ki-67 and patient prognosis. AI-based PET-volumetry using this radiotracer as a proliferation marker also revealed promising preliminary results in terms of guide-targeting bone marrow-preserving adaptive radiation therapy. Similar to [18F]F-FET, the other amino acid tracer which reflects cellular proliferation, [11C]C-MET, has also shown acceptable performance in predicting tumor grade, distinguishing brain tumor recurrence from radiation necrosis, and treatment monitoring by PET-derived radiomics models. In addition, PET-derived radiomics features of various radiotracers such as [18F]F-DOPA, [18F]F-FACBC, [18F]F-NaF, [68Ga]Ga-CXCR-4 and [18F]F-FMISO may also provide useful information for tumor characterization and predict of disease outcome. In conclusion, AI using tracers beyond [18F]F-FDG could improve the diagnostic performance of PET-imaging for specific indications and help clinicians in their daily routine by providing features that are often not detectable by the naked eye.

SPECT/CT, PET/CT, and PET/MRI for Response Assessment of Bone Metastases.

Recent developments in hybrid SPECT/CT systems and the use of cadmium-zinc-telluride (CZT) detectors have improved the diagnostic accuracy of bone scintigraphy. These advancements have paved the way for novel quantitative approaches to accurate and reproducible treatment monitoring of bone metastases. PET/CT imaging using [18F]F-FDG and [18F]F-NaF have shown promising clinical utility in bone metastases assessment and monitoring response to therapy and prediction of treatment response in a broad range of malignancies. Additionally, specific tumor-targeting tracers like [99mTc]Tc-PSMA, [68Ga]Ga-PSMA, or [11C]C- or [18F]F-Choline revealed high diagnostic performance for early assessment and prognostication of bone metastases, particularly in prostate cancer. PET/MRI appears highly accurate imaging modality, but has associated limitations notably, limited availability, more complex logistics and high installation costs. Advances in artificial intelligence (Al) seem to improve the accuracy of imaging modalities and provide an assistant role in the evaluation of treatment response of bone metastases.

Diagnostic Performance of [18F]F-FDG Positron Emission Tomography (PET) in Non-Ophthalmic Malignant Melanoma: A Systematic Review and Meta-Analysis of More Than 10,000 Melanoma Patients.

We described the diagnostic performance of [18F]F-FDG-PET in malignant melanoma by conducting a comprehensive systematic review and meta-analysis of the existing literature. The study was designed following PRISMA-DTA. Original articles with adequate crude data for meta-analytic calculations that evaluated [18F]F-FDG-PET and compared it with a valid reference standard were considered eligible. The pooled measurements were calculated based on the data level (patient/lesion-based). Regarding sub-groups, diagnostic performances were calculated for local, regional and distant involvement. The bivariate model was employed to calculate sensitivity and specificity. The initial search resulted in 6678 studies. Finally, 100 entered the meta-analysis, containing 82 patient-based (10,403 patients) and 32 lesion-based (6188 lesions) datasets. At patient level, overall, [18F]F-FDG-PET had pooled sensitivity and specificity of 81% (95%CI: 73-87%) and 92% (95%CI: 90-94%), respectively. To detect regional lymph node metastasis, the pooled sensitivity and specificity were 56% (95%CI: 40-72%) and 97% (95%CI: 94-99%), respectively. To detect distant metastasis, they were 88% (95%CI: 81-93%) and 94% (95%CI: 91-96%), respectively. At lesion level, [18F]F-FDG-PET had a pooled sensitivity and specificity of 70% (95%CI: 57-80%) and 94% (95%CI: 88-97%), respectively. Thus, [18F]F-FDG-PET is a valuable diagnostic modality for melanoma assessment. It was accurate in various clinical scenarios. However, despite its high specificity, it showed low sensitivity in detecting regional lymph node metastasis and could not replace lymph node biopsy.

Diagnostic value of [ 68 Ga]Ga-Pentixafor PET/CT in malignant melanoma: a pilot study.

OBJECTIVE: To evaluate the diagnostic value of [ 68 Ga] Ga-Pentixafor in malignant melanoma patients. METHODS: In this prospective study, patients with histology-proven melanoma were included and underwent [ 18 F]fluoro-D-glucose ([ 18 F]FDG) and [ 68 Ga] Ga-Pentixafor PET/computed tomography (CT) within a week. Suspicious lesions were interpreted as benign vs. malignant, and the corresponding semi-quantitative PET/CT parameters were recorded and compared. RESULTS: Twelve consecutive melanoma patients (mean age: 60 ±â€…6) were included. Two patients were referred for initial staging, two for detecting recurrence and eight for evaluating the extent of metastases. Overall, [ 18 F]FDG PET/CT showed 236 tumoral lesions, including two primary tumors, two recurrent lesions, 29 locoregional metastases and 203 distant metastases. In [ 68 Ga]Ga-Pentixafor PET/CT, 101 tumoral lesions were detected, including two primary tumors, one recurrence, 16 locoregional metastases and 82 distant metastases. Notably, a documented brain metastasis was only visualized on [ 68 Ga]Ga-Pentixafor PET/CT images. Compared with [ 18 F]FDG, [ 68 Ga]Ga-Pentixafor PET/CT provided a 42% detection rate. Regarding semi-quantitative measures, the intensity of uptake and tumor-to-background ratios were significantly lower on [ 68 Ga]Ga-Pentixafor PET/CT [average maximum standard uptake value (SUV max ) of 2.72 ±â€…1.33 vs. 11.41 ±â€…14.79; P value <0.001 and 1.17 ±â€…0.53 vs. 5.32 ±â€…7.34; P value <0.001, respectively]. CONCLUSION: When comparing [ 68 Ga]Ga-Pentixafor PET/CT with [ 18 F]FDG PET/CT, not only did [ 68 Ga]Ga-Pentixafor PET/CT detect fewer lesions, but the intensity of uptake and the TBRs were also lower on [ 68 Ga]Ga-Pentixafor PET/CT. Thus, our results may indicate a limited potential of this novel tracer in cutaneous melanoma patients compared to [ 18 F]FDG PET/CT. Given the lower TBRs, applying this radiotracer in radioligand therapies is also questionable.

Diagnostic performance of whole-body [18F]FDG PET/MR in cancer M staging: A systematic review and meta-analysis.

OBJECTIVES: To calculate the pooled diagnostic performances of whole-body [18F]FDG PET/MR in M staging of [18F]FDG-avid cancer entities. METHODS: A diagnostic meta-analysis was conducted on the [18F]FDG PET/MR in M staging, including studies: (1) evaluated [18F]FDG PET/MR in detecting distant metastasis; (2) compared[ 18F]FDG PET/MR with histopathology, follow-up, or asynchronous multimodality imaging as the reference standard; (3) provided data for the whole-body evaluation; (4) provided adequate data to calculate the meta-analytic performances. Pooled performances were calculated with their confidence interval. In addition, forest plots, SROC curves, and likelihood ratio scatterplots were drawn. All analyses were performed using STATA 16. RESULTS: From 52 eligible studies, 2289 patients and 2072 metastases were entered in the meta-analysis. The whole-body pooled sensitivities were 0.95 (95%CI: 0.91-0.97) and 0.97 (95%CI: 0.91-0.99) at the patient and lesion levels, respectively. The pooled specificities were 0.99 (95%CI: 0.97-1.00) and 0.97 (95%CI: 0.90-0.99), respectively. Additionally, subgroup analyses were performed. The calculated pooled sensitivities for lung, gastrointestinal, breast, and gynecological cancers were 0.90, 0.93, 1.00, and 0.97, respectively. The pooled specificities were 1.00, 0.98, 0.97, and 1.00, respectively. Furthermore, the pooled sensitivities for non-small cell lung, colorectal, and cervical cancers were 0.92, 0.96, and 0.86, respectively. The pooled specificities were 1.00, 0.95, and 1.00, respectively. CONCLUSION: [18F]FDG PET/MR was a highly accurate modality in M staging in the reported [18F]FDG-avid malignancies. The results showed high sensitivity and specificity in each reviewed malignancy type. Thus, our findings may help clinicians and patients to be confident about the performance of [18F]FDG PET/MR in the clinic. CLINICAL RELEVANCE STATEMENT: Although [18F]FDG PET/MR is not a routine imaging technique in current guidelines, mostly due to its availability and logistic issues, our findings might add to the limited evidence regarding its performance, showing a sensitivity of 0.95 and specificity of 0.97. KEY POINTS: • The whole-body [18F]FDG PET/MR showed high accuracy in detecting distant metastases at both patient and lesion levels. • The pooled sensitivities were 95% and 97% and pooled specificities were 99% and 97% at patient and lesion levels, respectively. • The results suggested that 18F-FDG PET/MR was a strong modality in the exclusion and confirmation of distant metastases.

Application of Artificial Intelligence in Oncologic Molecular PET-Imaging: A Narrative Review on Beyond [18F]F-FDG Tracers - Part I. PSMA, Choline, and DOTA Radiotracers.

Artificial intelligence (AI) has evolved significantly in the past few decades. This thriving trend has also been seen in medicine in recent years, particularly in the field of imaging. Machine learning (ML), deep learning (DL), and their methods (eg, SVM, CNN), as well as radiomics, are the terminologies that have been introduced to this field and, to some extent, become familiar to the expert clinicians. PET is one of the modalities that has been enhanced via these state-of-the-art algorithms. This robust imaging technique further merged with anatomical modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), to provide reliable hybrid modalities, PET/CT and PET/MRI. Applying AI-based algorithms on the different components (PET, CT, and MRI) has resulted in promising results, maximizing the value of PET imaging. However, [18F]F-FDG, the most commonly utilized tracer in molecular imaging, has been mainly in the spotlight. Thus, we aimed to look into the less discussed tracers in this review, moving beyond [18F]F-FDG. The novel non-[18F]F-FDG agents also showed to be valuable in various clinical tasks, including lesion detection and tumor characterization, accurate delineation, and prognostic impact. Regarding prostate patients, PSMA-based models were highly accurate in determining tumoral lesions' location and delineating them, particularly within the prostate gland. However, they also could assess whole-body images to detect extra-prostatic lesions in a patient automatically. Considering the prognostic value of prostate-specific membrane antigen (PSMA) PET using AI, it could predict response to treatment and patient survival, which are crucial in patient management. Choline imaging, another non-[18F]F-FDG tracer, similarly showed acceptable results that may be of benefit in the clinic, though the current evidence is significantly more limited than PSMA. Lastly, different subtypes of DOTA ligands were found to be valuable. They could diagnose tumoral lesions in challenging sites and even predict histopathology grade, being a highly advantageous noninvasive tool. In conclusion, the current limited investigations have shown promising results, leading us to a bright future for AI in molecular imaging beyond [18F]F-FDG.

Impact of the COVID-19 Pandemic on Staging Oncologic PET/CT Imaging and Patient Outcome in a Public Healthcare Context: Overview and Follow Up of the First Two Years of the Pandemic.

To assess the impact of the COVID-19 pandemic on the diagnosis, staging and outcome of a selected population throughout the first two years of the pandemic, we evaluated oncology patients undergoing PET/CT at our institution. A retrospective population of lung cancer, melanoma, lymphoma and head and neck cancer patients staged using PET/CT during the first 6 months of the years 2019, 2020 and 2021 were included for analysis. The year in which the PET was performed was our exposure variable, and our two main outcomes were stage at the time of the PET/CT and overall survival (OS). A total of 1572 PET/CTs were performed for staging purposes during the first 6 months of 2019, 2020 and 2021. The median age was 66 (IQR 16), and 915 (58%) were males. The most prevalent staged cancer was lung cancer (643, 41%). The univariate analysis of staging at PET/CT and OS by year of PET/CT were not significantly different. The multivariate Cox regression of non-COVID-19 significantly different variables at univariate analysis and the year of PET/CT determined that lung cancer (HR 1.76 CI95 1.23-2.53, p < 0.05), stage III (HR 3.63 CI95 2.21-5.98, p < 0.05), stage IV (HR 11.06 CI95 7.04-17.36, p < 0.05) and age at diagnosis (HR 1.04 CI95 1.02-1.05, p < 0.05) had increased risks of death. We did not find significantly higher stages or reduced OS when assessing the year PET/CT was performed. Furthermore, OS was not significantly modified by the year patients were staged, even when controlled for non-COVID-19 significant variables (age, type of cancer, stage and gender).

Impact of 18F-DCFPyL PET/MRI in Selecting Men With Low-/Intermediate-Risk Prostate Cancer for Focal Ablative Therapies.

PURPOSE: To compare the diagnostic performance of multiparametric (mp) MRI to 18F-DCFPyL PET/MRI for detecting clinically significant (cs) prostate cancer (PCa) in men with low-/intermediate-risk PCa being considered for focal ablative therapy (FT), using 2 interpretation schemes, and to assess the rate of exclusion from FT for each modality. METHODS: This prospective study evaluated men with low- or intermediate-risk PCa, potential candidates for FT based on initial biopsy as per institutional protocol, who underwent 18F-DCFPyL PET/MRI. Each modality (mpMRI, PET/MRI using PROMISE classification [PET/MRI PROMISE], and PET/MRI considering any focal lesion on PET as positive [PETFL/MRI]) was assessed independently. All suspicious lesions underwent PET/MRI-ultrasound fusion biopsies. Diagnostic performances were calculated and compared using the exact binomial test on paired proportions. RESULTS: Thirty-four men (median age, 64 years; interquartile range, 60-70 years) were included. Overall, 40 of 67 lesions (60%) identified on mpMRI and/or PET/MRI were malignant, and 34 of 40 lesions (85%) were csPCa (≥6 mm ISUP [International Society of Urological Pathology Grade Group] GG1 or ISUP-GG ≥2). On lesion-level analysis, for detecting csPCa, sensitivity appeared higher for PETFL/MRI than mpMRI and PET/MRI PROMISE (97% vs 76% and 79%, respectively [P = 0.02 and 0.03]), whereas specificity was lower (30% vs 85% and 88%, respectively [P < 0.001]). The calculated overall accuracy rates for PETFL/MRI, mpMRI, and PET/MRI PROMISE were 64%, 81%, and 84%, respectively. PETFL/MRI, mpMRI, and PET/MRI PROMISE excluded 10 of 34 (29%), 7 of 34 (21%), and 6 of 34 (18%) men from FT, respectively. CONCLUSIONS: 18F-DCFPyL PET/MRI excluded nearly 30% of patients with low-/intermediate-risk PCa from FT, with a potential role in decreasing selection failure. Compared with mpMRI, PET/MRI had a higher sensitivity for detecting csPCa in men who were candidates for FT.ClinicalTrials.gov identifier NCT03149861.

Evaluation of MR anatomically-guided PET reconstruction using a convolutional neural network in PSMA patients.

Background. Recently, approaches have utilized the superior anatomical information provided by magnetic resonance imaging (MRI) to guide the reconstruction of positron emission tomography (PET). One of those approaches is the Bowsher's prior, which has been accelerated lately with a convolutional neural network (CNN) to reconstruct MR-guided PET in the imaging domain in routine clinical imaging. Two differently trained Bowsher-CNN methods (B-CNN0 and B-CNN) have been trained and tested on brain PET/MR images with non-PSMA tracers, but so far, have not been evaluated in other anatomical regions yet.Methods. A NEMA phantom with five of its six spheres filled with the same, calibrated concentration of 18F-DCFPyL-PSMA, and thirty-two patients (mean age 64 ± 7 years) with biopsy-confirmed PCa were used in this study. Reconstruction with either of the two available Bowsher-CNN methods were performed on the conventional MR-based attenuation correction (MRAC) and T1-MR images in the imaging domain. Detectable volume of the spheres and tumors, relative contrast recovery (CR), and background variation (BV) were measured for the MRAC and the Bowsher-CNN images, and qualitative assessment was conducted by ranking the image sharpness and quality by two experienced readers.Results. For the phantom study, the B-CNN produced 12.7% better CR compared to conventional reconstruction. The small sphere volume (<1.8 ml) detectability improved from MRAC to B-CNN by nearly 13%, while measured activity was higher than the ground-truth by 8%. The signal-to-noise ratio, CR, and BV were significantly improved (p< 0.05) in B-CNN images of the tumor. The qualitative analysis determined that tumor sharpness was excellent in 76% of the PET images reconstructed with the B-CNN method, compared to conventional reconstruction.Conclusions. Applying the MR-guided B-CNN in clinical prostate PET/MR imaging improves some quantitative, as well as qualitative imaging measures. The measured improvements in the phantom are also clearly translated into clinical application.