Breast cancer (BC) is a heterogeneous malignancy that still represents the second cause of cancer-related death among women worldwide. Due to the heterogeneity of BC, the correct identification of valuable biomarkers able to predict tumor biology and the best treatment approaches are still far from clear. Although molecular imaging with positron emission tomography/computed tomography (PET/CT) has improved the characterization of BC, these methods are not free from drawbacks. In recent years, radiomics and artificial intelligence (AI) have been playing an important role in the detection of several features normally unseen by the human eye in medical images. The present review provides a summary of the current status of radiomics and AI in different clinical settings of BC. A systematic search of PubMed, Web of Science and Scopus was conducted, including all articles published in English that explored radiomics and AI analyses of PET/CT images in BC. Several studies have demonstrated the potential role of such new features for the staging and prognosis as well as the assessment of biological characteristics. Radiomics and AI features appear to be promising in different clinical settings of BC, although larger prospective trials are needed to confirm and to standardize this evidence.

The aim of this review is to provide a comprehensive overview of the existing literature concerning the applications of positron emission tomography (PET) radiomics in lung cancer patient candidates or those undergoing immunotherapy. Materials and Methods: A systematic review was conducted on databases and web sources. English-language original articles were considered. The title and abstract were independently reviewed to evaluate study inclusion. Duplicate, out-of-topic, and review papers, or editorials, articles, and letters to editors were excluded. For each study, the radiomics analysis was assessed based on the radiomics quality score (RQS 2.0). The review was registered on the PROSPERO database with the number CRD42023402302. Results: Fifteen papers were included, thirteen were qualified as using conventional radiomics approaches, and two used deep learning radiomics. The content of each study was different; indeed, seven papers investigated the potential ability of radiomics to predict PD-L1 expression and tumor microenvironment before starting immunotherapy. Moreover, two evaluated the prediction of response, and four investigated the utility of radiomics to predict the response to immunotherapy. Finally, two papers investigated the prediction of adverse events due to immunotherapy. Conclusions: Radiomics is promising for the evaluation of TME and for the prediction of response to immunotherapy, but some limitations should be overcome.

[¹⁸F]F-FDG (FDG) PET is emerging as a relevant diagnostic and prognostic tool in neuroendocrine neoplasms (NENs), as a simultaneous decrease in [⁶⁸Ga]Ga-DOTA peptides and increase in FDG uptake (the “flip-flop” phenomenon) occurs during the natural history of these tumors. The aim of this study was to evaluate the variations on FDG PET in NEN patients treated with two different schemes of radioligand therapy (RLT) and to correlate them with clinical–pathologic variables. A prospective evaluation of 108 lesions in 56 patients (33 males and 23 females; median age, 64.5 years) affected by NENs of various primary origins (28 pancreatic, 13 gastrointestinal, 9 bronchial, 6 unknown primary (CUP-NENs) and 1 pheochromocytoma) and grades (median Ki-67 = 9%) was performed. The patients were treated with RLT within the phase II clinical trial FENET-2016 (CTID: NCT04790708). RLT was offered for 32 patients with the MONO scheme (five cycles of [¹⁷⁷Lu]Lu-DOTATOC) and for 24 with the DUO scheme (three cycles of [¹⁷⁷Lu]Lu-DOTATOC alternated with two cycles of [⁹⁰Y]Y-DOTATOC). Variations in terms of the ΔSUVmax of a maximum of three target lesions per patient (58 for MONO and 50 for DUO RLT) were assessed between baseline and 3 months post-RLT FDG PET. In patients with negative baseline FDG PET, the three most relevant lesions on [⁶⁸Ga]Ga-DOTA-peptide PET were assessed and matched on post-RLT FDG PET, to check for any possible changes in FDG avidity. Thirty-five patients (62.5%) had at least one pathological FDG uptake at the baseline scans, but the number was reduced to 29 (52%) after RLT. In the patients treated with DUO-scheme RLT, 20 out of 50 lesions were FDG positive before therapy, whereas only 14 were confirmed after RLT (p = 0.03). Moreover, none of the 30 FDG-negative lesions showed an increased FDG uptake after RLT. The lesions of patients with pancreatic and CUP-NENs treated with the DUO scheme demonstrated a significant reduction in ΔSUVmax in comparison to those treated with MONO RLT (p = 0.03 and p = 0.04, respectively). Moreover, we found a mild positive correlation between the grading and ΔSUVmax in patients treated with the MONO scheme (r = 0.39, p < 0.02), while no evidence was detected for patients treated with the DUO scheme. Our results suggest that RLT, mostly with the DUO scheme, could be effective in changing NEN lesions’ glycometabolism, in particular, in patients affected by pancreatic and CUP-NENs, regardless of their Ki-67 index. Probably, associating [⁹⁰Y]Y-labelled peptides, which have high energy emission and a crossfire effect, and [¹⁷⁷Lu]Lu ones, characterized by a longer half-life and a safer profile for organs at risk, might represent a valid option in FDG-positive NENs addressed to RLT. Further studies are needed to validate our preliminary findings. In our opinion, FDG PET/CT should represent a potent tool for fully assessing a patient’s disease characteristics, both before and after RLT.

Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) is a strong prognostic factor in breast cancer (BC). The aim of this study was to investigate whether semiquantitative parameters derived from baseline [¹⁸F]Fluorodeoxyglucose ([¹⁸F]FDG) positron emission computed tomography/computed tomography (PET/CT) could predict pCR after NAC and survival outcomes in patients affected by different molecular subtypes of BC. We retrospectively retrieved patients from the databases of two Italian hospitals (Centre A: University Hospital of Ferrara; Centre B: University of Padua) meeting the following inclusion criteria: (1) diagnosis of BC; (2) history of NAC; (3) baseline [¹⁸F]FDG PET/CT performed before the first cycle of NAC; (4) available follow-up data (response after NAC and survival information). For each [¹⁸F]FDG PET/CT scan, semiquantitative parameters (SUVmax, SUVmean, MTV and TLG) related to the primary tumor (B), to the reference lesion for both axillary (N) and distant lymph node (DN), and to the whole-body burden of disease (WB) were evaluated. Patients enrolled were 133: 34 from centre A and 99 from centre B. Patients’ molecular subtypes were: 9 luminal A, 49 luminal B, 33 luminal B + HER-2, 10 HER-2 enriched, and 32 triple negative (TNBC). Luminal A and HER-2 enriched BC patients were excluded from the analysis due to the small sample size. pCR after NAC was achieved in 47 patients (41.2%). [¹⁸F]FDG PET/CT detected the primary tumor in 98.3% of patients and lymph node metastases were more frequently detected in Luminal B subgroup. Among Luminal B patients, median SUVmean_B values were significantly higher (p = 0.027) in responders (7.06 ± 5.9) vs. non-responders (4.4 ± 2.1) to NAC. Luminal B + HER-2 non-responders showed a statistically significantly higher median MTV_B (7.3 ± 4.2 cm³ vs. 3.5 ± 2.5 cm³; p = 0.003) and TLG_B (36.5 ± 24.9 vs. 18.9 ± 17.7; p = 0.025) than responders at baseline [¹⁸F]FDG PET/CT. None of the semiquantitative parameters predicted pCR after NAC in TNBC patients. However, among TNBC patients who achieved pCR after NAC, 4 volumetric parameters (MTV_B, TLG_B, MTV_WB and TLG_WB) were significantly higher in patients dead at follow-up. If confirmed in further studies, these results could open up a widespread use of [¹⁸F]FDG PET/CT as a baseline predictor of response to NAC in luminal B and luminal B + HER-2 patients and as a prognostic tool in TNBC.

AIM: To examine the role of [18F]FDG PET/CT for assessing response to immunotherapy in patients with some solid tumors. METHODS: Data recorded in a multicenter (n = 17), retrospective database between March and November 2021 were analyzed. The sample included patients with a confirmed diagnosis of a solid tumor who underwent serial [18F]FDG PET/CT (before and after one or more cycles of immunotherapy), who were >18 years of age, and had a follow-up of at least 12 months after their first PET/CT scan. Patients enrolled in clinical trials or without a confirmed diagnosis of cancer were excluded. The authors classified cases as having a complete or partial metabolic response to immunotherapy, or stable or progressive metabolic disease, based on a visual and semiquantitative analysis according to the EORTC criteria. Clinical response to immunotherapy was assessed at much the same time points as the serial PET scans, and both the obtained responses were compared. RESULTS: The study concerned 311 patients (median age: 67; range: 31–89 years) in all. The most common neoplasm was lung cancer (56.9%), followed by malignant melanoma (32.5%). Nivolumab was administered in 46.3%, and pembrolizumab in 40.5% of patients. Baseline PET and a first PET scan performed at a median 3 months after starting immunotherapy were available for all 311 patients, while subsequent PET scans were obtained after a median 6, 12, 16, and 21 months for 199 (64%), 102 (33%), 46 (15%), and 23 (7%) patients, respectively. Clinical response to therapy was recorded at around the same time points after starting immunotherapy for 252 (81%), 173 (56%), 85 (27%), 40 (13%), and 22 (7%) patients, respectively. After a median 18 (1–137) months, 113 (36.3%) patients had died. On Kaplan–Meier analysis, metabolic responders on the first two serial PET scans showed a better prognosis than non-responders, while clinical response became prognostically informative from the second assessment after starting immunotherapy onwards. CONCLUSIONS: [18F]FDG PET/CT could have a role in the assessment of response to immunotherapy in patients with some solid tumors. It can provide prognostic information and thus contribute to a patient’s appropriate treatment. Prospective randomized controlled trials are mandatory.

Background: ¹⁸F-Fluciclovine ([¹⁸F]FACBC) has been recently proposed as a synthetic radiolabeled amino acid for positron emission tomography (PET) imaging in patients with brain neoplasms. Our aim is to evaluate the diagnostic performance of [¹⁸F]FACBC PET in high-grade glioma (HGG) patients, taking into account the literature data. Methods: A comprehensive literature search was performed. We included original articles evaluating [¹⁸F]FACBC PET in the detection of HGG before therapy and for the suspicion of tumor recurrence. Pooled sensitivity, specificity, positive and negative likelihood ratios (LR+ and LR−), and diagnostic odds ratios (DOR), including 95% confidence intervals (95% CI), were measured. Statistical heterogeneity and publication bias were also assessed. Results: ten studies were included in the review and eight in the meta-analysis (113 patients). Regarding the identification of HGG, the sensitivity of [¹⁸F]FACBC PET ranged between 85.7% and 100%, with a pooled estimate of 92.9% (95% CI: 84.4–96.9%), while the specificity ranged from 50% to 100%, with a pooled estimate of 70.7% (95% CI: 47.5–86.5%). The pooled LR+, LR−, and DOR of [¹⁸F]FACBC PET were 2.5, 0.14, and 37, respectively. No significant statistical heterogeneity or publication bias were found. Conclusions: evidence-based data demonstrate the good diagnostic accuracy of [¹⁸F]FACBC PET for HGG detection. Due to the still limited data, further studies are warranted to confirm the promising role of [¹⁸F]FACBC PET in this context.