Composite Prediction Score to Interpret Bone Focal Uptake in Hormone-Sensitive Prostate Cancer Patients Imaged with [18F]PSMA-1007 PET/CT.

Unspecific bone uptake (UBU) related to [18F]PSMA-1007 PET/CT imaging represents a clinical challenge. We aimed to assess whether a combination of clinical, biochemical, and imaging parameters could predict skeletal metastases in patients with [18F]PSMA-1007 bone focal uptake, aiding in result interpretation. Methods: We retrospectively analyzed [18F]PSMA-1007 PET/CT performed in hormone-sensitive prostate cancer (PCa) patients at 3 tertiary-level cancer centers. A fourth center was involved in performing an external validation. For each, a volume of interest was drawn using a threshold method to extract SUVmax, SUVmean, PSMA tumor volume, and total lesion PSMA. The same volume of interest was applied to CT images to calculate the mean Hounsfield units (HUmean) and maximum Hounsfield units. Clinical and laboratory data were collected from electronic medical records. A composite reference standard, including follow-up histopathology, biochemistry, and imaging data, was used to distinguish between PCa bone metastases and UBU. PET readers with less (n = 2) or more (n = 2) experience, masked to the reference standard, were asked to visually rate a subset of focal bone uptake (n = 178) as PCa metastases or not. Results: In total, 448 bone [18F]PSMA-1007 focal uptake specimens were identified in 267 PCa patients. Of the 448 uptake samples, 188 (41.9%) corresponded to PCa metastases. Ongoing androgen deprivation therapy at PET/CT (P < 0.001) with determination of SUVmax (P < 0.001) and HUmean (P < 0.001) independently predicted bone metastases. A composite prediction score, the bone uptake metastatic probability (BUMP) score, achieving an area under the receiver-operating-characteristic curve (AUC) of 0.87, was validated through a 10-fold internal and external validation (n = 89 bone uptake, 51% metastatic; AUC, 0.92). The BUMP score's AUC was significantly higher than that of HUmean (AUC, 0.62) and remained high among lesions with HUmean in the first tertile (AUC, 0.80). A decision-curve analysis showed a higher net benefit with the score. Compared with the visual assessment, the BUMP score provided added value in terms of specificity in less-experienced PET readers (88% vs. 54%, P < 0.001). Conclusion: The BUMP score accurately distinguished UBU from bone metastases in PCa patients with [18F]PSMA-1007 focal bone uptake at PET imaging, offering additional value compared with the simple assessment of the osteoblastic CT correlate. Its use could help clinicians interpret imaging results, particularly those with less experience, potentially reducing the risk of patient overstaging.

End of induction [18F]FDG PET is prognostic for progression-free survival and overall survival in follicular lymphoma patients enrolled in the FOLL12 trial.

PURPOSE: To evaluate the reliability of the Deauville score (DS) in therapy response assessment and to define the prognostic value of the metabolic response of end of induction (EOI) [18F]FDG PET (PET) in follicular lymphoma patients. METHODS: Adult patients with untreated grade 1-3a FL/ stage II-IV enrolled in the multicentre, prospective, phase III FOLL12 trial (NCT02063685) were randomized to receive standard immunochemotherapy followed by rituximab maintenance (standard arm) versus standard immunochemotherapy followed by response-adapted post-induction management (experimental arm). Baseline and EOI PET were mandatory for the study. All PET scans were centralized on the WIDEN® platform and classified according to DS in a blind independent central review. DS1-3 was considered negative (CMR), whereas DS4-5 was considered positive (not CMR). The primary endpoint was PFS. The main secondary endpoint was overall survival (OS). RESULTS: Overall, 807 follicular lymphoma patients-52% women, 89% stage III-IV disease, 40% with a high-risk FLIPI-2 score (3-5)-were enrolled in the study; 729 (90.4%) baseline and EOI PET were available for the analysis. EOI PET was positive (DS4-5) in 88/729 (12.1%) cases. Overall inter-reviewer agreement on PET pos/neg result was 0.92, while agreement on positive and negative cases was 0.77 and 0.94, respectively. The median follow-up was 69 months; 247 events were registered in the 5-yr follow-up, with a 5-yr PFS of 67% (95%CI: 63%-70%). The 5-yr PFS rate for PET neg (DS1-3) and PET pos (DS4-5) patients was 71% (95%CI: 67%-75%) and 36% (95%CI: 25%-46%), respectively, with HR 3.49 (95%CI: 2.57-4.72). Five-year PFS was worse as DS increased, with 74% (70%-78%), 58% (48%-67%; HR 1.71; p = 0.001)] and 36% (25%-46%; HR 3.88; p < 0.001) in DS1-2, DS3 and DS4-5, respectively. EOI PET maintained its prognostic value in both the standard and experimental arms. In the whole population, 5-yr OS was 94% (95%CI: 92%-96%), with 96% (95%CI: 94-97) and 82% (95%CI: 72%-89%) in EOI PET negative (DS1-3) and positive (DS4-5), respectively (HR 4.48; p < 0.001). When DS was associated with FLIPI-2, patients with DS3 or DS1-2 with high FLIPI-2 (3-5) experienced worse OS than patients with DS1-2 and low FLIPI-2 (1-2) (p = 0.003). CONCLUSION: This study shows that DS is a reliable prognostic tool to evaluate EOI PET in follicular lymphoma patients, with prognostic value maintained both in the standard and experimental arms, making metabolic imaging a robust tool to assess response in FL. Moreover, although preliminary, this study provides further information on DS3 patients, who are considered as CMR but show a less favourable PFS than DS1-2 patients.

[11C]Choline PET/CT in a Patient with Prostate Cancer Biochemical Recurrence Showing Two Suspicious Findings in the Breast and Liver.

A 79-year-old man with prostate cancer (PCa) was referred to our center to perform a [11C]Choline PET/CT for biochemical recurrence. Positron emission tomography/computed tomography (PET/CT) scan detected PCa recurrence in the prostate gland and several pelvic and abdominal lymph nodes. Two abnormal uptakes were also identified in the right breast and in the liver, respectively. Breast histological findings turned out to be gynecomastia, while the liver lesion resulted in a benign perfusion anomaly at follow-up magnetic resonance imaging (MRI). Although incidental findings were benign in this case, it is important to always investigate abnormal uptakes of [11C]Choline, as it could be an expression of further metastases or synchronous malignancies such as breast cancer and hepatocellular carcinoma.

Applications of Artificial Intelligence and Radiomics in Molecular Hybrid Imaging and Theragnostics for Neuro-Endocrine Neoplasms (NENs).

Nuclear medicine has acquired a crucial role in the management of patients with neuroendocrine neoplasms (NENs) by improving the accuracy of diagnosis and staging as well as their risk stratification and personalized therapies, including radioligand therapies (RLT). Artificial intelligence (AI) and radiomics can enable physicians to further improve the overall efficiency and accuracy of the use of these tools in both diagnostic and therapeutic settings by improving the prediction of the tumor grade, differential diagnosis from other malignancies, assessment of tumor behavior and aggressiveness, and prediction of treatment response. This systematic review aims to describe the state-of-the-art AI and radiomics applications in the molecular imaging of NENs.

Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics.

In prostate cancer (PCa), the use of new radiopharmaceuticals has improved the accuracy of diagnosis and staging, refined surveillance strategies, and introduced specific and personalized radioreceptor therapies. Nuclear medicine, therefore, holds great promise for improving the quality of life of PCa patients, through managing and processing a vast amount of molecular imaging data and beyond, using a multi-omics approach and improving patients' risk-stratification for tailored medicine. Artificial intelligence (AI) and radiomics may allow clinicians to improve the overall efficiency and accuracy of using these "big data" in both the diagnostic and theragnostic field: from technical aspects (such as semi-automatization of tumor segmentation, image reconstruction, and interpretation) to clinical outcomes, improving a deeper understanding of the molecular environment of PCa, refining personalized treatment strategies, and increasing the ability to predict the outcome. This systematic review aims to describe the current literature on AI and radiomics applied to molecular imaging of prostate cancer.

Non-conventional and Investigational PET Radiotracers for Breast Cancer: A Systematic Review.

Breast cancer is one of the most common malignancies in women, with high morbidity and mortality rates. In breast cancer, the use of novel radiopharmaceuticals in nuclear medicine can improve the accuracy of diagnosis and staging, refine surveillance strategies and accuracy in choosing personalized treatment approaches, including radioligand therapy. Nuclear medicine thus shows great promise for improving the quality of life of breast cancer patients by allowing non-invasive assessment of the diverse and complex biological processes underlying the development of breast cancer and its evolution under therapy. This review aims to describe molecular probes currently in clinical use as well as those under investigation holding great promise for personalized medicine and precision oncology in breast cancer.