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Objective: a considerable subgroup of meningiomas (MN) exhibit indolent and insidious growth. Strategies to detect earlier treatment responses based on tumour biology rather than on size can be useful. We aimed to characterize therapy-induced changes in the apparent diffusion coefficient (ADC) of MN treated with proton-therapy (PT), determining whether the pre- and early post-treatment ADC values may predict tumour response. Methods: Forty-four subjects with MN treated with PT were retrospectively enrolled. All patients underwent conventional magnetic resonance imaging (MRI) including diffusion-weighted imaging (DWI) at baseline and each 3 months for a follow-up period up to 36 months after the beginning of PT. Mean relative ADC (rADCm) values of 46 MN were measured at each exam. The volume variation percentage (VV) for each MN was calculated. The Wilcoxon test was used to assess the differences in rADCm values between pre-treatment and post-treatment exams. Patients were grouped in terms of VV (threshold −20%). A p < 0.05 was considered statistically significant for all the tests. Results: A significant progressive increase of rADCm values was detected at each time point when compared to baseline rADCm (p < 0.05). Subjects that showed higher pre-treatment rADCm values had no significant volume changes or showed volume increase, while subjects that showed a VV < −20% had significantly lower pre-treatment rADCm values. Higher and earlier rADCm increases (3 months) are related to greater volume reduction. Conclusion: In MN treated with PT, pre-treatment rADCm values and longitudinal rADCm changes may predict treatment response.

Rhabdomyosarcoma is the most common soft-tissue sarcoma of childhood. Despite clinical advances, subsets of these patients continue to suffer high morbidity and mortality rates associated with their disease. Following the European guidelines for 18F-FDG PET and PET-CT imaging in pediatric oncology, the routine use of 18F-FDG PET-CT may be useful for patients affected by rhabdomyosarcoma, in staging, in the evaluation of response to therapy, and for restaging/detection of relapse. The European Pediatric Protocols are very old, and for staging and restaging, they recommend only radionuclide bone scan. The 18F-FDG PET-CT exam is listed as an optional investigation prescribed according to local availability and local protocols in the investigations panel required at the end of the treatment. We present two cases highlighting the usefulness of 18F-FDG PET-CT in managing pediatric patients affected by rhabdomyosarcoma, providing some bibliographic references.

To measure the early impact of robot-assisted partial nephrectomy (RAPN) on renal function as assessed by renal scan (Tc 99m-DTPA), addressing the issue of risk factors for ischemic damage to the kidney. All patients undergoing RAPN for cT1 renal masses between June 2013 and May 2014 were included in this prospective study. Renal function as expressed by glomerular filtration rate (GFR) was assessed by Technetium 99m-diethylenetriaminepentaacetic acid (Tc 99m-DTPA) renal scan preoperatively and postoperatively at 1 month in every patient. A multivariable analysis was used for the determination of independent factors predictive of GFR decrease of the operated kidney. Overall, 32 patients underwent RAPN in the time interval. Median tumor size, blood loss, and ischemia time were 4 cm, 200 mL, and 24 min, respectively. Two grade III complications occurred (postoperative bleeding in the renal fossa, urinoma). The GFR of the operated kidney decreased significantly from 51.7 ± 15.1 mL/min per 1.73 m 2 preoperatively to 40, 12 ± 12.4 mL/min per 1.73 m 2 1 month postoperatively ( p  = 0.001) with a decrease of 22.4 %. On multivariable analysis, only tumor size ( p  = 0.05) was a predictor of GFR decrease of the operated kidney. Robotic-assisted partial nephrectomy had a detectable impact on early renal function in a series of relatively large tumors and prevailing intermediate nephrometric risk. A mean decrease of 22 % of GFR as assessed by renal scan in the operated kidney was found at 1 month postoperatively. In multivariable analysis, tumor size only was a significant predictor of renal function loss.

The burden of Parkinson Disease (PD) represents a key public health issue and it is essential to develop innovative and cost-effective approaches to promote sustainable diagnostic and therapeutic interventions. In this perspective the adoption of a P3 (predictive, preventive and personalized) medicine approach seems to be pivotal. The NeuroArtP3 (NET-2018-12366666) is a four-year multi-site project co-funded by the Italian Ministry of Health, bringing together clinical and computational centers operating in the field of neurology, including PD. The core objectives of the project are: i) to harmonize the collection of data across the participating centers, ii) to structure standardized disease-specific datasets and iii) to advance knowledge on disease's trajectories through machine learning analysis. The 4-years study combines two consecutive research components: i) a multi-center retrospective observational phase; ii) a multi-center prospective observational phase. The retrospective phase aims at collecting data of the patients admitted at the participating clinical centers. Whereas the prospective phase aims at collecting the same variables of the retrospective study in newly diagnosed patients who will be enrolled at the same centers. The participating clinical centers are the Provincial Health Services (APSS) of Trento (Italy) as the center responsible for the PD study and the IRCCS San Martino Hospital of Genoa (Italy) as the promoter center of the NeuroartP3 project. The computational centers responsible for data analysis are the Bruno Kessler Foundation of Trento (Italy) with TrentinoSalute4.0 -Competence Center for Digital Health of the Province of Trento (Italy) and the LISCOMPlab University of Genoa (Italy). The work behind this observational study protocol shows how it is possible and viable to systematize data collection procedures in order to feed research and to advance the implementation of a P3 approach into the clinical practice through the use of AI models.

The burden of Parkinson Disease (PD) represents a key public health issue and it is essential to develop innovative and cost-effective approaches to promote sustainable diagnostic and therapeutic interventions. In this perspective the adoption of a P3 (predictive, preventive and personalized) medicine approach seems to be pivotal. The NeuroArtP3 (NET-2018-12366666) is a four-year multi-site project co-funded by the Italian Ministry of Health, bringing together clinical and computational centers operating in the field of neurology, including PD. The core objectives of the project are: i) to harmonize the collection of data across the participating centers, ii) to structure standardized disease-specific datasets and iii) to advance knowledge on disease's trajectories through machine learning analysis. The 4-years study combines two consecutive research components: i) a multi-center retrospective observational phase; ii) a multi-center prospective observational phase. The retrospective phase aims at collecting data of the patients admitted at the participating clinical centers. Whereas the prospective phase aims at collecting the same variables of the retrospective study in newly diagnosed patients who will be enrolled at the same centers. The participating clinical centers are the Provincial Health Services (APSS) of Trento (Italy) as the center responsible for the PD study and the IRCCS San Martino Hospital of Genoa (Italy) as the promoter center of the NeuroartP3 project. The computational centers responsible for data analysis are the Bruno Kessler Foundation of Trento (Italy) with TrentinoSalute4.0 -Competence Center for Digital Health of the Province of Trento (Italy) and the LISCOMPlab University of Genoa (Italy). The work behind this observational study protocol shows how it is possible and viable to systematize data collection procedures in order to feed research and to advance the implementation of a P3 approach into the clinical practice through the use of AI models.

IntroductionMedullary thyroid carcinoma (MTC) is a malignancy accounting for about 5–8% of thyroid cancers. Serum calcitonin and carcinoembryonic antigen (CEA) levels are widely used to monitor disease progression. However, prognostic factors able to predict outcomes are highly desirable. We, therefore, aimed to assess the prognostic role of 18F-DOPA PET/CT in patients with recurrent MTC.Materials and methods60 patients (mean age 64 ± 13 years, range 44–82) with recurrent MTC were eligible from a multicenter database. All patients underwent a restaging 18F-DOPA PET/CT, performed at least 6 months after surgery. CEA/calcitonin levels, local recurrences, nodal involvement and metastases at PET/CT were recorded. SUVmax, SUVmean (also normalized to mediastinal uptake) and metabolic tumor volume were automatically calculated for each lesion, by placing a volume of interest around the lesion with 40% of peak activity as threshold for the automatic contouring. The patients were clinically and radiologically followed up for 21 ± 11 months. Rate of progression-free survival (PFS), disease-specific survival (DSS) and incremental prognostic value of 18F-DOPA PET/CT over conventional imaging modalities were assessed by Kaplan–Meier curves and Log-Rank test. Cox regression univariate and multivariate analyses were performed for assessing predictors of prognosis.Results18F-DOPA PET/CT showed abnormal findings in 27 patients (45%) and resulted unremarkable in 33 (55%). PFS was significantly longer in patients with an unremarkable PET/CT scan (p = 0.018). Similarly, an unremarkable PET/CT study was associated with a significantly longer DSS (p = 0.04). 18F-DOPA PET/CT added prognostic value over other imaging modalities both for PFS and for DSS (p < 0.001 and p = 0.012, respectively). Neither semiquantitative PET parameters nor clinical or laboratory data were predictive of a worse PFS and DSS in patients with recurrent MTC.Conclusion18F-DOPA PET/CT scan has an important prognostic value in predicting disease progression and mortality rate.

Background Although widely used for the management of patients with cutaneous melanoma, the sentinel lymph node (SLN) biopsy (SNB) procedure raises several issues. This study was designed to investigate: the predictive factors of SLN status, the false-negative (FN) rate, and patients’ prognosis after SNB. Patients and Methods This is an observational, prospective study conducted on a large series of consecutive patients ( n  = 1,313) enrolled by 23 Italian centers from 2000 through 2002. A commonly shared protocol was adopted for the SNB surgical procedure and the SLN pathological examination. Results The SLN positive and false-negative (FN) rates were 16.9% and 14.4%, respectively (median follow-up, 4.5 years). At multivariable logistic regression analysis, the frequency of positive SLN increased with increasing Breslow thickness ( p  < 0.0001) and decreased in patients with melanoma regression ( p  = 0.024). At the multivariable Cox regression analysis, SLN status was the most important prognostic factor (hazards ratio (HR) = 3.08) for overall survival; the other statistically significant factors were sex, age, Breslow thickness, and Clark’s level. Considering SLN and NSLN status, including FN cases, we identified four groups of patients with different prognoses. The 5-year overall survival of patients with positive SLNs was 71.3% in those with negative nonsentinel lymph nodes (NSLNs) and 50.4% if NSLNs were positive. Conclusions Regression in the primary melanoma seems to be a protective factor from metastasis in the SLN. When correctly calculated, the SNB FN rate is 15–20%. Furthermore, the SNB is important to more precisely assess the prognosis of patients with melanoma.

The following affiliation should be added to the authors Agostino Chiaravalloti and Orazio Schillaci.

High rate of non-target lesions in metastatic castration-resistant prostate cancer usually limits applicability of Response Evaluation Criteria in Solid Tumors (RECIST) criteria, and this has led to a growing interest in using PET/computed tomography (CT). We prospectively investigated the role of F-choline (FCH)-PET/CT in patients receiving enzalutamide after docetaxel. 30 patients were monitored by means of FCH-PET/CT before and during the treatment. A Cox proportional hazards regression model was used to assess the associations between metabolic parameters and clinical outcomes. Univariate analysis showed no significant correlation between biochemical and FCH-PET responses. Multivariate analysis showed that only baseline maximum standardized uptake value (SUV ) significantly correlated with biochemical progression-free survival, radiological progression-free survival and overall survival. Our findings suggest that FCH-PET/CT may play a role in defining prognosis of patients receiving enzalutamide because baseline SUV proved to be an independent prognostic factor.