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Purpose: To explore the role of fully hybrid 68Ga-DOTATOC PET/MR imaging and radiomic parameters in predicting histopathological prognostic factors in patients with pancreatic neuroendocrine tumours (PanNETs) undergoing surgery. Methods: One hundred eighty-seven consecutive 68Ga-DOTATOC PET/MRI scans (March 2018–June 2020) performed for gastroenteropancreatic neuroendocrine tumour were retrospectively evaluated; 16/187 patients met the eligibility criteria (68Ga-DOTATOC PET/MRI for preoperative staging of PanNET and availability of histological data). PET/MR scans were qualitatively and quantitatively interpreted, and the following imaging parameters were derived: PET-derived SUVmax, SUVmean, somatostatin receptor density (SRD), total lesion somatostatin receptor density (TLSRD), and MRI-derived apparent diffusion coefficient (ADC), arterial and late enhancement, necrosis, cystic degeneration, and maximum diameter. Additionally, first-, second-, and higher-order radiomic parameters were extracted from both PET and MRI scans. Correlations with several PanNETs' histopathological prognostic factors were evaluated using Spearman's coefficient, while the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate parameters' predictive performance. Results: Primary tumour was detected in all 16 patients (15/16 by 68Ga-DOTATOC PET and 16/16 by MRI). SUVmax and SUVmean resulted good predictors of lymphnodal (LN) involvement (AUC of 0.850 and 0.783, respectively). Second-order radiomic parameters GrayLevelVariance and HighGrayLevelZoneEmphasis extracted from T2 MRI demonstrated significant correlations with LN involvement (adjusted p = 0.009), also showing good predictive performance (AUC = 0.992). Conclusion: This study demonstrates the role of the fully hybrid PET/MRI tool for the synergic function of imaging parameters extracted by the two modalities and highlights the potentiality of imaging and radiomic parameters in assessing histopathological features of PanNET aggressiveness. [ABSTRACT FROM AUTHOR]

Background : PSMA PET radiomics is a promising tool for primary prostate cancer (PCa) characterisation. However, small single-centre studies and lack of external validation hinder definitive conclusions on the potential of PSMA PET radiomics in the initial workup of PCa. We aimed to validate a radiomics signature in a larger internal cohort and in an external cohort from a separate centre. Methods : One hundred and twenty-seven PCa patients were retrospectively enrolled across two independent hospitals. The first centre (IRCCS San Raffaele Scientific Institute, Centre 1) contributed 62 [ 68 Ga]Ga-PSMA-11 PET scans, 20 patients classified as low-grade (ISUP grade < 4), and 42 as high-grade (ISUP grade ≥ 4). The second centre (Stanford University Hospital, Centre 2) provided 65 [ 68 Ga]Ga-PSMA-11 PET scans, and 49 low-grade and 16 high-grade patients. A radiomics model previously generated in Centre 1 was tested on the two cohorts separately and afterward on the entire dataset. Then, we evaluated whether the radiomics features selected in the previous investigation could generalise to new data. Several machine learning (ML) models underwent training and testing using 100-fold Monte Carlo cross-validation, independently at both Centre 1 and Centre 2, with a 70-30% train-test split. Additionally, models were trained in one centre and tested in the other, and vice versa. Furthermore, data from both centres were combined for training and testing using Monte Carlo cross-validation. Finally, a new radiomics signature built on this bicentric dataset was proposed. Several performance metrics were computed. Results: The previously generated radiomics signature resulted in an area under the receiver operating characteristic curve (AUC) of 80.4% when tested on Centre 1, while it generalised poorly to Centre 2, where it reached an AUC of 62.7%. When the whole cohort was considered, AUC was 72.5%. Similarly, new ML models trained on the previously selected features yielded, at best, an AUC of 80.9% for Centre 1 and performed at chance for Centre 2 (AUC of 49.3%). A new signature built on this bicentric dataset reached, at best, an average AUC of 91.4% in the test set. Conclusions: The satisfying performance of radiomics models when used in the original development settings, paired with the poor performance otherwise observed, emphasises the need to consider centre-specific factors and dataset characteristics when developing radiomics models. Combining radiomics datasets is a viable strategy to reduce such centre-specific biases, but external validation is still needed.

Purpose: Accurate identification of lymph node (LN) metastases is pivotal for surgical planning of pancreatic neuroendocrine tumours (PanNETs); however, current imaging techniques have sub-optimal diagnostic sensitivity. Aim of this study is to investigate whether [ 68 Ga]Ga-DOTATOC PET radiomics might improve the identification of LN metastases in patients with non-functioning PanNET (NF-PanNET) referred to surgical intervention., Methods: Seventy-two patients who performed preoperative [ 68 Ga]Ga-DOTATOC PET between December 2017 and March 2022 for NF-PanNET. [ 68 Ga]Ga-DOTATOC PET qualitative assessment of LN metastases was measured using diagnostic balanced accuracy (bACC), sensitivity (SN), specificity (SP), positive and negative predictive values (PPV, NPV). SUVmax, SUVmean, Somatostatin receptor density (SRD), total lesion SRD (TLSRD) and IBSI-compliant radiomic features (RFs) were obtained from the primary tumours. To predict LN involvement, these parameters were engineered, selected and used to train different machine learning models. Models were validated using tenfold repeated cross-validation and control models were developed. Models' bACC, SN, SP, PPV and NPV were collected and compared (Kruskal-Wallis, Mann-Whitney)., Results: LN metastases were detected in 29/72 patients at histology. [ 68 Ga]Ga-DOTATOC PET qualitative examination of LN involvement provided bACC = 60%, SN = 24%, SP = 95%, PPV = 78% and NPV = 65%. The best-performing radiomic model provided a bACC = 70%, SN = 77%, SP = 61%, PPV = 60% and NPV = 83% (outperforming the control model, p < 0.05*)., Conclusion: In this study, [ 68 Ga]Ga-DOTATOC PET radiomics allowed to increase diagnostic sensitivity in detecting LN metastases from 24 to 77% in NF-PanNET patients candidate to surgery. Especially in case of micrometastatic involvement, this approach might assist clinicians in a better patients' stratification., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: To compare the diagnostic accuracy and detection rates of PET/MRI with [ 68 Ga]Ga-PSMA-11 and [ 68 Ga]Ga-M2 in patients with biochemical recurrence of prostate cancer (PCa)., Methods: Sixty patients were enrolled in this prospective single-center phase II clinical trial from June 2020 to October 2022. Forty-four/60 completed all study examinations and were available at follow-up (median: 22.8 months, range: 6-31.5 months). Two nuclear medicine physicians analyzed PET images and two radiologists interpreted MRI; images were then re-examined to produce an integrated PET/MRI report for both [ 68 Ga]Ga-PSMA-11 and [ 68 Ga]Ga-RM2 examinations. A composite reference standard including histological specimens, response to treatment, and conventional imaging gathered during follow-up was used to validate imaging findings. Detection rates, accuracy, sensitivity, specificity, positive, and negative predictive value were assessed. McNemar's test was used to compare sensitivity and specificity on a per-patient base and detection rate on a per-region base. Prostate bed, locoregional lymph nodes, non-skeletal distant metastases, and bone metastases were considered. p-value significance was defined below the 0.05 level after correction for multiple testing., Results: Patients' median age was 69.8 years (interquartile range (IQR): 61.8-75.1) and median PSA level at time of imaging was 0.53 ng/mL (IQR: 0.33-2.04). During follow-up, evidence of recurrence was observed in 31/44 patients. Combining MRI with [ 68 Ga]Ga-PSMA-11 PET and [ 68 Ga]Ga-RM2 PET resulted in sensitivity = 100% and 93.5% and specificity of 69.2% and 69.2%, respectively. When considering the individual imaging modalities, [ 68 Ga]Ga-RM2 PET showed lower sensitivity compared to [ 68 Ga]Ga-PSMA-11 PET and MRI (61.3% vs 83.9% and 87.1%, p = 0.046 and 0.043, respectively), while specificity was comparable among the imaging modalities (100% vs 84.6% and 69.2%, p = 0.479 and 0.134, respectively)., Conclusion: This study brings further evidence on the utility of fully hybrid PET/MRI for disease characterization in patients with biochemically recurrent PCa. Imaging with [ 68 Ga]Ga-PSMA-11 PET showed high sensitivity, while the utility of [ 68 Ga]Ga-RM2 PET in absence of a simultaneous whole-body/multiparametric MRI remains to be determined., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Nearly two-thirds of patients with heart failure with reduced ejection fraction (HFrEF) have right ventricular dysfunction, previously identified as an independent predictor of reduced functional capacity and poor prognosis. Beta-blocker therapy (β-BT) reduces mortality and hospitalizations in patients with HFrEF and is approved as first-line therapy regardless of concomitant right ventricular function. However, the exact role of sympathetic nervous system activation in right ventricular dysfunction and the potential usefulness (or harmfulness) of β-BT in these patients are still unclear., Objectives: The aim of the study is to evaluate the medium-term effect of β-BT discontinuation on functional capacity and right ventricular remodelling based on cardiopulmonary exercise testing (CPET), echocardiography and serum biomarkers in patients with clinically stable biventricular dysfunction., Methods: In this single-centre, open-label, prospective trial, 16 patients were enrolled using the following criteria: patients were clinically stable without signs of peripheral congestion; NYHA II-III while on optimal medical therapy (including β-BT); LVEF 40% or less; echocardiographic criteria of right ventricular dysfunction. Patients were randomized 1 : 1 either to withdraw (group 0) or continue (group 1) β-BT. In group 0, optimal heart rate was obtained with alternative rate-control drugs. Echo and serum biomarkers were performed at baseline, after 3 and 6 months; CPET was performed at baseline and 6 months. Mann--Whitney U test was adopted to determine the relationships between β-BT discontinuation and effects on right ventricular dysfunction., Results: At 6 months' follow up, S' DTI improved (ΔS': 1.01 vs. -0.92 cm/s; P = 0.03), while estimated PAPs (ΔPAPs: 0.8 vs. -7.5 mmHg; P = 0.04) and echo left ventricular-remodelling (ΔEDVi: 19.55 vs. -0.96 ml/mq; P = 0.03) worsened in group 0. In absolute terms, the only variables significantly affected by β-BT withdrawal were left ventricular EDV and ESV, appearing worse in group 0 (mean EDVi 115 vs. 84 ml/mq; mean ESVi 79 vs. 53.9 ml/mq, P = 0.03). No significant changes in terms of functional capacity were observed after β-BT withdrawal., Conclusion: In HFrEF patients with concomitant right ventricular dysfunction, β-BT discontinuation did not produce any beneficial effects. In addition, despite maintenance of optimal heart rate control, β-BT discontinuation induced worsening of left ventricular remodelling. Our study corroborates the hypothesis that improvement in left ventricular function may likewise be a major determinant for improvement in right ventricular function, reducing pulmonary wedge pressure and right ventricular afterload, with only a marginal action of its negative inotropic effect. In conclusion, β-BT appears beneficial also in heart failure patients with biventricular dysfunction., (Copyright © 2023 Italian Federation of Cardiology - I.F.C. All rights reserved.)

The present systematic review and meta-analysis are focused on the diagnostic accuracy of PSMA PET/MRI in primary prostate cancer assessment. A literature search was conducted on the PubMed database using the terms "PSMA" AND "prostate cancer" or "prostate" AND "PET/MRI" or "PET MRI" or "PET-MRI" or "PET-MR" AND "primary" or "staging." Ten articles were eligible for analysis after applying the exclusion criteria. PET/MRI showed better diagnostic accuracy in detecting primary PCa compared to multiparametric (mp) MRI and PET alone. The pooled sensitivity and specificity of 68Ga-PSMA PET/MRI at the per-patient level were 0.976 (CI: 0.943-0.991) and 0.739 (CI: 0.437-0.912); respectively. PSMA PET/MRI has good sensitivity in detecting primary PCa, especially in patients with PIRADS 3 PCa., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Localized prostate cancer (PCa) can be treated with radical prostatectomy (RP). Up to 30% of patients undergoing this procedure experience biochemical recurrence (BCR), namely the rise in serum prostate-specific antigen (PSA) levels during the post-surgical follow-up, requiring further treatments and with the risk of severe disease progression. Currently, the most accurate imaging technique to confirm, detect, and locate disease relapses in BCR patients is prostate-specific membrane antigen (PSMA)-targeted PET, as recommended by international clinical guidelines. The aim of the study was to investigate potential clinical and pathological predictors of PSMA PET positivity, validated by clinical and instrumental follow-up or histopathological data. In this study, a selected cohort of BCR patients after RP and no other PCa-related therapy who underwent either PSMA PET/CT or PSMA PET/MRI has been analysed. Among the considered predictors, both pathological staging after RP equal or higher than pT3a and higher PSA levels at the time of the scan were significantly correlated with PSMA PET positivity on multivariate logistic regression analysis. As expected, PSMA PET confirmed its role as an accurate imaging technique in the setting of BCR in PCa. These findings may inform appropriate and tailored patient selection and scan timing to optimize and fully exploit this powerful diagnostic tool.

This study proposed a new workflow for co-registering prostate PET images from a dual-tracer PET/MRI study with histopathological images of resected prostate specimens. The method aims to establish an accurate correspondence between PET/MRI findings and histology, facilitating a deeper understanding of PET tracer distribution and enabling advanced analyses like radiomics. To achieve this, images derived by three patients who underwent both [ 68 Ga]Ga-PSMA and [ 68 Ga]Ga-RM2 PET/MRI before radical prostatectomy were selected. After surgery, in the resected fresh specimens, fiducial markers visible on both histology and MR images were inserted. An ex vivo MRI of the prostate served as an intermediate step for co-registration between histological specimens and in vivo MRI examinations. The co-registration workflow involved five steps, ensuring alignment between histopathological images and PET/MRI data. The target registration error (TRE) was calculated to assess the precision of the co-registration. Furthermore, the DICE score was computed between the dominant intraprostatic tumor lesions delineated by the pathologist and the nuclear medicine physician. The TRE for the co-registration of histopathology and in vivo images was 1.59 mm, while the DICE score related to the site of increased intraprostatic uptake on [ 68 Ga]Ga-PSMA and [ 68 Ga]Ga-RM2 PET images was 0.54 and 0.75, respectively. This work shows an accurate co-registration method for histopathological and in vivo PET/MRI prostate examinations that allows the quantitative assessment of dual-tracer PET/MRI diagnostic accuracy at a millimetric scale. This approach may unveil radiotracer uptake mechanisms and identify new PET/MRI biomarkers, thus establishing the basis for precision medicine and future analyses, such as radiomics.

Purpose: The aim of this study is to investigate the role of [ 68 Ga]Ga-PSMA-11 PET radiomics for the prediction of post-surgical International Society of Urological Pathology ( PS ISUP) grade in primary prostate cancer (PCa)., Methods: This retrospective study included 47 PCa patients who underwent [ 68 Ga]Ga-PSMA-11 PET at IRCCS San Raffaele Scientific Institute before radical prostatectomy. The whole prostate was manually contoured on PET images and 103 image biomarker standardization initiative (IBSI)-compliant radiomic features (RFs) were extracted. Features were then selected using the minimum redundancy maximum relevance algorithm and a combination of the 4 most relevant RFs was used to train 12 radiomics machine learning models for the prediction of PS ISUP grade: ISUP ≥ 4 vs ISUP < 4. Machine learning models were validated by means of fivefold repeated cross-validation, and two control models were generated to assess that our findings were not surrogates of spurious associations. Balanced accuracy (bACC) was collected for all generated models and compared with Kruskal-Wallis and Mann-Whitney tests. Sensitivity, specificity, and positive and negative predictive values were also reported to provide a complete overview of models' performance. The predictions of the best performing model were compared against ISUP grade at biopsy., Results: ISUP grade at biopsy was upgraded in 9/47 patients after prostatectomy, resulting in a bACC = 85.9%, SN = 71.9%, SP = 100%, PPV = 100%, and NPV = 62.5%, while the best-performing radiomic model yielded a bACC = 87.6%, SN = 88.6%, SP = 86.7%, PPV = 94%, and NPV = 82.5%. All radiomic models trained with at least 2 RFs (GLSZM-Zone Entropy and Shape-Least Axis Length) outperformed the control models. Conversely, no significant differences were found for radiomic models trained with 2 or more RFs (Mann-Whitney p > 0.05)., Conclusion: These findings support the role of [ 68 Ga]Ga-PSMA-11 PET radiomics for the accurate and non-invasive prediction of PS ISUP grade., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: To evaluate the role of 68 Ga-DOTATOC PET parameters in predicting DAXX/ATRX loss of expression in patients with Pancreatic neuroendocrine tumors (PanNET) candidate to surgery., Methods: This retrospective study included 72 consecutive patients with PanNET (January 2018-March 2022) who underwent to 68 Ga-DOTATOC PET for preoperative staging. Image analysis: qualitative assessment and extraction of SUVmax, SUV mean, somatostatin receptor density (SRD), and total lesion somatostatin receptor density (TLSRD) from primary PanNET. Radiological diameter and biopsy information (grade, Ki67) were collected. Loss of expression (LoE) of DAXX/ATRX was assessed by immunohistochemistry on surgical specimen. Student t-test, univariate and multivariate logistic regression and ROC curves have been used to investigate the predictive value of PET parameters on DAXX/ATRX LoE., Results: Forty-two/72 patients had a G1, 28/72 a G2, and 2/72 a G3 PanNET. Seven/72 patients had DAXX LoE, 10/72 ATRX LoE, and 2/72 DAXX/ATRX LoE. SRD and TLSRD could predict DAXX LoE (p = 0.002, p = 0.018, respectively). By evaluating SRD in combination with radiological diameter, only SRD maintained statistical significance (multivariate logistic regression: p = 0.020, OR = 1.05), providing the best prediction (AUC-ROC = 79.01%; cut-off = 46.96; sensitivity = 77.78%; specificity = 88.89%). In the sub-analysis performed on 55 patients with biopsy availability, SRD demonstrated its role in providing useful and additional information (multivariate logistic regression: SRD p = 0.007; grade p = 0.040)., Conclusion: SRD has a predictive role on DAXX LoE in PanNETs, with higher probability of LoE at increasing SRD values. SRD provides complementary/additional information to grade assessed on biopsy material, and the combined use of these approaches might support patients' management by preoperatively identifying subjects with more aggressive diseases., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: State of the art artificial intelligence (AI) models have the potential to become a "one-stop shop" to improve diagnosis and prognosis in several oncological settings. The external validation of AI models on independent cohorts is essential to evaluate their generalization ability, hence their potential utility in clinical practice. In this study we tested on a large, separate cohort a recently proposed state-of-the-art convolutional neural network for the automatic segmentation of intraprostatic cancer lesions on PSMA PET images., Methods: Eighty-five biopsy proven prostate cancer patients who underwent 68 Ga PSMA PET for staging purposes were enrolled in this study. Images were acquired with either fully hybrid PET/MRI ( N = 46) or PET/CT ( N = 39); all participants showed at least one intraprostatic pathological finding on PET images that was independently segmented by two Nuclear Medicine physicians. The trained model was available at https://gitlab.com/dejankostyszyn/prostate-gtv-segmentation and data processing has been done in agreement with the reference work., Results: When compared to the manual contouring, the AI model yielded a median dice score = 0.74, therefore showing a moderately good performance. Results were robust to the modality used to acquire images (PET/CT or PET/MRI) and to the ground truth labels (no significant difference between the model's performance when compared to reader 1 or reader 2 manual contouring)., Discussion: In conclusion, this AI model could be used to automatically segment intraprostatic cancer lesions for research purposes, as instance to define the volume of interest for radiomics or deep learning analysis. However, more robust performance is needed for the generation of AI-based decision support technologies to be proposed in clinical practice., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Ghezzo, Mongardi, Bezzi, Samanes Gajate, Preza, Gotuzzo, Baldassi, Jonghi-Lavarini, Neri, Russo, Brembilla, De Cobelli, Scifo, Mapelli and Picchio.)

Purpose: to investigate the preoperative role of ML-based classification using conventional 18 F-FDG PET parameters and clinical data in predicting features of EC aggressiveness., Methods: retrospective study, including 123 EC patients who underwent 18 F-FDG PET (2009-2021) for preoperative staging. Maximum standardized uptake value (SUVmax), SUVmean, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were computed on the primary tumour. Age and BMI were collected. Histotype, myometrial invasion (MI), risk group, lymph-nodal involvement (LN), and p53 expression were retrieved from histology. The population was split into a train and a validation set (80-20%). The train set was used to select relevant parameters (Mann-Whitney U test; ROC analysis) and implement ML models, while the validation set was used to test prediction abilities., Results: on the validation set, the best accuracies obtained with individual parameters and ML were: 61% (TLG) and 87% (ML) for MI; 71% (SUVmax) and 79% (ML) for risk groups; 72% (TLG) and 83% (ML) for LN; 45% (SUVmax; SUVmean) and 73% (ML) for p53 expression., Conclusions: ML-based classification using conventional 18 F-FDG PET parameters and clinical data demonstrated ability to characterize the investigated features of EC aggressiveness, providing a non-invasive way to support preoperative stratification of EC patients.

Venetoclax (VEN) and hypomethylating agent (HMAs) regimens are emerging as the standard of care for unfit for chemotherapy acute myeloid leukemia (AML) patients, but the safety and feasibility of a total outpatient management have not been fully investigated. Fifty-nine AML patients with active disease received VEN and HMAs. Nineteen out of 59 (32.2%) patients received the first cycle as inpatients, whereas 40/59 (67.8%) patients were treated in the outpatient setting. No significant differences were observed with regard to incidence of adverse events (AEs), including tumor lysis syndrome (TLS), and the 30-day and 60-day mortality was comparable. Notably, an infectious prophylaxis inspired to that adopted during intensive chemotherapy resulted in a low infection rate with a reduced bacterial infections incidence in out- versus hospitalized patients (p < .0001). The overall time of hospitalization was significantly shorter in patients who received a total outpatient treatment as compared to those who received the first cycle as inpatients (5.9 vs. 39.7 days, p < .0001). Despite the adopted differences in treatment management, the efficacy was similar. These data indicate that a total outpatient management of VEN and HMAs is feasible in AML patients without negatively impacting on treatment efficacy and may yield pharmacoeconomic and quality-of-life benefits., (© 2022 The Authors. European Journal of Haematology published by John Wiley & Sons Ltd.)

Purpose: The aim of this study was to investigate the role of 18F-FDG PET/CT in predicting pathological prognostic factors, including tumor type and International Federation of Gynecology and Obstetrics (FIGO) score, in gestational trophoblastic disease (GTD)., Methods: Retrospective monocentric study including 24 consecutive patients who underwent to 18F-FDG PET/CT from May 2005 to March 2021 for GTD staging purpose. The following semiquantitative PET parameters were measured from the primary tumor and used for the analysis: maximum standardized uptake value (SUVmax), SUVmean, metabolic tumor volume (MTV) and total lesion glycolisis (TLG). Statistical analysis included Spearman correlation coefficient to evaluate the correlations between imaging parameters and tumor type (nonmolar trophoblastic vs postmolar trophoblastic tumors) and risk groups (high vs low, defined according to the FIGO score), whereas area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the predictive value of the PET parameters. Mann-Whitney U test was used to further describe the parameter's potential in differentiating the populations., Results: SUVmax and SUVmean resulted fair (AUC, 0.783; 95% confidence interval [CI], 0.56-0.95) and good (AUC, 0.811; 95% CI, 0.59-0.97) predictors of tumor type, respectively, showing a low (ρ = 0.489, adjusted P = 0.030) and moderate (ρ = 0.538, adjusted P = 0.027) correlation. According to FIGO score, TLG was instead a fair predictor (AUC, 0.770; 95% CI, 0.50-0.99) for patient risk stratification., Conclusions: 18F-FDG PET parameters have a role in predicting GTD pathological prognostic factors, with SUVmax and SUVmean being predictive for tumor type and TLG for risk stratification., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Aim: The assessment of deep myometrial invasion (MI) and lymph node involvement is of utmost importance in the preoperative staging of endometrial cancer (EC). Imaging parameters derived respectively from MRI and PET have shown good predictive value. The main aim of the present study is to assess the diagnostic performance of hybrid 18F-FDG PET/MRI in EC staging, with particular focus on MI and lymphnodal involvement detection., Patients and Methods: Prospective monocentric study including 35 patients with biopsy-proven EC undergoing preoperative 18F-FDG PET/MRI (December 2018-March 2021) for staging purpose. Histological examination was the reference standard. PET (SUVmax, SUVmean with a threshold of 40% of SUVmax-SUVmean40, metabolic tumor volume, total lesion glycolysis) and MRI (volume index [VI], total tumor volume, tumor volume ratio [TVR], mean apparent diffusion coefficient, minimum apparent diffusion coefficient) parameters were calculated on the primary tumor, and their role in predicting EC risk group, the presence of lymphovascular space invasion (LVSI), and MI was assessed. Receiver operating characteristics analysis was used to assess the predictive value of PET and MRI parameters on EC characteristics., Results: Patients' median age was 66.57 years (SD, 10.21 years). 18F-FDG PET/MRI identified the primary tumor in all patients. Twenty-two of 35 patients had high-risk EC and 13/35 low-risk disease; 13/35 presented LVSI, 22/35 had deep MI at histological examination, and 13/35 had p53 hyperexpression.PET/MRI was able to detect lymphnodal involvement with high accuracy and high specificity (sensitivity of 0.8571, specificity of 0.9286, accuracy of 0.9143), also showing a high negative predictive value (NPV) for lymphnodal involvement (NPV of 0.9630, positive predictive value [PPV] of 0.7500).The assessment of deep MI using PET/MRI correctly staged 27 patients (77.1%; sensitivity of 0.7273, specificity of 0.8462, accuracy of 0.7714), with also a good PPV (PPV of 0.8889, NPV of 0.647).MRI-derived total tumor volume, VI, and TVR were significant in predicting EC groups (high-risk vs low-risk patients) (P = 0.0059, 0.0235, 0.0181, respectively). MRI-derived volume, VI, TVR, and PET-derived metabolic tumor volume and total lesion glycolysis were able to predict LVSI (P = 0.0023, 0.0068, 0.0068, 0.0027, 0.01394, respectively). Imaging was not able to predict grading, presence of deep MI, nor hyperexpression of p53., Conclusions: 18F-FDG PET/MRI has good accuracy in preoperative staging of EC; PET and MRI parameters have synergic role in preoperatively predicting LVSI, with MRI parameters being also predictive for EC risk group., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

The aim of the present study is to investigate and compare the performances of 68 Ga-PSMA and 68 Ga-DOTA-RM2 PET/MRI in identifying recurrent prostate cancer (PCa) after primary treatment and to explore the association of dual-tracer PET findings with clinical and histopathological characteristics. Thirty-five patients with biochemical relapse (BCR) of PCa underwent 68 Ga PSMA PET/MRI for restaging purpose, with 31/35 also undergoing 68 Ga-DOTA-RM2 PET/MRI scan within 16 days (mean: 3 days, range: 2-16 days). Qualitative and quantitative image analysis has been performed by comparing 68 Ga-PSMA and 68 Ga-DOTA-RM2 PET/MRI findings both on a patient and lesion basis. Clinical and instrumental follow-up was used to validate PET findings. Fisher's exact test and Mann-Whitney U test were used to investigate the association between dual-tracer PET findings, clinical and histopathological data. p -value significance was defined below the 0.05 level. Patients' mean age was 70 years (range: 49-84) and mean PSA at time of PET/MR scans was 1.88 ng/mL (range: 0.21-14.4). A higher detection rate was observed for 68 Ga-PSMA PET/MRI, with more lesions being detected compared to 68 Ga-DOTA-RM2 PET/MRI (26/35 patients, 95 lesions vs. 15/31 patients, 41 lesions; p = 0.016 and 0.002). 68 Ga-PSMA and 68 Ga-DOTA-RM2 PET/MRI findings were discordant in 11/31 patients; among these, 10 were 68 Ga-PSMA positive (9/10 confirmed as true positive and 1/10 as false positive by follow-up examination). Patients with higher levels of PSA and shorter PSA doubling time (DT) presented more lesions on 68 Ga-PSMA PET/MRI ( p = 0.006 and 0.044), while no association was found between PET findings and Gleason score. 68 Ga-PSMA has a higher detection rate than 68 Ga-DOTA-RM2 in detecting PCa recurrence. The number of 68 Ga-PSMA PET positive lesions is associated with higher levels of PSA and shorter PSA DT, thus representing potential prognostic factors.

We present the current clinical applications of radiomics in the context of prostate cancer (PCa) management. Several online databases for original articles using a combination of the following keywords: "(radiomic or radiomics) AND (prostate cancer or prostate tumour or prostate tumor or prostate neoplasia)" have been searched. The selected papers have been pooled as focus on (i) PCa detection, (ii) assessing the clinical significance of PCa, (iii) biochemical recurrence prediction, (iv) radiation-therapy outcome prediction and treatment efficacy monitoring, (v) metastases detection, (vi) metastases prediction, (vii) prediction of extra-prostatic extension. Seventy-six studies were included for qualitative analyses. Classifiers powered with radiomic features were able to discriminate between healthy tissue and PCa and between low- and high-risk PCa. However, before radiomics can be proposed for clinical use its methods have to be standardized, and these first encouraging results need to be robustly replicated in large and independent cohorts., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The aim of the present study is to investigate the synergic role of 68 Ga-PSMA PET/MRI and 68 Ga-DOTA-RM2 PET/MRI in prostate cancer (PCa) staging. We present pilot data on twenty-two patients with biopsy-proven PCa that underwent 68 Ga-PSMA PET/MRI for staging purposes, with 19/22 also undergoing 68 Gaa-DOTA-RM2 PET/MRI. TNM classification based on image findings was performed and quantitative imaging parameters were collected for each scan. Furthermore, twelve patients underwent radical prostatectomy with the availability of histological data that were used as the gold standard to validate intraprostatic findings. A DICE score between regions of interest manually segmented on the primary tumour on 68 Ga-PSMA PET, 68 Ga-DOTA-RM2 PET and on T2 MRI was computed. All imaging modalities detected the primary PCa in 18/19 patients, with 68 Ga-DOTA-RM2 PET not detecting any lesion in 1/19 patients. In the remaining patients, 68 Ga-PSMA and MRI were concordant. Seven patients presented seminal vesicles involvement on MRI, with two of these being also detected by 68 Ga-PSMA, and 68 Ga-DOTA-RM2 PET being negative. Regarding extraprostatic disease, 68 Ga-PSMA PET, 68 Ga-DOTA-RM2 PET and MRI resulted positive in seven, four and five patients at lymph-nodal level, respectively, and at a bone level in three, zero and one patients, respectively. These preliminary results suggest the potential complementary role of 68 Ga-PSMA PET, 68 Ga-DOTA-RM2 PET and MRI in PCa characterization during the staging phase.

Carfilzomib-lenalidomide-dexamethasone (KRd) has been approved for the treatment of relapsed/refractory multiple myeloma (RRMM). We conducted a retrospective analysis of 197 RRMM patients (pts) between January 2016 and March 2018 in six Italian hematologic centers, with the aim to evaluate efficacy and safety of KRd in real-life. At KRd initiation 27% carried high risk cytogenetic abnormalities (HRCA) [del17p and/or t(4;14) and/or t(14;16)], median number of prior lines of therapy was 2 (1-8), nearly all pts (96%) received prior bortezomib (18% refractory) while 45% were exposed to lenalidomide (R; 22% refractory). At the median of 12.5 months, 52% of the pts had discontinued treatment, mainly (66%) for progression. Main grade 3-4 adverse events were neutropenia (21%), infections (11%), and hypertension (6%). Overall, the response rate was 88%. The median progression-free survival (PFS) was 19.8 months and 1-year overall survival (OS) rate was 80.6%. By subgroup analysis, extended PFS and OS were observed for pts who received ≤2 prior lines of therapy (HR = 0.42, p < 0.001 and HR = 0.35, p = 0.001, respectively), not refractory to prior R (HR = 0.37, p < 0.001, and HR = 0.47, p = 0.024), without HRCA (HR = 0.33, p = 0.005 and HR = 0.26, p = 0.016) and achieving ≥ very good partial response (VGPR; HR = 0.17, p < 0.001 and HR = 0.18, p < 0.001). In conclusion, KRd demonstrated to be effective in RRMM pts treated in real-world setting, without new safety concerns. Better survival outcomes emerged for pts with ≤2 prior lines of therapy, achieving at least a VGPR, and without HRCA., (© 2020 John Wiley & Sons Ltd.)

Purpose: To define an imaging risk profile in a population of patients affected by Pancreatic neuroendocrine neoplasms (PanNENs) candidates to surgery, by assessing the predictive role of 68Ga-DOTATOC and 18F-FDG PET/CT and PET/MR derived parameters in risk stratification, particularly regarding histological features of aggressive behaviour., Patients and Methods: Retrospective study including 83 patients (53 males, 30 females; median age: 60 years, interquartile range 52-66.5), who underwent to 68Ga-DOTATOC (PET/CT: n = 77; PET/MR: n = 6) and, 68/83 patients, also to 18F-FDG PET (PET/CT: n = 65; PET/MR: n = 3) before surgery for PanNEN between 2011 and 2019, with available histological and follow-up data. The PET scans were interpreted with both qualitative (positive vs. negative) and semiquantitative measurements as follows: maximum and mean standardized uptake value (SUVmax and SUVmean) for both 18F-FDG and 68Ga-DOTATOC scans, metabolic tumour volume (MTV) and tumour lesion glycolysis (TLG) for 18F-FDG scans and somatostatin receptor density (SRD) and total lesion somatostatin receptor density (TLSRD) for 68Ga-DOTATOC PET. Receiver Operating Characteristics (ROC) curve analysis was used to investigate the performance of several PET parameters in predicting tumour stage or characteristic. For each PET parameter, the optimal cut-off was derived. Logistic regression analysis was used to assess if the PET parameters, categorized with the optimal cut-off values, were able to predict significantly the corresponding tumour stage or characteristic., Results: Overall, 29 (35%) patients had G1, 49 (59%) a G2 and five (6%) had a G3 PanNEN. The median Ki-67 index was 4% (interquartile range: 1-8%). SRD and TLSRD significantly discriminated between pT3 or pT4 PanNEN versus pT1 or pT2, as well as 18F-FDG MTV and TLG. 68Ga-DOTATOC SUVmax was able to significantly predict the presence of distant metastases with a threshold of 51.27 (sensitivity and specificity of 85.7 and 68.1%, respectively). 18F-FDG MTV and TLG were predictors of angioinvasion. The cut-off threshold for MTV was 7.98 (sensitivity and specificity of 69.7 and 82.4%, respectively) ( p = 0.0004) whereas the cut-off for TLG was 32.4 (sensitivity and specificity of 69.7% and 82.4%, respectively) ( p = 0.0004)., Conclusion: Dual tracer 68Ga-DOTATOC and 18F-FDG PET scans provide relevant information regarding tumour behaviour and aggressiveness, implementing the diagnostic preoperative work-up.