The LUTADOSE trial: tumour dosimetry after the first administration predicts progression free survival in gastro-entero-pancreatic neuroendocrine tumours (GEP NETs) patients treated with [Lu]Lu-DOTATATE.

Purpose: In Peptide Receptor Radionuclide Therapy (PRRT) with [Lu]Lu-DOTATATE of gastro-entero-pancreatic neuroendocrine tumours (GEP NETs) a question remains open about the potential benefits of personalised dosimetry. This observational prospective study examines the association of individualized dosimetry with progression free survival (PFS) in G1-G2 GEP NETs patients following the standard [Lu]Lu-DOTATATE therapeutic regimen.

Methods: The analysis was conducted on 42 patients administered 4 times, and on 165 lesions.

Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data.

Medical imaging represents the primary tool for investigating and monitoring several diseases, including cancer. The advances in quantitative image analysis have developed towards the extraction of biomarkers able to support clinical decisions. To produce robust results, multi-center studies are often set up.

The complementary role of PSMA expression and [F]FDG PET/CT in predicting thyroid cancer outcome: from black and white to shades of gray, in the era of precision oncology.

Background: The value of Prostate Specific Membrane Antigen (PSMA) in thyroid carcinoma (TC) is still unknown. We aimed to test the potential complementary role of PSMA expression and 2-[F]fluoro-2-deoxy-D-glucose ([F]FDG) uptake on PET/CT as biomarkers for TC outcome prediction.

Materials And Methods: From a retrospective cohort of TC patients we selected those fulfilling the following inclusion/exclusion criteria: thyroidectomy in our Institution, available primary tumor tissue PSMA immunostaining, [F]FDG PET/CT and follow-up data.

FAP expression in alpha cells of Langherhans insulae-implications for FAPI radiopharmaceuticals' use.

Purpose: Radiopharmaceuticals targeting fibroblast activation protein (FAP) alpha are increasingly studied for diagnostic and therapeutic applications. We discovered FAP expression at immunohistochemistry (IHC) in the alpha cells of the Langerhans insulae of few patients. Therefore, we planned an investigation aimed at describing FAP expression in the pancreas and discussing the implications for radioligand applications.

Explainable domain transfer of distant supervised cancer subtyping model via imaging-based rules extraction.

Image texture analysis has for decades represented a promising opportunity for cancer assessment and disease progression evaluation, evolving in a discipline, i.e., radiomics.

The Development of an Intelligent Agent to Detect and Non-Invasively Characterize Lung Lesions on CT Scans: Ready for the "Real World"?

(1) Background: Once lung lesions are identified on CT scans, they must be characterized by assessing the risk of malignancy. Despite the promising performance of computer-aided systems, some limitations related to the study design and technical issues undermine these tools' efficiency; an "intelligent agent" to detect and non-invasively characterize lung lesions on CT scans is proposed. (2) Methods: Two main modules tackled the detection of lung nodules on CT scans and the diagnosis of each nodule into benign and malignant categories.

Hybrid PET/MRI in Infection and Inflammation: An Update About the Latest Available Literature Evidence.

PET/MRI has been reported to be promising in the diagnosis and evaluation of infection and inflammation including brain disorders, bone and soft tissue infections and inflammations, cardiovascular, abdominal, and systemic diseases. However, evidence came out manly from anecdotal cases or small cohorts. The present review aimed to update the latest available evidence about the role of PET/MRI in infection and inflammation.

Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs.

To identify the best transfer learning approach for the identification of the most frequent abnormalities on chest radiographs (CXRs), we used embeddings extracted from pretrained convolutional neural networks (CNNs). An explainable AI (XAI) model was applied to interpret black-box model predictions and assess its performance. Seven CNNs were trained on CheXpert.

COVID-19 vaccination, implications for PET/CT image interpretation and future perspectives.

Introduction: The present paper aims to systematically review the literature on COVID-19 vaccine-related findings in patients undergoing PET/CT.

Methods: The search algorithms included the following combination of terms: "PET" OR "positron emission tomography" AND "COVID"; "PET" OR "positron emission tomography" AND "COVID" AND "vaccination"; "PET" OR "positron emission tomography" AND "COVID", AND "autoimmune".

Results: We selected 17 articles which were assessed for quality and included in the systematic analysis.

Application of FLIC model to predict adverse events onset in neuroendocrine tumors treated with PRRT.

To develop predictive models of side effect occurrence in GEPNET treated with PRRT. Metastatic GEPNETs patients treated in our centre with PRRT (177Lu-Oxodotreotide) from 2019 to 2020 were considered. Haematological, liver and renal toxicities were collected and graded according to CTCAE v5.

The Impact of COVID-19 on Nuclear Medicine in Europe.

The COVID-19 pandemic has profoundly changed hospital activities, including nuclear medicine (NM) practice. This review aimed to determine and describe the impact of COVID-19 on NM in Europe and critically discuss actions and strategies applied to face the pandemic. A literature search for relevant articles was performed on PubMed, covering COVID-19 studies published up until January 21, 2021.

Methodological framework for radiomics applications in Hodgkin's lymphoma.

Background: According to published data, radiomics features differ between lesions of refractory/relapsing HL patients from those of long-term responders. However, several methodological aspects have not been elucidated yet.

Purpose: The study aimed at setting up a methodological framework in radiomics applications in Hodgkin's lymphoma (HL), especially at (a) developing a novel feature selection approach, (b) evaluating radiomic intra-patient lesions' similarity, and (c) classifying relapsing refractory (R/R) vs non-(R/R) patients.

State-of-the-art of FAPI-PET imaging: a systematic review and meta-analysis.

Introduction: Fibroblast activation protein-α (FAPα) is overexpressed on cancer-associated fibroblasts in approximately 90% of epithelial neoplasms, representing an appealing target for therapeutic and molecular imaging applications. [ Ga]Ga-labelled radiopharmaceuticals-FAP-inhibitors (FAPI)-have been developed for PET. We systematically reviewed and meta-analysed published literature to provide an overview of its clinical role.

Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer.

Objective: The objectives of our study were to assess the association of radiomic and genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC).

Methods: In this retrospective single-centre observational study, we selected 151 surgically treated patients with adenocarcinoma or squamous cell carcinoma who performed baseline [18F] FDG PET/CT. A subgroup of patients with cancer tissue samples at the Institutional Biobank (n = 74/151) was included in the genomic analysis.

Distributed learning: a reliable privacy-preserving strategy to change multicenter collaborations using AI.

Purpose: The present scoping review aims to assess the non-inferiority of distributed learning over centrally and locally trained machine learning (ML) models in medical applications.

Methods: We performed a literature search using the term "distributed learning" OR "federated learning" in the PubMed/MEDLINE and EMBASE databases. No start date limit was used, and the search was extended until July 21, 2020.

Climbing the steps of the evidence-based medicine pyramid: highlights from Annals of Nuclear Medicine 2019.

We aimed to provide an overview on research path in nuclear medicine climbing the steps of the Evidence-Based Medicine (EBM) pyramid using review of 14 subjectively selected papers out of 111 published in the Annals of Nuclear Medicine during January-December 2019. Following the structure of the EBM hierarchy, we chose at least one study for each step of the pyramid from the basis (pre-clinical research, expert opinion, case report and case series), to the middle (case-control and cohort studies, randomised controlled trials), towards the top (meta-analyses and systematic reviews). Additionally, we collected information on the promoter of each included study: investigator-initiated trials (IITs) vs industry-sponsored trials (ISTs).

Radiomics of MRI for pretreatment prediction of pathologic complete response, tumor regression grade, and neoadjuvant rectal score in patients with locally advanced rectal cancer undergoing neoadjuvant chemoradiation: an international multicenter study.

Objective: To investigate whether pretreatment MRI-based radiomics of locally advanced rectal cancer (LARC) and/or the surrounding mesorectal compartment (MC) can predict pathologic complete response (pCR), neoadjuvant rectal (NAR) score, and tumor regression grade (TRG).

Methods: One hundred thirty-two consecutive patients with LARC who underwent neoadjuvant chemoradiation and total mesorectal excision (TME) were retrospectively collected from 2 centers in the USA and Italy. The primary tumor and surrounding MC were segmented on the best available T2-weighted sequence (axial, coronal, or sagittal).

Imaging-Based Prediction of Molecular Therapy Targets in NSCLC by Radiogenomics and AI Approaches: A Systematic Review.

The objective of this systematic review was to analyze the current state of the art of imaging-derived biomarkers predictive of genetic alterations and immunotherapy targets in lung cancer. We included original research studies reporting the development and validation of imaging feature-based models. The overall quality, the standard of reporting and the advancements towards clinical practice were assessed.

FDG-PET/CT findings highly suspicious for COVID-19 in an Italian case series of asymptomatic patients.

Aim: To illustrate the [18F]FDG-PET/CT findings in patients affected by cancer with clinical diagnosis of Covid-19 METHODS: We retrospectively reviewed the cases of patients who showed pulmonary involvement unrelated to cancer metastases on March 13 and 16 2020. We reviewed the scans, collected medical history, and exposure information.

Results: Among the 13 scans, we identified 5 cases with imaging findings suspicious for viral infection.

Computed tomography (CT)-derived radiomic features differentiate prevascular mediastinum masses as thymic neoplasms versus lymphomas.

Objectives: We aimed to assess the ability of radiomics, applied to not-enhanced computed tomography (CT), to differentiate mediastinal masses as thymic neoplasms vs lymphomas.

Methods: The present study was an observational retrospective trial. Inclusion criteria were pathology-proven thymic neoplasia or lymphoma with mediastinal localization, availability of CT.