0000000000061959

AUTHOR

Riccardo Laudicella

0000-0002-2842-0301

showing 9 related works from this author

Theragnostic Use of Radiolabelled Dota-Peptides in Meningioma: From Clinical Demand to Future Applications.

2019

Meningiomas account for approximately 30% of all new diagnoses of intracranial masses. The 2016 World Health Organization’s (WHO) classification currently represents the clinical standard for meningioma’s grading and prognostic stratification. However, watchful waiting is frequently the chosen treatment option, although this means the absence of a certain histological diagnosis. Consequently, MRI (or less frequently CT) brain imaging currently represents the unique available tool to define diagnosis, grading, and treatment planning in many cases. Nonetheless, these neuroimaging modalities show some limitations, particularly in the evaluation of skull base lesions. The emerging evidence supp…

Cancer Researchmedicine.medical_specialtypositron emission tomographymedicine.medical_treatmentReviewlcsh:RC254-282meningioma030218 nuclear medicine & medical imagingMeningioma03 medical and health sciences0302 clinical medicineNeuroimagingFunctional neuroimagingmedicineotorhinolaryngologic diseasesMedical diagnosisRadiation treatment planningGrading (tumors)neoplasmsMeningioma; Neuroimaging; Positron emission tomography; Radionuclide therapy; Somatostatin receptorneuroimagingbusiness.industryradionuclide therapylcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogensmedicine.diseasesomatostatin receptorOncologymeningioma; somatostatin receptor; neuroimaging; positron emission tomography; radionuclide therapy030220 oncology & carcinogenesisRadionuclide therapyRadiologybusinessWatchful waitingCancers
researchProduct

Choline PET/CT Features to Predict Survival Outcome in High Risk Prostate Cancer Restaging: A Preliminary Machine-Learning Radiomics Study

2020

Background Radiomic features are increasingly utilized to evaluate tumor heterogeneity in PET imaging but to date its role has not been investigated for Cho-PET in prostate cancer. The potential application of radiomics features analysis using a machine-learning radiomics algorithm was evaluated to select 18F-Cho PET/CT imaging features to predict disease progression in PCa. Methods We retrospectively analyzed high-risk PCa patients who underwent restaging 18F-Cho PET/CT from November 2013 to May 2018. 18F-Cho PET/CT studies and related structures containing volumetric segmentations were imported in the "CGITA" toolbox to extract imaging features from each lesion. A Machine-learning model h…

Malemedicine.medical_specialtyn artificial intelligence model demonstrated to be feasible and able to select a panel of 18F-Cho PET/CT features with valuable association with PCa patients' outcome.business.industryProstatic NeoplasmsFeature selectionPet imagingCholine pet ctmedicine.diseaseTumor heterogeneitySurvival outcomeCholineMachine LearningProstate cancerRadiomicsFeature (computer vision)Artificial IntelligencePositron Emission Tomography Computed TomographyMedicineHumansRadiology Nuclear Medicine and imagingRadiologybusinessRetrospective Studies
researchProduct

Potential clinical value of quantitative fluorine-18-fluorodeoxyglucose-PET/computed tomography using a graph-based method analysis in evaluation of …

2019

Objectives To identify the clinical relevance of incidentally detected lesions (IDLs) in the gastrointestinal tract (GIT) with 18F-FDG PET/CT and to assess the potential benefit of using semiquantitative PET measures to discern malignant from benign lesions. Methods Forty-one patients who underwent F-FDG PET/CT scans during the oncologic follow-up, revealing abnormal incidental 18F-FDG accumulations in the GIT were included in this retrospective analysis. Incidental PET/CT findings were correlated with endoscopic and histological findings. Semiquantitative PET values (SUVmax, SUVmean, SULpeak, and TLG) were evaluated by using a new graph-based method. Two sample t-test analysis has been per…

AdultMale-Endoscopy Gastrointestinal030218 nuclear medicine & medical imagingCorrelation03 medical and health sciences0302 clinical medicineFluorodeoxyglucose F18Positron Emission Tomography Computed TomographyBiopsymedicineImage Processing Computer-AssistedHumansRadiology Nuclear Medicine and imagingClinical significanceGastrointestinal NeoplasmsRetrospective StudiesGastrointestinal tractIncidental FindingsFluorine-18-fluorodeoxyglucosemedicine.diagnostic_testbusiness.industryRetrospective cohort studyGeneral Medicinemedicine.diseaseEndoscopyTumor BurdenDysplasia030220 oncology & carcinogenesisFemalebusinessNuclear medicineGlycolysisNuclear medicine communications
researchProduct

Radiomics Analysis of Brain [18F]FDG PET/CT to Predict Alzheimer’s Disease in Patients with Amyloid PET Positivity: A Preliminary Report on the Appli…

2022

Background: Early in-vivo diagnosis of Alzheimer’s disease (AD) is crucial for accurate management of patients, in particular, to select subjects with mild cognitive impairment (MCI) that may evolve into AD, and to define other types of MCI non-AD patients. The application of artificial intelligence to functional brain [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography(CT) aiming to increase diagnostic accuracy in the diagnosis of AD is still undetermined. In this field, we propose a radiomics analysis on advanced imaging segmentation method Statistical Parametric Mapping (SPM)-based completed with a Machine-Learning (ML) application to predict the diagnosi…

radiomics; Alzheimer’s disease; PET/CT; machine learningAlzheimer’s disease; machine learning; PET/CT; radiomicsmachine learningPET/CTradiomicsradiomicClinical Biochemistryradiomics; Alzheimer's disease; PET/CT; machine learningAlzheimer’s diseaseDiagnostics
researchProduct

Radiomics analysis of 18F-Choline PET/CT in the prediction of disease outcome in high-risk prostate cancer: an explorative study on machine learning …

2021

Objective: The aim of this study was (1) to investigate the application of texture analysis of choline PET/CT images in prostate cancer (PCa) patients and (2) to propose a machine-learning radiomics model able to select PET features predictive of disease progression in PCa patients with a same high-risk class at restaging. Material and methods: Ninety-four high-risk PCa patients who underwent restaging Cho-PET/CT were analyzed. Follow-up data were recorded for a minimum of 13 months after the PET/CT scan. PET images were imported in LIFEx toolbox to extract 51 features from each lesion. A statistical system based on correlation matrix and point-biserial-correlation coefficient has been impl…

Malemedicine.medical_specialtyMachine learningcomputer.software_genre030218 nuclear medicine & medical imagingCholineCorrelationMachine Learning03 medical and health sciences0302 clinical medicineArtificial IntelligencePositron Emission Tomography Computed TomographymedicineHumansRadiology Nuclear Medicine and imagingCholine; Machine learning; Positron emission tomography computed tomography; Prostate cancer; Radiomics.Prospective StudiesEntropy (energy dispersal)Prospective cohort studySurvival analysisPET-CTbusiness.industryProstatic NeoplasmsGeneral MedicineLinear discriminant analysismedicine.diseasePrimary tumorFeature (computer vision)030220 oncology & carcinogenesisRadiologyArtificial intelligenceNeoplasm Recurrence LocalbusinesscomputerMachine learning Positron emission tomography computed tomography Prostate cancer Radiomics Artificial Intelligence
researchProduct

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

2022

AbstractIn 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…

MaleArtificial intelligencePositron emission tomographyProstate cancerRadiomicsTheragnosticsProstatic Neoplasms610 Medicine & health10181 Clinic for Nuclear MedicineMultimodal ImagingImage Processing Computer-AssistedQuality of Life2741 Radiology Nuclear Medicine and ImagingHumansRadiology Nuclear Medicine and imaging
researchProduct

The role of PET radiomic features in prostate cancer: a systematic review

2021

Aim: This systematic review aims to present the available evidence on the use of radiomic features (RFs) extracted from PET imaging in patients with prostate cancer (PCa). Materials and methods: A comprehensive literature search of studies on the utility of PET-derived RFs in patients with PCa was performed in the PubMed/MEDLINE database through February 24th, 2021 using the following search string: [“positron-emission tomography” (MeSh terms) OR “positron emission tomography computed tomography” (MeSh terms) OR “positron-emission tomography” (all fields) OR “positron emission tomography computed tomography” (all fields) OR “PET” (all fields)] AND [“radiomics” (all fields) OR “radiomic” (al…

medicine.medical_specialtyPositron emission tomographymedicine.medical_treatmentRadiogenomics030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicineProstateMachine learningCarcinomamedicineRadiology Nuclear Medicine and imagingLymph nodeProstate cancerRadiomicsmedicine.diagnostic_testbusiness.industryInterventional radiologyDeep learningmedicine.diseaseRadiation therapymedicine.anatomical_structure030220 oncology & carcinogenesisRadiologyTomographybusiness
researchProduct

Clinical and Prognostic Value of 18F-FDG-PET/CT in the Restaging Process of Recurrent Cutaneous Melanoma

2020

Background: Several studies on 18F-FDG-PET/CT have investigated the prognostic role of this imaging modality in different tumors after treatment. Nevertheless, its role in restaging patients with recurrent CM still needs to be defined. Objective: The aim of this retrospective multicenter study was to evaluate the clinical and prognostic impact of 18F-FDG-PET/CT on the restaging process of cutaneous melanoma (CM) after surgery in patients with suspected distant recurrent disease or suspected metastatic progression disease. Materials and Methods: 74 patients surgically treated for CM underwent 18F-FDG-PET/CT for suspected distant recurrent disease or suspected metastatic progression disease.…

PharmacologyPET-CTmedicine.medical_specialtybusiness.industryProportional hazards modelMelanomaArea under the curveHistologyDiseasemedicine.disease030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicine030220 oncology & carcinogenesisCutaneous melanomaMedical imagingmedicineRadiology Nuclear Medicine and imagingRadiologybusinessCurrent Radiopharmaceuticals
researchProduct

Artificial Intelligence Applications on Restaging [18F]FDG PET/CT in Metastatic Colorectal Cancer: A Preliminary Report of Morpho-Functional Radiomic…

2022

Featured Application Based on results defined in this study, new investigations might propose morpho-functional-based radiomics algorithms for risk stratification with possible impact on treatment management in colorectal cancer. The aim of this study was to investigate the application of [F-18]FDG PET/CT images-based textural features analysis to propose radiomics models able to early predict disease progression (PD) and survival outcome in metastatic colorectal cancer (MCC) patients after first adjuvant therapy. For this purpose, 52 MCC patients who underwent [F-18]FDGPET/CT during the disease restaging process after the first adjuvant therapy were analyzed. Follow-up data were recorded f…

Fluid Flow and Transfer ProcessescolonradiomicsProcess Chemistry and TechnologyGeneral Engineeringpositron emission tomography-computed tomographycancercolon; cancer; radiomics; artificial intelligence; positron emission tomography-computed tomography; nuclear medicineGeneral Materials Sciencenuclear medicineartificial intelligenceInstrumentationComputer Science Applications
researchProduct