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NCT Number: NCT07174089

New AI-based Technologies in Nuclear Medicine

The study aims to identify and predict radiopharmaceutical extravasation events using new semi-quantitative parameters and machine learning models. It involves dose rate measurements to develop metrics for real-time monitoring. It also investigates the correlation between extravasation and SUV correction in PET/CT diagnostics, providing an estimate of the correction factor necessary for accurate SUV evaluation in case of an extravasation event.

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Key information

Age range

18 year–90 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Azienda USL IRCCS di Reggio Emilia

Reggio Emilia, Italy

Location status: Recruiting

Location contact

Mauro Iori, MD

PRINCIPAL_INVESTIGATOR

About this study

This is a descriptive, observational, non-profit study aimed at detecting and predicting extravasation events during the administration of radiopharmaceuticals for diagnostic and therapeutic purposes in nuclear medicine. Extravasation can lead to local tissue damage and compromise the accuracy of semi-quantitative imaging parameters such as the Standardized Uptake Value (SUV), widely used in PET/CT for diagnosis, staging, and therapy response evaluation. Literature reports that extravasation may cause a 21-50% change in SUV, potentially leading to incorrect assessment of tumor response.

The study will use a CE-marked portable spectroscopic personal radiation detector (RadEye SPRD-ER, Thermo Fisher Scientific™), already validated in a previous Ethics Committee-approved study, to record dose-rate (DR) curves during radiopharmaceutical injections. Using these data, new dosimetric metrics will be developed to characterize correct, abnormal, and extravasation events. Machine learning (ML) algorithms will be trained on patient clinical data, injection metrics, and DR curves to classify injection events in real time and to estimate correction factors for SUV quantification. Monte Carlo simulations (MCNP code, anthropomorphic phantoms, and reconstructed patient geometries) will be performed to evaluate absorbed dose distributions in extravascular regions.

The project is structured into three phases:

Phase 1 (Data Acquisition & Analysis): Real-time monitoring with RadEye SPRD-ER, extraction of quantitative metrics (DRmax, DRmean, Δp, t*, Δt), development of ML classifiers and regression models for SUV correction.

Phase 2 (Monte Carlo Simulations): Activity and dose calibration, dose distribution modeling in extravascular tissues.

Phase 3 (Dissemination): Scientific publications and presentation of results at international conferences.

This study has the potential to improve safety, diagnostic reliability, and accuracy of radiopharmaceutical administrations by introducing predictive monitoring and real-time correction of quantitative imaging parameters.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • patients undergoing PET/CT scans or therapeutic treatments with radiopharmaceuticals labelled with alpha or beta emitting nuclides

Exclusion criteria

  • patients whose clinical or psychological conditions do not allow for their involvement

Treatment and study plan

RadEye SPRD-ER device: spectrometric radiation detector capable of detecting gamma radiation.

Other

Acquisition of data during the infusion of PET radiotracers and the administration of α and β emitting radiopharmaceuticals for therapy.

Primary outcomes

  1. Characterization of new semi-quantitative metrics to detect extravasation events

    Time frame: During and immediately after radiopharmaceutical injection

    Identification and validation of quantitative parameters derived from dose-rate (DR) curves capable of reliably distinguishing between normal injection, abnormal venous retention, and extravasation events. Metrics will be applicable to both therapeutic radiopharmaceuticals (α and β emitters) and diagnostic radiotracers (e.g., PET/CT)

Secondary outcomes

  1. Correlation between extravasation severity and SUV alterations in nuclear medicine diagnostics

    Time frame: within 90 minutes after radiopharmaceutical administration

    Identification and quantification of the relationship between the extent of radiopharmaceutical extravasation and changes in Standardized Uptake Value (SUV) in diagnostic imaging. This analysis will be performed using Monte Carlo simulations and OLINDA software for activity estimation and dosimetric calibration. Patient-specific imaging data (CT, PET) will be used to model extravasation events and evaluate their impact on SUV quantification.

Study contacts

Contact information is provided by the study sponsor or research team.

Federica Fioroni, MD

CONTACT

[email protected]

0522/296653

Mauro Iori, MD

CONTACT

[email protected]

0522/296655

Sponsors and collaborators

Lead sponsor

Azienda USL Reggio Emilia - IRCCS

Other Gov

Registry information

Official study title

New AI-based Technologies for Even Safer and More Precise Nuclear Medicine

Acronym: AI-basedMedNuc

Important dates

Study start
2021
Primary completion
2022
Study completion
2026
First posted
Sep 15, 2025
Registry last updated
May 29, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.