New AI-based Technologies in Nuclear Medicine

NCT ID: NCT07174089

Last Updated: 2025-09-15

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

1500 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-07-30

Study Completion Date

2026-03-31

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Patients Undergoing PET/CT Investigation or Nuclear Medicine Therapy

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Patients undergoing radiotherapy

The individuals studied will all be patients administered with radiopharmaceuticals for diagnostic and therapy purposes (aged between 18 and 90).

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

Intervention Type OTHER

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

Interventions

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

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

Intervention Type OTHER

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Maximum Eligible Age

90 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Azienda USL Reggio Emilia - IRCCS

OTHER_GOV

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Azienda USL IRCCS di Reggio Emilia

Reggio Emilia, , Italy

Site Status RECRUITING

Countries

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Italy

Central Contacts

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Mauro Iori, MD

Role: CONTACT

0522/296655

Federica Fioroni, MD

Role: CONTACT

0522/296653

References

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Wilson S, Osborne D, Long M, Knowland J, Fisher DR. Practical Tools for Patient-specific Characterization and Dosimetry of Radiopharmaceutical Extravasation. Health Phys. 2022 Nov 1;123(5):343-347. doi: 10.1097/HP.0000000000001600. Epub 2022 Jul 15.

Reference Type BACKGROUND
PMID: 35838538 (View on PubMed)

Iori M, Grassi E, Piergallini L, Meglioli G, Botti A, Sceni G, Cucurachi N, Verzellesi L, Finocchiaro D, Versari A, Fraboni B, Fioroni F. Safety injections of nuclear medicine radiotracers: towards a new modality for a real-time detection of extravasation events and 18F-FDG SUV data correction. EJNMMI Phys. 2023 May 23;10(1):31. doi: 10.1186/s40658-023-00556-5.

Reference Type BACKGROUND
PMID: 37221434 (View on PubMed)

Tylski P, Pina-Jomir G, Bournaud-Salinas C, Jalade P. Tissue dose estimation after extravasation of 177Lu-DOTATATE. EJNMMI Phys. 2021 Mar 31;8(1):33. doi: 10.1186/s40658-021-00378-3.

Reference Type BACKGROUND
PMID: 33788043 (View on PubMed)

Kiser JW, Benefield T, Lattanze RK, Ryan KA, Crowley J. Assessing and Reducing Positron Emission Tomography/Computed Tomography Radiotracer Infiltrations: Lessons in Quality Improvement and Sustainability. JCO Oncol Pract. 2020 Jul;16(7):e636-e640. doi: 10.1200/JOP.19.00302. Epub 2020 Feb 11.

Reference Type BACKGROUND
PMID: 32045542 (View on PubMed)

Williams JM, Arlinghaus LR, Rani SD, Shone MD, Abramson VG, Pendyala P, Chakravarthy AB, Gorge WJ, Knowland JG, Lattanze RK, Perrin SR, Scarantino CW, Townsend DW, Abramson RG, Yankeelov TE. Towards real-time topical detection and characterization of FDG dose infiltration prior to PET imaging. Eur J Nucl Med Mol Imaging. 2016 Dec;43(13):2374-2380. doi: 10.1007/s00259-016-3477-3. Epub 2016 Aug 25.

Reference Type BACKGROUND
PMID: 27557845 (View on PubMed)

Osborne D, Lattanze R, Knowland J, Bryant TE, Barvi I, Fu Y, Kiser JW. The Scientific and Clinical Case for Reviewing Diagnostic Radiopharmaceutical Extravasation Long-Standing Assumptions. Front Med (Lausanne). 2021 Jun 28;8:684157. doi: 10.3389/fmed.2021.684157. eCollection 2021.

Reference Type BACKGROUND
PMID: 34262915 (View on PubMed)

Bilgic S. FDG Extravasation in PET/CT Imaging: A Visual Grading Approach Based on Clinical Observations. J Med Imaging Radiat Oncol. 2025 Sep;69(6):617-625. doi: 10.1111/1754-9485.13876. Epub 2025 Jul 2.

Reference Type BACKGROUND
PMID: 40600568 (View on PubMed)

van der Pol J, Voo S, Bucerius J, Mottaghy FM. Consequences of radiopharmaceutical extravasation and therapeutic interventions: a systematic review. Eur J Nucl Med Mol Imaging. 2017 Jul;44(7):1234-1243. doi: 10.1007/s00259-017-3675-7. Epub 2017 Mar 16.

Reference Type BACKGROUND
PMID: 28303300 (View on PubMed)

Other Identifiers

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267/2022/SPER/IRCCSRE

Identifier Type: -

Identifier Source: org_study_id

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