journal article·2022-10-19Open access

A Workflow for Dosimetry of 90Y Radioembolization Based on Quantitative 99mTc-MAA SPECT/CT Imaging and a 3D-Printed Phantom

Sara Ungania, Marco D’Arienzo, Emilio Mezzenga, Giuseppe Pizzi, Giulio Vallati, Anna Ianiro, Sandra Rea, Rosa Sciuto, Antonella Soriani, Lidia Strigari

Applied Sciences· Volume 12· Issue 20

Abstract

At a time of increasing evidence for dose-effect relationships in radioembolization (RE) with 90Y-microspheres, the general consensus is that there is an urgent need for accurate treatment planning and dose assessment in patients undergoing RE treatment. This work aimed at assessing the usefulness of 99mTc macroaggregated albumin (MAA) SPECT/CT imaging for personalized provisional RE dosimetry considering a 3D-printed patientlike phantom (AdboMan phantom). A homemade tool was developed in MATLAB for image analysis and absorbed dose calculation. Two dose calculaton methods were implemented and used to calculate dose volume histograms: (I) dose kernel method and (II) local energy deposition method. The accuracy of the two different dosimetric methods was evaluated by means of 3D γ-index (1%–1 mm and 2%–2 mm) implemented in the tool. Differences between the two dose calculation methods using the 3D γ-index are within 1%–1 mm and 2%–2 mm for all AbdoMan inserts, with a passing rate of 99.9% and 100%, respectively, proving a good agreement between the two calculation methods. The present study supports the use of 99mTc-MAA SPECT acquisition for provisional dosimetry along with the local energy deposition method to convert reconstructed SPECT data into absorbed dose maps. As long as 99mTc-MAA SPECT acquisitions are performed on liver lesions larger than 40 mm, the absorbed dose computed by means of the local energy deposition method can lead to results in line with those obtained by Monte Carlo calculations.
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Research context

OpenAlex topics: Advanced Radiotherapy Techniques · Medical Imaging Techniques and Applications · Hepatocellular Carcinoma Treatment and Prognosis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Laboratory of Medical Physics and Expert System, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy

Medical Physics, ASL Roma 6, 00041 Rome, Italy

Medical Physics Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, 47014 Meldola, Italy

Radiology Department, Regina Elena National Cancer Institute, 00144 Rome, Italy

Nuclear Medicine Department, Regina Elena National Cancer Institute, 00144 Rome, Italy

Department of Medical Physics, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40139 Bologna, Italy

Funding

Associazione Italiana per la Ricerca sul Cancro (AIRC)

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