Patient-specific gamma-index analysis to evaluate ^99mTc-MAA as a predictor for ⁹⁰Y glass microspheres liver radioembolisation dosimetry

ABSTRACT

Radioembolisation (RE) is a minimally invasive therapy for primary/metastatic liver tumours. Yttrium-90 (90Y) microspheres (MS) are infused through the hepatic artery. Positron emission tomography (PET) allows visualisation of the 90Y-MS distribution in the liver after the RE procedure. All patients are submitted to a pretherapeutic Technetium-99m (99mTc) macroaggregated albumin (MAA) perfusion scintigraphy and single-photon emission computed tomography (SPECT) liver imaging. This work investigates the value of pre-treatment 99mTc-MAA SPECT to predict intrahepatic 90Y-MS treatment dosimetry, using the gamma-index (γ-index) analytical method. Six treatments with MAA and MS administered in the same hepatic artery branches were retrospectively selected. Multimodal images were used for semi-automatic and manual segmentation of liver and tumour volumes. Absorbed dose was calculated on SPECT and PET maps using the Imalytics Research Workstation (Philips). The γ-index calculation and analysis were performed using ‘in-house’ software with multiple distance to agreement (DTA) and dose difference (DD) tolerance criteria. γ-index passing rate values of 80% and > 90% were achieved for respectively conservative 10 mm/10% and less conservative 15 mm/15% (DTA/DD) tolerance criteria. RE treatments performed in similar conditions to planning give γ-index passing rates (several DTA/DD criteria) indicating potential predictive power of dosimetry planning for post-radioembolisation dosimetry outcome.

KEYWORDS:

• Liver radioembolisation
• patient specific
• dose distribution
• gamma-index
• predictive power

Acknowledgements

PF is supported by a Champalimaud Foundation PhD grant.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethics

All patients signed informed written consent as per local Ethics Committee guidelines. This was a retrospective study completely blind of patient identification.