Ali Alhuseinalkhudhur1,2, Mark Lubberink3, Henrik Lindman4, Vladimir Tolmachev4,5, Fredrik Y Frejd4,6, Joachim Feldwisch4,6, Irina Velikyan3, Jens Sörensen3. 1. Nuclear Medicine and PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. ali.alkhudhur@igp.uu.se. 2. Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden. ali.alkhudhur@igp.uu.se. 3. Nuclear Medicine and PET, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. 4. Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden. 5. Research Centrum for Oncotheranostics, Research School of Chemistry and Applied Biomedical Sciences, Research Tomsk Polytechnic University, Tomsk, Russia. 6. Affibody AB, Solna, Sweden.
Abstract
BACKGROUND: High expression of human epidermal growth factor receptor type 2 (HER2) represents an aggressive subtype of breast cancer. Anti-HER2 treatment requires a theragnostic approach wherein sufficiently high receptor expression in biopsy material is mandatory. Heterogeneity and discordance of HER2 expression between primary tumour and metastases, as well as within a lesion, present a complication for the treatment and require multiple biopsies. Molecular imaging using the HER2-targeting Affibody peptide ABY-025 radiolabelled with 68Ga-gallium for PET/CT is currently under investigation as a non-invasive tool for whole-body evaluation of metastatic HER2 expression. Initial studies demonstrated a high correlation between 68Ga-ABY-025 standardized uptake values (SUVs) and histopathology. However, detecting small liver lesions might be compromised by high background uptake. This study aimed to explore the applicability of kinetic modelling and parametric image analysis for absolute quantification of 68Ga-ABY-025 uptake and HER2-receptor expression and how that relates to static SUVs. METHODS: Dynamic 68Ga-ABY-025 PET of the upper abdomen was performed 0-45 min post-injection in 16 patients with metastatic breast cancer. Five patients underwent two examinations to test reproducibility. Parametric images of tracer delivery (K1) and irreversible binding (Ki) were created with an irreversible two-tissue compartment model and Patlak graphical analysis using an image-derived input function from the descending aorta. A volume of interest (VOI)-based analysis was performed to validate parametric images. SUVs were calculated from 2 h and 4 h post-injection static whole-body images and compared to Ki. RESULTS: Characterization of HER2 expression in smaller liver metastases was improved using parametric images. Ki values from parametric images agreed very well with VOI-based gold standard (R2 > 0.99, p < 0.001). SUVs of metastases at 2 h and 4 h post-injection were highly correlated with Ki values from both the two-tissue compartment model and Patlak method (R2 = 0.87 and 0.95, both p < 0.001). 68Ga-ABY-025 PET yielded high test-retest reliability (relative repeatability coefficient for Patlak 30% and for the two-tissue compartment model 47%). CONCLUSION: 68Ga-ABY-025 binding in HER2-positive metastases was well characterized by irreversible two-tissue compartment model wherein Ki highly correlated with SUVs at 2 and 4 h. Dynamic scanning with parametric image formation can be used to evaluate metastatic HER2 expression accurately.
BACKGROUND: High expression of humanepidermal growth factor receptor type 2 (HER2) represents an aggressive subtype of breast cancer. Anti-HER2 treatment requires a theragnostic approach wherein sufficiently high receptor expression in biopsy material is mandatory. Heterogeneity and discordance of HER2 expression between primary tumour and metastases, as well as within a lesion, present a complication for the treatment and require multiple biopsies. Molecular imaging using the HER2-targeting Affibody peptide ABY-025 radiolabelled with 68Ga-gallium for PET/CT is currently under investigation as a non-invasive tool for whole-body evaluation of metastatic HER2 expression. Initial studies demonstrated a high correlation between 68Ga-ABY-025 standardized uptake values (SUVs) and histopathology. However, detecting small liver lesions might be compromised by high background uptake. This study aimed to explore the applicability of kinetic modelling and parametric image analysis for absolute quantification of 68Ga-ABY-025 uptake and HER2-receptor expression and how that relates to static SUVs. METHODS: Dynamic 68Ga-ABY-025 PET of the upper abdomen was performed 0-45 min post-injection in 16 patients with metastatic breast cancer. Five patients underwent two examinations to test reproducibility. Parametric images of tracer delivery (K1) and irreversible binding (Ki) were created with an irreversible two-tissue compartment model and Patlak graphical analysis using an image-derived input function from the descending aorta. A volume of interest (VOI)-based analysis was performed to validate parametric images. SUVs were calculated from 2 h and 4 h post-injection static whole-body images and compared to Ki. RESULTS: Characterization of HER2 expression in smaller liver metastases was improved using parametric images. Ki values from parametric images agreed very well with VOI-based gold standard (R2 > 0.99, p < 0.001). SUVs of metastases at 2 h and 4 h post-injection were highly correlated with Ki values from both the two-tissue compartment model and Patlak method (R2 = 0.87 and 0.95, both p < 0.001). 68Ga-ABY-025 PET yielded high test-retest reliability (relative repeatability coefficient for Patlak 30% and for the two-tissue compartment model 47%). CONCLUSION: 68Ga-ABY-025 binding in HER2-positive metastases was well characterized by irreversible two-tissue compartment model wherein Ki highly correlated with SUVs at 2 and 4 h. Dynamic scanning with parametric image formation can be used to evaluate metastatic HER2 expression accurately.
Entities:
Keywords:
Affibody; Dynamic PET; HER2 receptor; Kinetic modelling; Metastatic breast cancer
Authors: Victoria O Shipunova; Olga A Kolesnikova; Polina A Kotelnikova; Vladislav D Soloviev; Anton A Popov; Galina M Proshkina; Maxim P Nikitin; Sergey M Deyev Journal: ACS Omega Date: 2021-06-10