Secondary Logo

Journal Logo

Institutional members access full text with Ovid®

Bone scan index as metastatic bone disease quantifier and predictor of radium-223-dichloride biochemical response

Roque, Valentina; Jessop, Maryamb; Pereira, Luisac; Gape, Paulb; Dizdarevic, Sabinab; Sousa, Evaa,d; Carolino, Elizabetea,e

Nuclear Medicine Communications: June 2019 - Volume 40 - Issue 6 - p 588–596
doi: 10.1097/MNM.0000000000001005
ORIGINAL ARTICLES
Buy

Objectives This work aims to assess whether the biochemical response of radium-223-dichloride treatment can be predicted based on the pretherapy bone scan, and consequently if bone scan index (BSI) and maximum lesion intensity have a place as alternatives or as complements to extent of bone disease (EOBD) scoring in predicting biochemical response to treatment. Many cases of advanced prostate cancer have evidence of bone metastasis. Accurate EOBD quantification could help predict the response to radium-223-dichloride therapy. Current EOBD score is simple to use but does not consider size, intensity or localisation of lesion BSI might be more suitable for stratification of bone metastases.

Patients and methods Bone scans (n=20) preceding radium-223-dichloride treatment for prostate cancer were assessed retrospectively using automated BSI software (EXINI) and by assessing maximum counts per lesion. Results were then compared to total alkaline phosphatase (ALP) as a measure of biochemical response to therapy using linear regressions and to their EOBD scores using box plot analysis.

Results Moderate correlation was found between ALP response and maximum lesion intensity (R2=0.41) and BSI (R2=0.46). Strong correlation (R2=0.71) was found between baseline ALP and BSI and between lesion number and BSI (R2=0.60). Visual assessment of EOBD score was found to correlate well with baseline ALP and maximum ALP response.

Conclusion BSI is a useful asset in stratification of patients with metastatic bone disease. It may also have a place in prediction of biochemical response.

aDepartment of Radiation Sciences and Technologies and Health Biosignals, Lisbon School of Health Technology, Lisbon, Portugal

bNuclear Medicine, Department of Imaging, Brighton and Sussex University Hospitals, NHS Trust, Brighton

cDepartment of Nuclear Medicine Physics, Maidstone and Tunbridge Wells NHS Trust, Maidstone, UK

dDepartment of Mechanical Engineering, Research Group on Modeling and Optimization of Multifunctional Systems

eH&TRC- Health & Technology Research Center, Lisbon, Portugal

Correspondence to Valentin Roque, BSc, Av. Dom João II MB, Lisbon 1990 094, Portugal Tel: +351 915 952 497; e-mail: valentimrq@gmail.com

Received December 5, 2018

Received in revised form January 18, 2019

Accepted February 10, 2019

Copyright © 2019 Wolters Kluwer Health, Inc. All rights reserved.