Abstract
Whole-body 123I-Metaiodobenzylguanidine (mIBG) scintigraphy is used as primary image modality to visualize neuroblastoma tumours and metastases because it is the most sensitive and specific radioactive tracer in staging the disease and evaluating the response to treatment. However, especially in paediatric neuroblastoma, information from mIBG scans is difficult to extract because of acquisition difficulties that produce low definition images, with poor contours, resolution and contrast. These problems limit physician assessment. Current oncological guidelines are based on qualitative observer-dependant analysis. This makes comparing results taken at different moments of therapy, or in different institutions, difficult. In this paper, we present a computerized method that processes an image and calculates a quantitative measurement considered as its entropy, suitable for the identification of abnormal uptake regions, for which there is enough suspicion that they may be a tumour or metastatic site. This measurement can also be compared with future scintigraphies of the same patient. Over 46 scintigraphies of 22 anonymous patients were tested; the procedure identified 96.7% of regions of abnormal uptake and it showed a low overall false negative rate of 3.3%. This method provides assistance to physicians in diagnosing tumours and also allows the monitoring of patients’ evolution.
Highlights
In the management of neuroblastoma, 123 I-Metaiodobenzylguanidine scintigraphy remains the most specific and sensible imaging modality of staging and response to therapy evaluation [1]
Peaks of higher intensity than expected are the main variable analyzed by radiologists when identifying the uptake regions [2]
The objective of our study is to assist physicians in the application of the scoring method recommended by the International Society of Paediatric Oncology Europe Neuroblastoma (SIOPEN)
Summary
In the management of neuroblastoma, 123 I-Metaiodobenzylguanidine (mIBG) scintigraphy remains the most specific and sensible imaging modality of staging and response to therapy evaluation [1]. A scintigraphic image is a representation of the radioactive distribution inside the body. Analyzing an image to detect shapes is a classic problem in literature [3]. Existing techniques cannot be applied to the images used in this article, since generally they have intrinsic problems of low resolution, low contrast and low definition, asides from noise as an important factor in its deterioration [4,5]. The proposed method performs a preprocessing of the image, extracting numeric values, which highlights the zones with a high probability of containing a tumour or metastasis [6]
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