An innovative iterative thresholding algorithm for tumour segmentation and volumetric quantification on SPECT images: Monte Carlo-based methodology and validation

• Published in: Medical physics (Lancaster) 2011-06, Vol.38 (6), p.3050-3061
• Main Authors: Pacilio, M., Basile, C., Shcherbinin, S., Caselli, F., Ventroni, G., Aragno, D., Mango, L., Santini, E.
• Format: Article
• Language: English
• Subjects: Algorithms; Applied neuroscience; Biological Transport; brain; Brain Neoplasms - diagnostic imaging; Brain Neoplasms - secondary; Calibration; Cancer; Computed tomography; Distribution theory and Monte Carlo studies; Glioma - diagnostic imaging; Glioma - pathology; Humans; image segmentation; iterative methods; Lung Neoplasms - pathology; mathematics computing; medical image processing; Medical image reconstruction; Medical image segmentation; Medical imaging; Monte Carlo; Monte Carlo Method; Monte Carlo methods; Neoplasms - diagnostic imaging; Neoplasms - pathology; Neuroscience; Numerical approximation and analysis; phantoms; Phantoms, Imaging; Positron emission tomography; Segmentation; single photon emission computed tomography; Single photon emission computed tomography (SPECT); Spatial resolution; SPECT; Standards and calibration; statistical analysis; thresholding; Tomography, Emission-Computed, Single-Photon - methods; Tumor Burden; tumours
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1118/1.3590359

Purpose: Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging play an important role in the segmentation of functioning parts of organs or tumours, but an accurate and reproducible delineation is still a challenging task. In this work, an innovative iterative thresholding method for tumour segmentation has been proposed and implemented for a SPECT system. This method, which is based on experimental threshold-volume calibrations, implements also the recovery coefficients (RC) of the imaging system, so it has been called recovering iterative thresholding method (RIThM). The possibility to employ Monte Carlo (MC) simulations for system calibration was also investigated.Methods: The RIThM is an iterative algorithm coded using matlab: after an initial rough estimate of the volume of interest, the following calculations are repeated: (i) the corresponding source-to-background ratio (SBR) is measured and corrected by means of the RC curve; (ii) the threshold corresponding to the amended SBR value and the volume estimate is then found using threshold-volume data; (iii) new volume estimate is obtained by image thresholding. The process goes on until convergence. The RIThM was implemented for an Infinia Hawkeye 4 (GE Healthcare) SPECT/CT system, using a Jaszczak phantom and several test objects. Two MC codes were tested to simulate the calibration images: SIMIND and SimSet. For validation, test images consisting of hot spheres and some anatomical structures of the Zubal head phantom were simulated with SIMIND code. Additional test objects (flasks and vials) were also imaged experimentally. Finally, the RIThM was applied to evaluate three cases of brain metastases and two cases of high grade gliomas.Results: Comparing experimental thresholds and those obtained by MC simulations, a maximum difference of about 4% was found, within the errors (±2% and ±5%, for volumes ≥5 ml or