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

Pacilio, Massimiliano; Basile, Chiara; Shcherbinin, Sergey; Caselli, Federica; Ventroni, Guido; Aragno, D.; Mango, Lucio; Santini, Enrico

doi:10.1118/1.3590359

Cited by 18 publications

(22 citation statements)

References 48 publications

(55 reference statements)

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“…Organ delineation can be always performed with coregistered CT, but tumor delineation could be more challenging, as CT images do not provide adequate information in all cases, so techniques for accurate tumor delineation on PET or SPECT images should be implemented. [65][66][67] …”

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confidence: 99%

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

et al. 2016

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Purpose: Many centers aim to plan liver transarterial radioembolization (TARE) with dosimetry, even without CT-based attenuation correction (AC), or with unoptimized scatter correction (SC) methods. This work investigates the impact of presence vs absence of such corrections, and limited spatial resolution, on 3D dosimetry for TARE. Methods: Three voxelized phantoms were derived from CT images of real patients with different body sizes. Simulations of 99m Tc-SPECT projections were performed with the SIMIND code, assuming three activity distributions in the liver: uniform, inside a "liver's segment," or distributing multiple uptaking nodules ("nonuniform liver"), with a tumoral liver/healthy parenchyma ratio of 5:1. Projection data were reconstructed by a commercial workstation, with OSEM protocol not specifically optimized for dosimetry (spatial resolution of 12.6 mm), with/without SC (optimized, or with parameters predefined by the manufacturer; dual energy window), and with/without AC. Activity in voxels was calculated by a relative calibration, assuming identical microspheres and 99m Tc-SPECT counts spatial distribution. 3D dose distributions were calculated by convolution with lesions and healthy parenchyma from different reconstructions were compared with those obtained from the reference biodistribution (the "gold standard," GS), assessing differences for D95%, D70%, and D50% (i.e., minimum value of the absorbed dose to a percentage of the irradiated volume). γ tool analysis with tolerance of 3%/13 mm was used to evaluate the agreement between GS and simulated cases. The influence of deep-breathing was studied, blurring the reference biodistributions with a 3D anisotropic gaussian kernel, and performing the simulations once again. Results: Differences of the dosimetric indicators were noticeable in some cases, always negative for lesions and distributed around zero for parenchyma. Application of AC and SC reduced systematically the differences for lesions by 5%-14% for a liver segment, and by 7%-12% for a nonuniform liver. For parenchyma, the data trend was less clear, but the overall range of variability passed from −10%/40% for a liver segment, and −10%/20% for a nonuniform liver, to −13%/6% in both cases. Applying AC, SC with preset parameters gave similar results to optimized SC, as confirmed by γ tool analysis. Moreover, γ analysis confirmed that solely AC and SC are not sufficient to obtain accurate 3D dose distribution. With breathing, the accuracy worsened severely for all dosimetric indicators, above all for lesions: with AC and optimized SC, −38%/−13% in liver's segment, −61%/−40% in the nonuniform liver. For parenchyma, D50% resulted always less sensitive to breathing and sub-optimal correction methods (difference overall range: −7%/13%). Conclusions: Reconstruction protocol optimization, AC, SC, PVE and respiratory motion corrections should be implemented to obtain the best possible dosimetric accuracy. On the other side, thanks to the relative calibration, D50% inaccuracy for the healthy paren...

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confidence: 99%

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

et al. 2016

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“…The present study shows a new strategy for automatic segmentation on PET images by using adaptive thresholding techniques 12 , 16 . For more precision, this strategy consists of adjusting threshold functions directly from the information extracted from the patient's body, rather than from phantoms.…”

Section: Discussionmentioning

confidence: 99%

“…Among these segmentation methods, adaptive thresholding techniques 12 , 16 characterize each image by specific parameters such as background, maximum intensity of grayscale pixels, and size of lesions 9 , 17 . After adjustment, a mathematical “threshold adjustment function” will give a threshold value for each image corresponding to these specific parameters.…”

Section: Introductionmentioning

confidence: 99%

New strategy for automatic tumor segmentation by adaptive thresholding on PET/CT images

Moussallem

Valette

Traverse-Gléhen

et al. 2012

J Applied Clin Med Phys

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Tumor delineation is a critical aspect in radiotherapy treatment planning and is usually performed with the anatomical images of a computed tomography (CT) scan. For non‐small cell lung cancer, it has been recommended to use functional positron emission tomography (PET) images to take into account the biological target characteristics. However, today, there is no satisfactory segmentation technique for PET images in clinical applications. In the present study, a solution to this problem is proposed. The development of the segmentation technique is based on the threshold's adjustment directly from patients, rather than from phantoms. To this end, two references were chosen: measurements performed on CT images of the selected lesions, and histological measurements of surgically removed tumors. The inclusion and exclusion criteria were chosen to produce references that are assumed to have measured tumor sizes equal to the true in vivo tumor sizes. In total, for the two references, 65 lung lesions of 54 patients referred for FDG‐PET/CT exams were selected. For validation, measurements of segmented lesions on PET images using this technique were also compared to CT and histological measurements. For lesions greater than 20 mm, our segmentation technique showed a good estimation of histological measurements (mean difference between measured and calculated data equal to −0.8±9.0%) and an acceptable estimation of CT measurements. For lesions smaller than or equal to 20 mm, the method showed disagreement with the measurements derived from histological or CT data. This novel segmentation technique shows high accuracy for the lesions with largest axes between 2 and 4.5 cm. However, it does not correctly evaluate smaller lesions, likely due to the partial volume effect and/or respiratory motions.PACS numbers: 87.53.Bn, 87.53.Kn, 87.55.D, 87.57.nm, 87.57.U

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“…[22][23][24] In this study, adaptive segmentation thresholding curves were applied for target volume identification in three conditions of signal-to-background activity ratios.…”

Section: Introductionmentioning

confidence: 99%

⁹⁰Y-PET/CT Imaging Quantification for Dosimetry in Peptide Receptor Radionuclide Therapy: Analysis and Corrections of the Impairing Factors

FabbriCinzia¹,

BartolomeiMirco²,

MattoneVincenzo³

et al. 2015

Cancer Biotherapy and Radiopharmaceuticals

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

Cited by 18 publications

References 48 publications

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

New strategy for automatic tumor segmentation by adaptive thresholding on PET/CT images

⁹⁰Y-PET/CT Imaging Quantification for Dosimetry in Peptide Receptor Radionuclide Therapy: Analysis and Corrections of the Impairing Factors

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

Cited by 18 publications

References 48 publications

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

New strategy for automatic tumor segmentation by adaptive thresholding on PET/CT images

90Y-PET/CT Imaging Quantification for Dosimetry in Peptide Receptor Radionuclide Therapy: Analysis and Corrections of the Impairing Factors

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⁹⁰Y-PET/CT Imaging Quantification for Dosimetry in Peptide Receptor Radionuclide Therapy: Analysis and Corrections of the Impairing Factors