A Preanalytic Validation Study of Automated Bone Scan Index: Effect on Accuracy and Reproducibility Due to the Procedural Variabilities in Bone Scan Image Acquisition

Abstract

The effect of the procedural variability in image acquisition on the quantitative assessment of bone scan is unknown. Here, we have developed and performed preanalytical studies to assess the impact of the variability in scanning speed and in vendor-specific γ-camera on reproducibility and accuracy of the automated bone scan index (BSI). Methods: Two separate preanalytical studies were performed: a patient study and a simulation study. In the patient study, to evaluate the effect on BSI reproducibility, repeated bone scans were prospectively obtained from metastatic prostate cancer patients enrolled in 3 groups (Grp). In Grp1, the repeated scan speed and the γ-camera vendor were the same as that of the original scan. In Grp2, the repeated scan was twice the speed of the original scan. In Grp3, the repeated scan used a different γ-camera vendor than that used in the original scan. In the simulation study, to evaluate the effect on BSI accuracy, bone scans of a virtual phantom with predefined skeletal tumor burden (phantom-BSI) were simulated against the range of image counts (0.2, 0.5, 1.0, and 1.5 million) and separately against the resolution settings of the γ-cameras. The automated BSI was measured with a computer-automated platform. Reproducibility was measured as the absolute difference between the repeated BSI values, and accuracy was measured as the absolute difference between the observed BSI and the phantom-BSI values. Descriptive statistics were used to compare the generated data. Results: In the patient study, 75 patients, 25 in each group, were enrolled. The reproducibility of Grp2 (mean ± SD, 0.35 ± 0.59) was observed to be significantly lower than that of Grp1 (mean ± SD, 0.10 ± 0.13; P , 0.0001) and that of Grp3 (mean ± SD, 0.09 ± 0.10; P , 0.0001). However, no significant difference was observed between the reproducibility of Grp3 and Grp1 (P 5 0.388). In the simulation study, the accuracy at 0.5 million counts (mean ± SD, 0.57 ± 0.38) and at 0.2 million counts (mean ± SD, 4.67 ± 0.85) was significantly lower than that observed at 1.5 million counts (mean ± SD, 0.20 ± 0.26; P , 0.0001). No significant difference was observed in the accuracy data of the simulation study with vendor-specific γ-cameras (P 5 0.266). Conclusion: In this study, we observed that the automated BSI accuracy and reproducibility were dependent on scanning speed but not on the vendor-specific γ-cameras. Prospective BSI studies should standardize scanning speed of bone scans to obtain image counts at or above 1.5 million. Mor e than 80% of metastatic prostate cancer patients have skeletal metastasis (1). In clinical routine, bone scan is the most common imaging modality to monitor bone metastasis. In therapeutic clinical trials, bone scan is the standard imaging modality to assess eligibility and progression for patients with metastatic prostate cancer. However, the clinical utility of bone scan is limited due to its subjective assessment, which is susceptible to the interobserver variability, and in its inability to assess re...

Denoising of Scintillation Camera Images Using a Deep Convolutional Neural Network: A Monte Carlo Simulation Approach

“…It is believed that machine learning will change radiology and nuclear medicine in the future (5). There have been recent publications on the use of machine learning algorithms for classification and segmentation purposes (6)(7)(8)(9)(10). CNNs have been used to obtain standard-dose CT and PET images from low-dose data (11,12) and to enhance images by determining scatter correction parameters (13) and CNN-augmented emission-based attenuation correction (14) in PET.…”

Bone scan index: A new biomarker of bone metastasis in patients with prostate cancer

“…The effect of variability in image acquisition on the BSI calculation was analyzed during the pre-analytical validation. 30 The results showed that the BSI is dependent on the quality of anterior and posterior images defined as counts, but not on vendor-specific gamma cameras. It is therefore recommended that the scan speed be adjusted to ensure that the total count is ≥1.5 million per image; that is, to adhere to the guidelines of the Society of Nuclear Medicine and Molecular Imaging.…”

“…The effect of variability in image acquisition on the BSI calculation was analyzed during the pre‐analytical validation . The results showed that the BSI is dependent on the quality of anterior and posterior images defined as counts, but not on vendor‐specific gamma cameras.…”

Automated Bone Scan Index as an Imaging Biomarker to Predict Overall Survival in the Zometa European Study/SPCG11

“…Automated Bone Scan Index (aBSI) is suggested to act as an imaging biomarker of whole-body bone-metastatic burden, and it represents the percentage of the total skeletal mass affected by metastases [4,5]. The aBSI is software developed using artificial intelligence for calculation from images acquired in whole-body bone scintigraphy within a few seconds, and it has been validated preanalytically and analytically as an imaging biomarker in patients with metastatic PCa [6,7].…”