A novel tool for improving the interpretation of isotope bone scans in metastatic prostate cancer

Abstract

Objectives: The isotope bone scan (IBS) is the gold-standard imaging modality for detecting skeletal metastases as part of prostate cancer staging. However, its clinical utility for assessing skeletal metastatic burden is limited due to the need for subjective interpretation. We designed and tested a novel custom software tool, the Metastatic Bone Scan Tool (MetsBST), aimed at improving interpretation of IBSs, and compared its performance with that of an established software programme. Methods: We used IBS images from 62 patients diagnosed with prostate cancer and suspected bone metastases to design and implement MetsBST in MATLAB by defining thresholds used to identify the texture and size of metastatic bone lesions. The results of MetsBST were compared with those of the commercially available automated Bone Scan Index (aBSI) with regression analysis. Results: There was strong agreement between the MetsBST and aBSI results (R2 = 0.9189). In a subregional analysis, MetsBST quantified the extent of metastatic disease in multiple bone sites in patients receiving multimodality therapy (radium-223 and external beam radiotherapy) to illustrate the differences in bone metastatic response to different treatments. Conclusion: The results of MetsBST and the commercial software aBSI were highly consistent. MetsBST introduces novel clinical utility by its ability to differentiate between the responses of different bone metastases to multimodality therapies. Advances in knowledge: MetsBST reduces the variability in assessment of tumour burden caused by subjective interpretation. Therefore, it is a useful aid to physicians reporting nuclear medicine scans, and may improve decision-making in the treatment of metastatic prostate cancer.

Radiomics in prostate cancer: an up-to-date review

“…MRI and PSMA-PET will be the focus of research for the future after standardizing the RF. 18 FDC FPyL, 18 F-fluorodeoxyglucose; 177 LU-PSMA, 177 Lutentium-prostate-specific membrane antigen; ADC, apparent diffusion coefficient; AE, adverse events; AS, active surveillance; DWI, diffusion-weighted imaging; EORTC, European Organization for Research and Treatment of Cancer; FUS-BG, fusion ultrasound-guided biopsies; mpMRI, multi-parametric magnetic resonance imaging; MRI, magnetic resonance imaging; PSA, prostate-specific antigen; PSMA-PET, prostate-specific membrane antigen positron emission tomography; RF, radiomic features; TRUS-BG, transrectal ultrasound-guided biopsies.…”

“…The generalizability and implementation of this classifiers could represent a breakthrough in using automated algorithms, but this can be limited by the use of simple statistical correlation analysis, like Waikato Environment for Knowledge Analysis (WEKA 3) 176 and neural network algorithms, like Matlab. 177 , 178 The R collection of algorithms 179 is easy to use for automatic tuning of features and it is available for researchers that are just familiarized with the methodology of statistics. All classifiers in a family have strong differences between data sets and the mean accuracy can have a limited significance if the data sets used are at low volume.…”

Diagnostic software proposal for bone scan follow-up using false color based on the gammagrams analysis from gray tone histograms

“…However, it is a fast alternative, with the additional feature of introducing color in the results to increase the diagnostic sensitivity of early-stage metastatic disease. There are in the literature several examples of CAD tools using machine learning, AI or neural networks (Aslantas et al 2016b, Yin et al 2004, Nakajima et al 2013c, Alshehri et al 2020aand Isaac et al 2020b yet considering the high bit depths, which are not fully exploited. Also, the human eye limitations should be considered, being capable of resolving only 32 gray tones in the interval [25-256] (Bourne et al 2010), which depends on the study and analyzed tones scale.…”