Bone texture analysis using CT-simulation scans to individuate risk parameters for radiation-induced insufficiency fractures

Nardone, Valerio; Tini, Paolo; Carbone, Salvatore Francesco; Grassi, A.; Biondi, M.; Sebaste, Lucio; Carfagno, Tommaso; Vanzi, E.; Otto, G. De; Battaglia, Giuseppe; Rubino, Giovanni; Pastina, Pierpaolo; Belmonte, Giuseppe; Mazzoni, Lorenzo Nicola; Buonamici, F. Banci; Mazzei, Maria Antonietta; Pirtoli, Luigi

doi:10.1007/s00198-017-3968-5

Cited by 20 publications

(15 citation statements)

References 38 publications

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“…This parameter is inversely correlated to the entropy, in accordance with previous works (28,33,34). This might be explained by the fibers being more marked in the control group, with an increase in the randomness of the pixel values, and eventually an increase in the entropy and a decrease in energy.…”

Section: Discussionsupporting

confidence: 90%

“…At this regard, the major novelties of this paper, in comparison to our previous work (28), are the 3D TA, the automatic contouring of the ROI and the higher number of texture parameters analysed.…”

Section: Discussionmentioning

confidence: 98%

“…We have previously studied (28,29) the role of bone TA, with an in-house 2D software, and we have decided to explore the potential role of 3D Bone TA. Moreover, we tested the possibility of automatically obtain 3D ROI with the treatment planning contouring workstation (Raystation © ).…”

Section: Discussionmentioning

confidence: 99%

“…We have previously studied the efficacy of bone TA, using a home-made ImageJ macro and selecting only two 2D ROI (the vertebral body of L5 and the femoral head) in a case-control study (28,29).…”

Section: Respectively the Risk Factors For Rt-induced Ifs That Havementioning

confidence: 99%

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3D bone texture analysis as a potential predictor of radiation-induced insufficiency fractures

Nardone¹,

Tini²,

Croci³

et al. 2018

Quant. Imaging Med. Surg.

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Background: The aim of our work is to assess the potential role of texture analysis (TA), applied to computed tomography (CT) simulation scans, in relation to the development of insufficiency fractures (IFs) in patients undergoing radiation therapy (RT) for pelvic malignancies. Methods:We analyzed patients undergoing pelvic RT from Jan-2010 to Dec-2016, 31 of whom had developed IFs of the pelvis. We analyzed CT simulation scans using LifeX Software © , and in particular we selected three regions of interest (ROI): L5 body, the sacrum and both the femoral heads. The ROI were automatically contoured using the treatment planning software Raystation © . TA parameters included parameters from the gray-level histogram, indices from sphericity and from the matrix of GLCM (gray level co-occurrence matrix). The IFs patients were matched (1:1 ratio) with control patients who had not developed IFs, and were matched for age, sex, type of tumor, menopausal status, RT dose and use of chemotherapy. Univariate and multivariate analyses (logistic regression) were used for statistical analysis.Results: Significant TA parameters on univariate analysis included both parameters from the histogram distribution, as well from the matrix of GLCM. On logistic regression analysis the significant parameters Conclusions: In our experience, 3D-bone CT TA can be used to stratify the risk of the patients to develop radiation-induced IFs. A prospective study will be conducted to validate these findings.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Respectively the Risk Factors For Rt-induced Ifs That Havementioning

confidence: 99%

See 2 more Smart Citations

3D bone texture analysis as a potential predictor of radiation-induced insufficiency fractures

Nardone¹,

Tini²,

Croci³

et al. 2018

Quant. Imaging Med. Surg.

View full text Add to dashboard Cite

show abstract

“…In addition to DXA, several other approaches are developed for BMD assessment. These methods are including quantitative computed tomography (QCT), peripheral DXA (pDXA), quantitative ultrasound (QUS) and magnetic resonance imaging (MRI) (3)(4)(5). Recently, quantitative radiomics texture analysis studies have been applied for a wide range of clinical applications such as diseases detection, diagnosis, prognosis and prediction (6)(7)(8).…”

Section: Introductionmentioning

confidence: 99%

Test–Retest Reproducibility Analysis of Bone Mineral Densitometry Radiomics Features

Qasempour

Akhash

Shiri³

et al. 2020

Preprint

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Background Radiomics features reproducibility assessment is a critical issue in imaging biomarker development era. In the present study, we aimed to assess test–retest reproducibility analysis of bone mineral densitometry (BMD) image radiomics features. Methods In this prospective research work, eighteen patients were included and were subjected to DXA BMD scans acquired within 10 min of each other under an approved protocol. Seven regions of interest (ROIs) including four lumbar spine regions (L1-L4) and three hip regions (trochanteric, inter trochanteric and neck) in both test and re-test images were segmented and 107 radiomics features from seven different feature sets were extracted. Intra-class correlation coefficient (ICC) were initially used to estimate radiomics features reproducibility. Results We showed that there is no radiomics feature with 90% < ICC < 100% in all ROIs, but there are three feature including Strength (from NGTDM feature set), SALGLE (Small Area Low Gray Level Emphasis) (from GLSZM feature set) and Busyness (from NGTDM feature set) with ICC < 70% in all eight ROIs. Shape features has features with ICC < 70%. Conclusion Our study on test–retest reproducibility analysis of bone mineral densitometry radiomics features shows radiomics features have several variations against changes of time of image acquisition. The reproducible features may be used as imaging biomarkers in the field of clinical densitometry. The results of this study may be repeated by more radiomics features and more BMD scanners as first line for bone mineral biomarker discovery.

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Automatic segmentation and radiomic texture analysis for osteoporosis screening using chest low-dose computed tomography

Chen

Kuo

et al. 2023

Eur Radiol

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Bone texture analysis using CT-simulation scans to individuate risk parameters for radiation-induced insufficiency fractures

Abstract: In our experience, bone CT TA could be correlated to the risk of radiation-induced IFs. Studies on a large patient series and methodological refinements are warranted.

Cited by 20 publications

References 38 publications

3D bone texture analysis as a potential predictor of radiation-induced insufficiency fractures

3D bone texture analysis as a potential predictor of radiation-induced insufficiency fractures

Test–Retest Reproducibility Analysis of Bone Mineral Densitometry Radiomics Features

Automatic segmentation and radiomic texture analysis for osteoporosis screening using chest low-dose computed tomography

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