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Title: TU-F-12A-02: Quantitative Characterization of Normal Bone Marrow Proliferative Activity with FLT PET/CT

Abstract

Purpose: [F-18]FLT PET is a tool for assessing health of bone marrow by evaluating its proliferative activity. This study establishes a baseline quantitative characterization of healthy marrow proliferation to aid in diagnosis of hematological disease. Methods: 31 patients (20 male, 11 female, 41–76 years) being treated for solid cancers with no history of hematological disease, osseous metastatic disease, or radiation therapy received pre-treatment FLT PET/CT scans. Total bone marrow was isolated from whole body FLT PET images by manually removing organs and applying a standardize uptake value (SUV) threshold of 1.0. Because adult marrow is concentrated in the axial skeleton, quantitative total bone marrow analysis (QTBMA) was used to isolate marrow in the lumbar spine, thoracic spine, sacrum, and pelvis for analysis. SUV mean, SUV max, and SUV CV were used to quantify bone marrow proliferation. Correlations were explored between SUV and patient characteristics including age, weight, height, and BMI using the Spearman coefficient (ρ). Results: The population-averaged whole-skeleton SUV mean, SUV max, and SUV CV were 3.0±0.6, 18.4±5.7, and 0.6±0.1, respectively. Uptake values in the axial skeleton were similar to the whole-skeleton demonstrated by SUV mean in the thoracic spine (3.6±0.6), lumbar spine (3.3±0.5), sacrum (3.0±0.6), and pelvis regionsmore » (2.8±0.5). Whole-skeleton SUV max correlated with patient weight (ρ=0.47, p<0.01) and BMI (ρ=0.60, p<0.01), suggesting marrow activity is related to the body's burden. SUV measures in the thoracic spine, lumbar spine, sacrum, and pelvis were negatively correlated with age (ρ:−0.41 to −0.46, p≤0.02). These negative correlations reflect the fact that active marrow in the adult skeleton is localized in the axial skeleton and decreases with age. Conclusions: Normal bone marrow characterizations were determined using FLT PET. These results provide a baseline characterization against which proliferative activity of abnormal marrow can be compared.« less

Authors:
;  [1]
  1. Department of Medical Physics, University of Wisconsin, Madison, WI (United States)
Publication Date:
OSTI Identifier:
22407848
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 41; Journal Issue: 6; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; ADULTS; BONE MARROW; CAT SCANNING; CELL PROLIFERATION; DIAGNOSIS; FLUORINE 18; METASTASES; NEOPLASMS; PATIENTS; PELVIS; RADIOTHERAPY; UPTAKE; VERTEBRAE

Citation Formats

Weisse, N, and Jeraj, R. TU-F-12A-02: Quantitative Characterization of Normal Bone Marrow Proliferative Activity with FLT PET/CT. United States: N. p., 2014. Web. doi:10.1118/1.4889357.
Weisse, N, & Jeraj, R. TU-F-12A-02: Quantitative Characterization of Normal Bone Marrow Proliferative Activity with FLT PET/CT. United States. doi:10.1118/1.4889357.
Weisse, N, and Jeraj, R. Sun . "TU-F-12A-02: Quantitative Characterization of Normal Bone Marrow Proliferative Activity with FLT PET/CT". United States. doi:10.1118/1.4889357.
@article{osti_22407848,
title = {TU-F-12A-02: Quantitative Characterization of Normal Bone Marrow Proliferative Activity with FLT PET/CT},
author = {Weisse, N and Jeraj, R},
abstractNote = {Purpose: [F-18]FLT PET is a tool for assessing health of bone marrow by evaluating its proliferative activity. This study establishes a baseline quantitative characterization of healthy marrow proliferation to aid in diagnosis of hematological disease. Methods: 31 patients (20 male, 11 female, 41–76 years) being treated for solid cancers with no history of hematological disease, osseous metastatic disease, or radiation therapy received pre-treatment FLT PET/CT scans. Total bone marrow was isolated from whole body FLT PET images by manually removing organs and applying a standardize uptake value (SUV) threshold of 1.0. Because adult marrow is concentrated in the axial skeleton, quantitative total bone marrow analysis (QTBMA) was used to isolate marrow in the lumbar spine, thoracic spine, sacrum, and pelvis for analysis. SUVmean, SUVmax, and SUVCV were used to quantify bone marrow proliferation. Correlations were explored between SUV and patient characteristics including age, weight, height, and BMI using the Spearman coefficient (ρ). Results: The population-averaged whole-skeleton SUVmean, SUVmax, and SUVCV were 3.0±0.6, 18.4±5.7, and 0.6±0.1, respectively. Uptake values in the axial skeleton were similar to the whole-skeleton demonstrated by SUVmean in the thoracic spine (3.6±0.6), lumbar spine (3.3±0.5), sacrum (3.0±0.6), and pelvis regions (2.8±0.5). Whole-skeleton SUVmax correlated with patient weight (ρ=0.47, p<0.01) and BMI (ρ=0.60, p<0.01), suggesting marrow activity is related to the body's burden. SUV measures in the thoracic spine, lumbar spine, sacrum, and pelvis were negatively correlated with age (ρ:−0.41 to −0.46, p≤0.02). These negative correlations reflect the fact that active marrow in the adult skeleton is localized in the axial skeleton and decreases with age. Conclusions: Normal bone marrow characterizations were determined using FLT PET. These results provide a baseline characterization against which proliferative activity of abnormal marrow can be compared.},
doi = {10.1118/1.4889357},
journal = {Medical Physics},
number = 6,
volume = 41,
place = {United States},
year = {Sun Jun 15 00:00:00 EDT 2014},
month = {Sun Jun 15 00:00:00 EDT 2014}
}
  • Purpose: Studies have shown cessation of anti-angiogenic treatment during the first cycle of therapy resulted in rebound of tumor proliferation (flare). This study characterized proliferation dynamics during the first and third cycle of anti-angiogenic treatment using [F-18]FLT PET. Methods: Thirteen patients with various solid cancers were treated with Axitinib (Pfizer, Inc) at a dose of 5mg orally, twice daily, on contiguous three-week cycles with intermittent dosing (two-weeks-on/one-week-off). All patients received three FLT PET/CT scans during cycle 1 (C1): at baseline (C1D0), peak Axitinib concentration (C1D14), and the end of washout (C1D21). Ten patients received up to an additional three scansmore » at corresponding time points during cycle 3 (C3). Lesions were identified by a nuclear medicine physician and manually contoured. Tumor burden was quantified using standard SUV metrics. Correlations between imaging metrics across C1 and C3 were calculated using the Spearman correlation. Results: At C1 peak drug concentration 11/13 patients had decreases in SUVtotal, with median decrease of 50% (change from C1D0 to C1D14). At C3 peak drug concentration 7/7 patients had decreases in SUVtotal, with median decrease of 20% (C3D0 to C3D14). Proliferative flare during C1 washout (>20% increase from C1D14 to C1D21) occurred in 9/13 patients, with median SUVtotal increase of 190%. Flare was also seen in C3 for 5/5 patients, with median SUVtotal increase of 70% (change from C3D14 to C3D21). Correlations were found between changes in imaging metrics across C1 and C3, notably the change in SUVtotal from C1D0 to C1D21 and the change in SUVtotal from C1D0 to C3D0 (ρ = 0.80). Conclusion: Measurements of SUVtotal showed that both patient response to treatment and flare were evident in both cycles of treatment. Correlation between changes in SUVtotal across C1 and C3 suggest early time points could be used to characterize patient response in later cycles. Research funded in part by Pfizer.« less
  • Purpose: The purpose of this study was to compare a radiation therapy treatment planning that would spare active bone marrow and whole pelvic bone marrow using 18F FLT PET/CT image. Methods: We have developed an IMRT planning methodology to incorporate functional PET imaging using 18F FLT/CT scans. Plans were generated for two cervical cancer patients, where pelvicactive bone marrow region was incorporated as avoidance regions based on the range: SUV>2., another region was whole pelvic bone marrow. Dose objectives were set to reduce the volume of active bone marrow and whole bone marraw. The volumes of received 10 (V10) andmore » 20 (V20) Gy for active bone marrow were evaluated. Results: Active bone marrow regions identified by 18F FLT with an SUV>2 represented an average of 48.0% of the total osseous pelvis for the two cases studied. Improved dose volume histograms for identified bone marrow SUV volumes and decreases in V10(average 18%), and V20(average 14%) were achieved without clinically significant changes to PTV or OAR doses. Conclusion: Incorporation of 18F FLT/CT PET in IMRT planning provides a methodology to reduce radiation dose to active bone marrow without compromising PTV or OAR dose objectives in cervical cancer.« less
  • Purpose: Proliferating bone marrow is exquisitely sensitive to ionizing radiation. Knowledge of its distribution could improve radiation therapy planning to minimize unnecessary marrow exposure and avoid consequential prolonged myelosuppression. [18F]-Fluoro-3-deoxy-3-L-fluorothymidine (FLT)–positron emission tomography (PET) is a novel imaging modality that provides detailed quantitative images of proliferating tissues, including bone marrow. We used FLT-PET imaging in cancer patients to produce an atlas of marrow distribution with potential clinical utility. Methods and Materials: The FLT-PET and fused CT scans of eligible patients with non-small cell lung cancer (no distant metastases, no prior cytotoxic exposure, no hematologic disorders) were reviewed. The proportions of skeletalmore » FLT activity in 10 predefined bony regions were determined and compared according to age, sex, and recent smoking status. Results: Fifty-one patients were studied: 67% male; median age 68 (range, 31-87) years; 8% never smokers; 70% no smoking in the preceding 3 months. Significant differences in marrow distribution occurred between sex and age groups. No effect was detected from smoking in the preceding 3 months. Using the mean percentages of FLT uptake per body region, we created an atlas of the distribution of functional bone marrow in 4 subgroups defined by sex and age. Conclusions: This atlas has potential utility for estimating the distribution of active marrow in adult cancer patients to guide radiation therapy planning. However, because of interindividual variation it should be used with caution when radiation therapy risks ablating large proportions of active marrow; in such cases, individual FLT-PET scans may be required.« less
  • Purpose: [F-18]NaF PET can be used to image bone metastases; however, tracer uptake in degenerative joint disease (DJD) often appears similar to metastases. This study aims to develop and compare different machine learning algorithms to automatically identify regions of [F-18]NaF scans that correspond to DJD. Methods: 10 metastatic prostate cancer patients received whole body [F-18]NaF PET/CT scans prior to treatment. Image segmentation resulted in 852 ROIs, 69 of which were identified by a nuclear medicine physician as DJD. For all ROIs, various PET and CT textural features were computed. ROIs were divided into training and testing sets used to trainmore » eight different machine learning classifiers. Classifiers were evaluated based on receiver operating characteristics area under the curve (AUC), sensitivity, specificity, and positive predictive value (PPV). We also assessed the added value of including CT features in addition to PET features for training classifiers. Results: The training set consisted of 37 DJD ROIs with 475 non-DJD ROIs, and the testing set consisted of 32 DJD ROIs with 308 non-DJD ROIs. Of all classifiers, generalized linear models (GLM), decision forests (DF), and support vector machines (SVM) had the best performance. AUCs of GLM (0.929), DF (0.921), and SVM (0.889) were significantly higher than the other models (p<0.001). GLM and DF, overall, had the best sensitivity, specificity, and PPV, and gave a significantly better performance (p<0.01) than all other models. PET/CT GLM classifiers had higher AUC than just PET or just CT. GLMs built using PET/CT information had superior or comparable sensitivities, specificities and PPVs to just PET or just CT. Conclusion: Machine learning algorithms trained with PET/CT features were able to identify some cases of DJD. GLM outperformed the other classification algorithms. Using PET and CT information together was shown to be superior to using PET or CT features alone. Research supported by the Prostate Cancer Foundation.« less
  • Purpose: To develop predictive models using quantitative PET/CT features for the evaluation of tumor response to neoadjuvant chemo-radiotherapy (CRT) in patients with locally advanced esophageal cancer. Methods: This study included 20 patients who underwent tri-modality therapy (CRT + surgery) and had {sup 18}F-FDG PET/CT scans before initiation of CRT and 4-6 weeks after completion of CRT but prior to surgery. Four groups of tumor features were examined: (1) conventional PET/CT response measures (SUVmax, tumor diameter, etc.); (2) clinical parameters (TNM stage, histology, etc.) and demographics; (3) spatial-temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associatedmore » changes resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross-validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, using cross-validations to avoid model over-fitting. Prediction accuracy was assessed via area under the receiver operating characteristic curve (AUC), and precision was evaluated via confidence intervals (CIs) of AUC. Results: When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). Using spatial-temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications), significantly better than using conventional PET/CT measures or clinical parameters and demographics alone. For groups with a large number of tumor features (groups 3 and 4), the SVM model achieved significantly higher accuracy than the LR model. Conclusion: The SVM model using all features including quantitative PET/CT features accurately and precisely predicted pathologic tumor response to CRT in esophageal cancer. This work was supported in part by National Cancer Institute Grant R21 CA131979 and R01 CA172638. Shan Tan was supported in part by the National Natural Science Foundation of China 60971112 and 61375018, and by Fundamental Research Funds for the Central Universities 2012QN086.« less