Comparing the blood oxygen level–dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imaging

PurposeThe aim of this study is to compare the blood oxygen level–dependent (BOLD) fluctuation power in 96 frequency points ranging from 0 to 0.25 Hz between benign and malignant musculoskeletal (MSK) tumors via power spectrum analyses using functional magnetic resonance imaging (fMRI).Materials and...

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Main Authors: Lisha Duan, Huiyuan Huang, Feng Sun, Zhenjiang Zhao, Mengjun Wang, Mei Xing, Yufeng Zang, Xiaofei Xiu, Meng Wang, Hong Yu, Jianling Cui, Han Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-08-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.794555/full
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author Lisha Duan
Lisha Duan
Huiyuan Huang
Huiyuan Huang
Feng Sun
Feng Sun
Zhenjiang Zhao
Zhenjiang Zhao
Mengjun Wang
Mengjun Wang
Mei Xing
Mei Xing
Yufeng Zang
Yufeng Zang
Xiaofei Xiu
Meng Wang
Hong Yu
Jianling Cui
Jianling Cui
Han Zhang
Han Zhang
author_facet Lisha Duan
Lisha Duan
Huiyuan Huang
Huiyuan Huang
Feng Sun
Feng Sun
Zhenjiang Zhao
Zhenjiang Zhao
Mengjun Wang
Mengjun Wang
Mei Xing
Mei Xing
Yufeng Zang
Yufeng Zang
Xiaofei Xiu
Meng Wang
Hong Yu
Jianling Cui
Jianling Cui
Han Zhang
Han Zhang
author_sort Lisha Duan
collection DOAJ
description PurposeThe aim of this study is to compare the blood oxygen level–dependent (BOLD) fluctuation power in 96 frequency points ranging from 0 to 0.25 Hz between benign and malignant musculoskeletal (MSK) tumors via power spectrum analyses using functional magnetic resonance imaging (fMRI).Materials and methodsBOLD-fMRI and T1-weighted imaging (T1WI) of 92 patients with benign or malignant MSK tumors were acquired by 1.5-T magnetic resonance scanner. For each patient, the tumor-related BOLD time series were extracted, and then, the power spectrum of BOLD time series was calculated and was then divided into 96 frequency points. A two-sample t-test was used to assess whether there was a significant difference in the powers (the “power” is the square of the BOLD fluctuation amplitude with arbitrary unit) of each frequency point between benign and malignant MSK tumors. The receiver operator characteristic (ROC) analysis was used to assess the diagnostic capability of distinguishing between benign and malignant MSK tumors.ResultsThe result of the two-sample t-test showed that there was significant difference in the power between benign and malignant MSK tumor at frequency points of 58 (0.1508 Hz, P = 0.036), 59 (0.1534 Hz, P = 0.032), and 95 (0.247 Hz, P = 0.014), respectively. The ROC analysis of mean power of three frequency points showed that the area of under curve is 0.706 (P = 0.009), and the cutoff value is 0.73130. If the power of the tumor greater than or equal to 0.73130 is considered the possibility of benign tumor, then the diagnostic sensitivity and specificity values are 83% and 59%, respectively. The post hoc analysis showed that the merged power of 0.1508 and 0.1534 Hz in benign MSK tumors was significantly higher than that in malignant ones (P = 0.014). The ROC analysis showed that, if the benign MSK tumor was diagnosed with the power greater than or equal to the cutoff value of 1.41241, then the sensitivity and specificity were 67% and 68%, respectively.ConclusionThe mean power of three frequency points at 0.1508, 0.1534, and 0.247 Hz may potentially be a biomarker to differentiate benign from malignant MSK tumors. By combining the power of 0.1508 and 0.1534 Hz, we could better detect the difference between benign and malignant MSK tumors with higher specificity.
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spelling doaj.art-4783fa9f1c7f4e88afde9af92295e9472022-12-22T04:01:18ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-08-011210.3389/fonc.2022.794555794555Comparing the blood oxygen level–dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imagingLisha Duan0Lisha Duan1Huiyuan Huang2Huiyuan Huang3Feng Sun4Feng Sun5Zhenjiang Zhao6Zhenjiang Zhao7Mengjun Wang8Mengjun Wang9Mei Xing10Mei Xing11Yufeng Zang12Yufeng Zang13Xiaofei Xiu14Meng Wang15Hong Yu16Jianling Cui17Jianling Cui18Han Zhang19Han Zhang20Department of Radiology, the Third Hospital of Hebei Medical University, Shijiazhuang, ChinaKey Laboratory of Biomechanics of Hebei Province, Shijiazhuang, ChinaCenter for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, ChinaSchool of Public Health and Management, Guangzhou University of Chinese Medicine, Guangzhou, ChinaDepartment of Radiology, the Third Hospital of Hebei Medical University, Shijiazhuang, ChinaKey Laboratory of Biomechanics of Hebei Province, Shijiazhuang, ChinaDepartment of Radiology, the Third Hospital of Hebei Medical University, Shijiazhuang, ChinaKey Laboratory of Biomechanics of Hebei Province, Shijiazhuang, ChinaDepartment of Radiology, the Third Hospital of Hebei Medical University, Shijiazhuang, ChinaKey Laboratory of Biomechanics of Hebei Province, Shijiazhuang, ChinaDepartment of Radiology, the Third Hospital of Hebei Medical University, Shijiazhuang, ChinaKey Laboratory of Biomechanics of Hebei Province, Shijiazhuang, ChinaCenter for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, ChinaZhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, ChinaDepartment of Pathology, The Third Hospital of Hebei Medical University, Shijiazhuang, ChinaDepartment of Radiology, the First Hospital of Hebei Medical University, Shijiazhuang, ChinaDepartment of Radiology, the Third Hospital of Hebei Medical University, Shijiazhuang, ChinaDepartment of Radiology, the Third Hospital of Hebei Medical University, Shijiazhuang, ChinaKey Laboratory of Biomechanics of Hebei Province, Shijiazhuang, ChinaCenter for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, ChinaSchool of Biomedical Engineering, ShanghaiTech University, Shanghai, ChinaPurposeThe aim of this study is to compare the blood oxygen level–dependent (BOLD) fluctuation power in 96 frequency points ranging from 0 to 0.25 Hz between benign and malignant musculoskeletal (MSK) tumors via power spectrum analyses using functional magnetic resonance imaging (fMRI).Materials and methodsBOLD-fMRI and T1-weighted imaging (T1WI) of 92 patients with benign or malignant MSK tumors were acquired by 1.5-T magnetic resonance scanner. For each patient, the tumor-related BOLD time series were extracted, and then, the power spectrum of BOLD time series was calculated and was then divided into 96 frequency points. A two-sample t-test was used to assess whether there was a significant difference in the powers (the “power” is the square of the BOLD fluctuation amplitude with arbitrary unit) of each frequency point between benign and malignant MSK tumors. The receiver operator characteristic (ROC) analysis was used to assess the diagnostic capability of distinguishing between benign and malignant MSK tumors.ResultsThe result of the two-sample t-test showed that there was significant difference in the power between benign and malignant MSK tumor at frequency points of 58 (0.1508 Hz, P = 0.036), 59 (0.1534 Hz, P = 0.032), and 95 (0.247 Hz, P = 0.014), respectively. The ROC analysis of mean power of three frequency points showed that the area of under curve is 0.706 (P = 0.009), and the cutoff value is 0.73130. If the power of the tumor greater than or equal to 0.73130 is considered the possibility of benign tumor, then the diagnostic sensitivity and specificity values are 83% and 59%, respectively. The post hoc analysis showed that the merged power of 0.1508 and 0.1534 Hz in benign MSK tumors was significantly higher than that in malignant ones (P = 0.014). The ROC analysis showed that, if the benign MSK tumor was diagnosed with the power greater than or equal to the cutoff value of 1.41241, then the sensitivity and specificity were 67% and 68%, respectively.ConclusionThe mean power of three frequency points at 0.1508, 0.1534, and 0.247 Hz may potentially be a biomarker to differentiate benign from malignant MSK tumors. By combining the power of 0.1508 and 0.1534 Hz, we could better detect the difference between benign and malignant MSK tumors with higher specificity.https://www.frontiersin.org/articles/10.3389/fonc.2022.794555/fullblood oxygen level-dependentmusculoskeletal tumorsfunctional magnetic resonance imagingbenignmalignant
spellingShingle Lisha Duan
Lisha Duan
Huiyuan Huang
Huiyuan Huang
Feng Sun
Feng Sun
Zhenjiang Zhao
Zhenjiang Zhao
Mengjun Wang
Mengjun Wang
Mei Xing
Mei Xing
Yufeng Zang
Yufeng Zang
Xiaofei Xiu
Meng Wang
Hong Yu
Jianling Cui
Jianling Cui
Han Zhang
Han Zhang
Comparing the blood oxygen level–dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imaging
Frontiers in Oncology
blood oxygen level-dependent
musculoskeletal tumors
functional magnetic resonance imaging
benign
malignant
title Comparing the blood oxygen level–dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imaging
title_full Comparing the blood oxygen level–dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imaging
title_fullStr Comparing the blood oxygen level–dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imaging
title_full_unstemmed Comparing the blood oxygen level–dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imaging
title_short Comparing the blood oxygen level–dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imaging
title_sort comparing the blood oxygen level dependent fluctuation power of benign and malignant musculoskeletal tumors using functional magnetic resonance imaging
topic blood oxygen level-dependent
musculoskeletal tumors
functional magnetic resonance imaging
benign
malignant
url https://www.frontiersin.org/articles/10.3389/fonc.2022.794555/full
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