Literature DB >> 29740660

Differentiation between malignant and benign musculoskeletal tumors using diffusion kurtosis imaging.

Masaki Ogawa1, Hirohito Kan2, Nobuyuki Arai2, Taro Murai3, Yoshihiko Manabe3, Yusuke Sawada3, Yuta Shibamoto3.   

Abstract

OBJECTIVE: The purpose of this study was to evaluate differences in parameters of diffusion kurtosis imaging (DKI) and minimum apparent diffusion coefficient (ADCmin) between benign and malignant musculoskeletal tumors.
MATERIALS AND METHODS: In this prospective study, 43 patients were scanned using a DKI protocol on a 3-T MR scanner. Eligibility criteria were: non-fatty, non-cystic soft tissue or osteolytic tumors; > 2 cm; location in the retroperitoneum, pelvis, leg, or neck; and no prior treatment. They were clinically or histologically diagnosed as benign (n = 27) or malignant (n = 16). In the DKI protocol, diffusion-weighted imaging was performed using four b values (0-2000 s/mm2) and 21 diffusion directions. Mean kurtosis (MK) values were calculated on the MR console. A recently developed software application enabling reliable calculation was used for DKI analysis.
RESULTS: MK showed a strong correction with ADCmin (Spearman's rs = 0.95). Both MK and ADCmin values differed between benign and malignant tumors (p < 0.01). For benign and malignant tumors, the mean MK values (± SD) were 0.49 ± 0.17 and 1.14 ± 0.30, respectively, and ADCmin values were 1.54 ± 0.47 and 0.49 ± 0.17 × 10-3 mm2/s, respectively. At cutoffs of MK = 0.81 and ADCmin = 0.77 × 10-3 mm2/s, the specificity and sensitivity for diagnosis of malignant tumors were 96.3 and 93.8% for MK and 96.3 and 93.8% for ADCmin, respectively. The areas under the curve were 0.97 and 0.99 for MK and ADCmin, respectively (p = 0.31).
CONCLUSIONS: MK and ADCmin showed high diagnostic accuracy and strong correlation, reflecting the accuracy of MK. However, no clear added value of DKI could be demonstrated in differentiating musculoskeletal tumors.

Entities:  

Keywords:  Differentiation; Diffusion kurtosis imaging; Diffusion weighted imaging; MR imaging; Musculoskeletal tumor

Mesh:

Year:  2018        PMID: 29740660     DOI: 10.1007/s00256-018-2946-0

Source DB:  PubMed          Journal:  Skeletal Radiol        ISSN: 0364-2348            Impact factor:   2.199


  20 in total

1.  Diffusion kurtosis as an in vivo imaging marker for reactive astrogliosis in traumatic brain injury.

Authors:  Jiachen Zhuo; Su Xu; Julie L Proctor; Roger J Mullins; Jonathan Z Simon; Gary Fiskum; Rao P Gullapalli
Journal:  Neuroimage       Date:  2011-07-30       Impact factor: 6.556

2.  Optimization of Scan Parameters to Reduce Acquisition Time for Diffusion Kurtosis Imaging at 1.5T.

Authors:  Suguru Yokosawa; Makoto Sasaki; Yoshitaka Bito; Kenji Ito; Fumio Yamashita; Jonathan Goodwin; Satomi Higuchi; Kohsuke Kudo
Journal:  Magn Reson Med Sci       Date:  2015-06-23       Impact factor: 2.471

3.  Is there a role for diffusion-weighted MRI (DWI) in the diagnosis of central cartilage tumors?

Authors:  H Douis; L Jeys; R Grimer; S Vaiyapuri; A M Davies
Journal:  Skeletal Radiol       Date:  2015-03-07       Impact factor: 2.199

4.  Diffusion-weighted imaging of soft tissue tumors: usefulness of the apparent diffusion coefficient for differential diagnosis.

Authors:  Shuji Nagata; Hiroshi Nishimura; Masafumi Uchida; Jun Sakoda; Tatsuyuki Tonan; Kouji Hiraoka; Kensei Nagata; Jun Akiba; Toshi Abe; Naofumi Hayabuchi
Journal:  Radiat Med       Date:  2008-07-27

5.  Diffusion-weighted magnetic resonance imaging for the initial characterization of non-fatty soft tissue tumors: correlation between T2 signal intensity and ADC values.

Authors:  Pedro Augusto Gondim Teixeira; Frederique Gay; Bailiang Chen; Marie Zins; François Sirveaux; Jacques Felblinger; Alain Blum
Journal:  Skeletal Radiol       Date:  2015-12-01       Impact factor: 2.199

6.  [A correlation between diffusion kurtosis imaging and the proliferative activity of brain glioma].

Authors:  A S Tonoyan; I N Pronin; D I Pitshelauri; L V Shishkina; L M Fadeeva; E L Pogosbekyan; N E Zakharova; E I Shults; N V Khachanova; V N Kornienko; A A Potapov
Journal:  Zh Vopr Neirokhir Im N N Burdenko       Date:  2015

7.  Characterization of breast tumors using diffusion kurtosis imaging (DKI).

Authors:  Dongmei Wu; Guanwu Li; Junxiang Zhang; Shixing Chang; Jiani Hu; Yongming Dai
Journal:  PLoS One       Date:  2014-11-18       Impact factor: 3.240

8.  The value of diffusion kurtosis imaging in assessing pathological complete response to neoadjuvant chemoradiation therapy in rectal cancer: a comparison with conventional diffusion-weighted imaging.

Authors:  Feixiang Hu; Wei Tang; Yiqun Sun; Dang Wan; Sanjun Cai; Zhen Zhang; Robert Grimm; Xu Yan; Caixia Fu; Tong Tong; Weijun Peng
Journal:  Oncotarget       Date:  2017-04-27

9.  Non-Gaussian analysis of diffusion weighted imaging in head and neck at 3T: a pilot study in patients with nasopharyngeal carcinoma.

Authors:  Jing Yuan; David Ka Wai Yeung; Greta S P Mok; Kunwar S Bhatia; Yi-Xiang J Wang; Anil T Ahuja; Ann D King
Journal:  PLoS One       Date:  2014-01-23       Impact factor: 3.240

10.  Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferation.

Authors:  Rifeng Jiang; Jingjing Jiang; Lingyun Zhao; Jiaxuan Zhang; Shun Zhang; Yihao Yao; Shiqi Yang; Jingjing Shi; Nanxi Shen; Changliang Su; Ju Zhang; Wenzhen Zhu
Journal:  Oncotarget       Date:  2015-12-08
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  5 in total

Review 1.  An update in musculoskeletal tumors: from quantitative imaging to radiomics.

Authors:  Vito Chianca; Domenico Albano; Carmelo Messina; Gabriele Vincenzo; Stefania Rizzo; Filippo Del Grande; Luca Maria Sconfienza
Journal:  Radiol Med       Date:  2021-05-19       Impact factor: 3.469

2.  Evaluation of Thin-slice Coronal Single-shot Turbo Spin-echo Diffusion-weighted Imaging of the Hand: A Comparison with Conventional Echo-planar Diffusion-weighted Imaging.

Authors:  Masaki Ogawa; Motoo Nakagawa; Nobuyuki Arai; Hirohito Kan; Shota Ohba; Shunsuke Shibata; Hiroyuki Maki; Yuta Shibamoto
Journal:  Magn Reson Med Sci       Date:  2019-10-24       Impact factor: 2.471

3.  A CT-based radiomics nomogram for distinguishing between benign and malignant bone tumours.

Authors:  Weikai Sun; Shunli Liu; Jia Guo; Song Liu; Dapeng Hao; Feng Hou; Hexiang Wang; Wenjian Xu
Journal:  Cancer Imaging       Date:  2021-02-06       Impact factor: 3.909

4.  Diagnostic Performance of Diffusion MRI for differentiating Benign and Malignant Nonfatty Musculoskeletal Soft Tissue Tumors: A Systematic Review and Meta-analysis.

Authors:  Qian Wang; Xinguang Xiao; Yanchang Liang; Hao Wen; Xiaopeng Wen; Meilan Gu; Cuiping Ren; Kunbin Li; Liangwen Yu; Liming Lu
Journal:  J Cancer       Date:  2021-10-28       Impact factor: 4.207

5.  Comparison of Conventional DWI, Intravoxel Incoherent Motion Imaging, and Diffusion Kurtosis Imaging in Differentiating Lung Lesions.

Authors:  Yu Zheng; Jie Li; Kang Chen; Xiaochun Zhang; Huan Sun; Shujiao Li; Xie Zhang; Zhenping Deng; Na Liang; Shihong Li
Journal:  Front Oncol       Date:  2022-01-20       Impact factor: 6.244

  5 in total

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