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Soft tissue sarcoma: DWI and DCE-MRI parameters correlate with Ki-67 labeling index

  • Musculoskeletal
  • Published:
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Abstract

Objectives

To examine the correlation of diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging (MRI) parameters with Ki-67 labeling index (LI) in soft tissue sarcoma (STS).

Methods

The institutional review board approved this retrospective study, and the requirement for informed consent was waived. Thirty-six patients with STS who underwent 3.0-T MRI, including diffusion-weighted and dynamic contrast-enhanced MRI, between July 2011 and February 2018, were included in this study. The mean and minimum apparent diffusion coefficients (ADCs) (ADCmean and ADCmin, respectively), volume transfer constant, reflux rate, and volume fraction of the extravascular extracellular matrix of each lesion were independently analyzed by two readers. Their relationship with the Ki-67 LI was examined using Spearman’s correlation analyses. Differences between low- and high-proliferation groups based on Ki-67 LI were evaluated statistically. Optimal cut-off points were determined using the area under the curve analysis for significant parameters. Interobserver agreement was assessed with the intraclass correlation coefficient.

Results

ADCmean (ρ = − 0.333, p = 0.047) was significantly and inversely correlated with Ki-67 LI. The high-proliferation group showed a significantly lower ADCmean than did the low-proliferation group (median, 1.08 vs. 1.20; p = 0.048). When a cut-off ADCmean value of 1.16 × 10−3 mm2/s was used, the sensitivity, specificity, and area under the curve for differentiating low- and high-proliferation groups were 75.0%, 60.0%, and 0.712, respectively. Interobserver agreements between the two readers were almost perfect for all parameters.

Conclusions

ADCmean was correlated with Ki-67 LI and could help differentiate between STS with low and high proliferation potential.

Key Points

• ADC mean was significantly and inversely correlated with Ki-67 labeling index in soft tissue sarcoma.

• In the high-proliferation group, ADC mean values were significantly lower than those of the low-proliferation group.

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Abbreviations

ADC:

Apparent diffusion coefficient

AIF:

Arterial input function

DW:

Diffusion-weighted

FNCLCC:

French Federation of Cancer Centers Sarcoma Group

ICC:

Intraclass correlation coefficient

LI:

Labeling index

MRI:

Magnetic resonance imaging

STS:

Soft tissue sarcoma

TE:

Echo time

TR:

Repetition time

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Funding

The authors state that this work has not received any funding.

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Correspondence to Young Cheol Yoon.

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Guarantor

The scientific guarantor of this publication is Young Cheol Yoon.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

We declare that some of our subjects overlap with the previously reported study [Lee JH, Yoon YC, Jin W, Cha JG, Kim S (2019) Development and validation of nomograms for malignancy prediction in soft tissue tumors using magnetic resonance imaging measurements. Sci Rep 9:4897]. In the prior study, we reported on 236 patients. Among them, 25 patients were included in the current study. The prior study developed, validated, and compared nomograms for malignancy prediction in soft tissue tumors using conventional and diffusion-weighed MRI measurements. On the contrary, the current study focuses on correlation between MRI parameters and Ki-67 labeling index using dynamic contrast-enhanced MRI as well as diffusion-weighed MRI.

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• retrospective

• observational

• performed at one institution

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Lee, J.H., Yoon, Y.C., Seo, S.W. et al. Soft tissue sarcoma: DWI and DCE-MRI parameters correlate with Ki-67 labeling index. Eur Radiol 30, 914–924 (2020). https://doi.org/10.1007/s00330-019-06445-9

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  • DOI: https://doi.org/10.1007/s00330-019-06445-9

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