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Abdominal Radiology

, Volume 42, Issue 5, pp 1485–1492 | Cite as

Subjective and objective heterogeneity scores for differentiating small renal masses using contrast-enhanced CT

  • Shuai Leng
  • Naoki Takahashi
  • Daniel Gomez Cardona
  • Kazuhiro Kitajima
  • Brian McCollough
  • Zhoubo Li
  • Akira Kawashima
  • Bradley C. Leibovich
  • Cynthia H. McCollough
Article

Abstract

Purpose

The aim of this study was to assess the effect of denoising on objective heterogeneity scores and its diagnostic capability for the diagnosis of angiomyolipoma (AML) and renal cell carcinoma (RCC).

Materials and Methods

A total of 158 resected renal masses ≤4 cm [98 clear cell (cc) RCCs, 36 papillary (pap)-RCCs, and 24 AMLs] from 139 patients were evaluated. A representative contrast-enhanced computed tomography (CT) image for each mass was selected by a genitourinary radiologist. A largest possible region of interest was drawn on each mass by the radiologist, from which three objective heterogeneity indices were calculated: standard deviation (SD), entropy (Ent), and uniformity (Uni). Objective heterogeneity indices were also calculated after images were processed with a denoising algorithm (non-local means) at three strengths: weak, medium, and strong. Two genitourinary radiologists also subjectively scored each mass independently using a three-point scale (1–3; with 1 the least and 3 the most heterogeneous), which were added to represent the final subjective heterogeneity score of each mass. Heterogeneity scores were compared among mass types, and area under the ROC curve (AUC) was calculated.

Results

For all heterogeneity indices, cc-RCC was significantly more heterogeneous than pap-RCC and AML (p < 0.001), but no significant difference was found between pap-RCC and AML (p > 0.01). For cc-RCC and pap-RCC differentiation, AUCs were 0.91, 0.81, 0.78, and 0.78 for the subjective score, SD, Ent, and Uni, respectively, using original images. The corresponding AUC values were 0.84, 0.74, 0.79, and 0.80 for differentiation of AML and cc-RCC. Noise reduction at weak setting improves AUC values by 0.03, 0.05, and 0.05 for SD, entropy, and uniformity for differentiation of cc-RCC from pap-RCC. Further increase of filtering strength did not improve AUC values. For differentiation of AML vs. cc-RCC, the AUC values stayed relatively flat using the noise reduction technique at different strengths for all three indices.

Conclusions

Both subjective and objective heterogeneity indices can differentiate cc-RCC from pap-RCC and AML. Noise reduction improved differentiation of cc-RCC from pap-RCC, but not differentiation of AML from cc-RCC.

Keywords

Renal mass Texture analysis Heterogeneity Noise reduction 

Notes

Compliance with ethical standards

Funding

No funding was received for this study.

Conflict of interest

Dr. McCollough receives industry funding from Siemens Healthcare, unrelated to this work. The other authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Shuai Leng
    • 1
  • Naoki Takahashi
    • 1
  • Daniel Gomez Cardona
    • 1
    • 3
  • Kazuhiro Kitajima
    • 1
    • 4
  • Brian McCollough
    • 1
  • Zhoubo Li
    • 1
    • 5
  • Akira Kawashima
    • 1
  • Bradley C. Leibovich
    • 2
  • Cynthia H. McCollough
    • 1
  1. 1.Department of RadiologyMayo ClinicRochesterUSA
  2. 2.Department of UrologyMayo ClinicRochesterUSA
  3. 3.Department of Medical PhysicsUniversity of Wisconsin-MadisonMadisonUSA
  4. 4.Department of Radiology, Faculty of MedicineKobe UniversityKobeJapan
  5. 5.GE HealthcareWaukeshaUSA

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