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Böbrek Kitlelerinin Benign-Malign Ayırıcı Tanısında Bilgisayarlı Tomografi Dansite Değerlerinin Etkinliği

Year 2021, Volume: 5 Issue: 1, 38 - 42, 20.04.2021
https://doi.org/10.46332/aemj.786090

Abstract

Amaç: Benign ve malign böbrek kitlelerinin ayrımında kontrastlı ve kontrastsız Bilgisayarlı Tomografi imajlar üzerinde lezyonlardan ölçülen ortalama Hounsfield Unit (HU) değerinin rolünü araştırmayı amaçladık.

Araçlar ve Yöntem: Bu retrospektif çalışmada böbrekte kitle nedeniyle biyopsi yapılan hastaların histopatolojik sonuçları, demografik özellikleri ve Bilgisayarlı Tomografi incelemeleri hastane veritabanından tarandı. Hastaların patoloji sonuçları benign ve malign olarak gruplara ayrıldı. Kontrastlı ve kontrastsız bilgisayarlı tomografi imajlarda lezyonlardan ortalama dansiteler HU olarak ölçüldü. Benign ve malign gruplar arasında ölçülen HU değerleri açısından student t testi ile karşılaştırmalar yapıldı.

Bulgular: Kontrastlı BT’si olan ve histopatoloji sonucu malign çıkan hastaların (17 erkek,11 kadın hasta) ölçülen HU değerlerinin ortalaması 83,7± 39,4 benign çıkanların (5 erkek,4 kadın) ortalaması ise 81,0± 52,9 olup iki grup arasında anlamlı farklılık saptanmadı (p:0.8704). Kontrastsız BT’si olup histopatoloji sonucu malign çıkan hastaların (12 erkek,9 kadın hasta) ölçülen HU değerlerinin ortalaması 29,3± 8,1, benign çıkanların (1 erkek, 4 kadın) ortalaması ise 9,4± 42,0 olup benign grupta HU değeri anlamlı olarak düşük bulundu. (p:0.0426). 

Sonuç: Kontrastlı BT imajlarında (70. Saniye) renal kitlelerden ölçülen ortalama HU değerlerinin çalışmamızda malign-benign kitle ayrımına katkı sağlamadığı saptanmıştır ancak kontrastsız imajlarda ölçülen değerler bu ayrım için faydalı olabilir.

References

  • 1. Kay FU, Pedrosa I. Imaging of Solid Renal Masses. Radiol Clin North Am. 2017;55(2):243-258.
  • 2. Laguna B, Westphalen AC, Guimarães CT, Whang Z, Simko J, Zagoria R. Uncommon malignant renal tumors and atypical presentation of common ones: a guide for radiologists. Abdom Radiol (NY). 2019;44(4):1430-1452.
  • 3. Kutikov A, Fossett LK, Ramchandani P, et al. Incidence of benign pathologic findings at partial nephrectomy for solitary renal mass presumed to be renal cell carcinoma on preoperative imaging. Urology. 2006;68(4):737-740.
  • 4. Hounsfield GN. Computed medical imaging. Nobel lecture, J Comput Assist Tomogr. 1980;4(5):665-674.
  • 5. Prasad SR, Surabhi VR, Menias CO, Raut AA, Chintapalli KN. Benign renal neoplasms in adults: cross-sectional imaging findings. AJR Am J Roentgenol. 2008;190(1):158-164.
  • 6. van Oostenbrugge TJ, Fütterer JJ, Mulders PFA. Diagnostic Imaging for Solid Renal Tumors: A Pictorial Review. Kidney Cancer. 2018;2(2):79-93.
  • 7. Kang SK, Huang WC, Pandharipande PV, Chandarana H. Solid renal masses: what the numbers tell us. Am J Roentgenol. 2014;202(6):1196-1206.
  • 8. Dyer R, DiSantis DJ, McClennan BL. Simplified imaging approach for evaluation of the solid renal mass in adults. Radiology. 2008;247(2):331-343.
  • 9. Choi JH, Kim JW, Lee JY, et al. Comparison of computed tomography findings between renal oncocytomas and chromophobe renal cell carcinomas. Korean J Urol. 2015;56(10):695-702.
  • 10. Yang CW, Shen SH, Chang YH, et al. Are there useful CT features to differentiate renal cell carcinoma from lipidpoor renal angiomyolipoma?. AJR Am J Roentgenol. 2013;201(5):1017-1028.
  • 11. Mancini ME, Albergo A, Moschetta M, Angelelli M, Scardapane A, Angelelli G. Diagnostic potential of multidetector computed tomography for characterizing small renal masses. Sci World J. 2015;2015:476750.
  • 12. Heilbrun ME, Remer EM, Casalino DD, et al. ACR Appropriateness Criteria indeterminate renal mass. J Am Coll Radiol. 2015;12(4):333-341.
  • 13. Zhou C, Urbauer DL, Fellman BM, et al. Metastases to the kidney: a comprehensive analysis of 151 patients from a tertiary referral centre. BJU Int. 2016;117(5):775-782.
  • 14. Adamy A, Von Bodman C, Ghoneim T, Favaretto RL, Bernstein M, Russo P. Solitary, isolated metastatic disease to the kidney: Memorial Sloan-Kettering Cancer Center experience. BJU Int. 2011;108(3):338-342.

Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions

Year 2021, Volume: 5 Issue: 1, 38 - 42, 20.04.2021
https://doi.org/10.46332/aemj.786090

Abstract

Purpose: We aimed to investigate the role of mean Hounsfield Unit(HU) values measured on enhanced or unenhanced Computed Tomography(CT) images for the differentiation of benign and malignant kidney lesions.

Materials and Methods: In this retrospective study, CT images, demographic features, and histopathological results of the patients with renal lesions were reviewed from the hospital database. The pathological results were classified as benign and malignant. Mean attenuation values of the lesions were measured as HU on enhanced or un-enhanced CT images. The mean HU values of benign and malignant lesions were compared by using the student’s t-test.

Results: The mean HU value of lesions who have enhanced CT scan with malignant histopathological results (17 males, 11 females) was 83,7±39,4, with benign histopathological results (5 males, 4 females) was 81,0±52,9. There was no statistically significant difference between malignant and benign lesions regarding the HU values on enhanced (70. Second delay) CT images (p:0.8704). The mean HU value of lesions which has unenhanced CT scan with malignant histopathological results (12 males, 9 females) was 29,3±8,1 with benign histopathological results (1 male, 4 females) was 9.4±42,0. The mean HU value of malignant lesions was higher than those of benign lesions on unenhanced images, and this difference was statistically significant (p:0,0426). 

Conclusion: The mean HU values of kidney masses on unenhanced CT images were found to be useful for the differentiation of benign and malignant lesions but values on enhanced (70 second delay) images in our study did not achieve such discrimination.

References

  • 1. Kay FU, Pedrosa I. Imaging of Solid Renal Masses. Radiol Clin North Am. 2017;55(2):243-258.
  • 2. Laguna B, Westphalen AC, Guimarães CT, Whang Z, Simko J, Zagoria R. Uncommon malignant renal tumors and atypical presentation of common ones: a guide for radiologists. Abdom Radiol (NY). 2019;44(4):1430-1452.
  • 3. Kutikov A, Fossett LK, Ramchandani P, et al. Incidence of benign pathologic findings at partial nephrectomy for solitary renal mass presumed to be renal cell carcinoma on preoperative imaging. Urology. 2006;68(4):737-740.
  • 4. Hounsfield GN. Computed medical imaging. Nobel lecture, J Comput Assist Tomogr. 1980;4(5):665-674.
  • 5. Prasad SR, Surabhi VR, Menias CO, Raut AA, Chintapalli KN. Benign renal neoplasms in adults: cross-sectional imaging findings. AJR Am J Roentgenol. 2008;190(1):158-164.
  • 6. van Oostenbrugge TJ, Fütterer JJ, Mulders PFA. Diagnostic Imaging for Solid Renal Tumors: A Pictorial Review. Kidney Cancer. 2018;2(2):79-93.
  • 7. Kang SK, Huang WC, Pandharipande PV, Chandarana H. Solid renal masses: what the numbers tell us. Am J Roentgenol. 2014;202(6):1196-1206.
  • 8. Dyer R, DiSantis DJ, McClennan BL. Simplified imaging approach for evaluation of the solid renal mass in adults. Radiology. 2008;247(2):331-343.
  • 9. Choi JH, Kim JW, Lee JY, et al. Comparison of computed tomography findings between renal oncocytomas and chromophobe renal cell carcinomas. Korean J Urol. 2015;56(10):695-702.
  • 10. Yang CW, Shen SH, Chang YH, et al. Are there useful CT features to differentiate renal cell carcinoma from lipidpoor renal angiomyolipoma?. AJR Am J Roentgenol. 2013;201(5):1017-1028.
  • 11. Mancini ME, Albergo A, Moschetta M, Angelelli M, Scardapane A, Angelelli G. Diagnostic potential of multidetector computed tomography for characterizing small renal masses. Sci World J. 2015;2015:476750.
  • 12. Heilbrun ME, Remer EM, Casalino DD, et al. ACR Appropriateness Criteria indeterminate renal mass. J Am Coll Radiol. 2015;12(4):333-341.
  • 13. Zhou C, Urbauer DL, Fellman BM, et al. Metastases to the kidney: a comprehensive analysis of 151 patients from a tertiary referral centre. BJU Int. 2016;117(5):775-782.
  • 14. Adamy A, Von Bodman C, Ghoneim T, Favaretto RL, Bernstein M, Russo P. Solitary, isolated metastatic disease to the kidney: Memorial Sloan-Kettering Cancer Center experience. BJU Int. 2011;108(3):338-342.
There are 14 citations in total.

Details

Primary Language English
Subjects Clinical Sciences
Journal Section Original Articles
Authors

Sercan Özkaçmaz 0000-0002-9245-0206

İlyas Dündar 0000-0002-1429-077X

Nazım Kankılıç This is me 0000-0002-3747-3798

Mesut Özgökçe 0000-0002-3095-2446

Abdullah Gül 0000-0001-7117-9210

Rahmi Aslan 0000-0002-4563-0386

Publication Date April 20, 2021
Published in Issue Year 2021 Volume: 5 Issue: 1

Cite

APA Özkaçmaz, S., Dündar, İ., Kankılıç, N., Özgökçe, M., et al. (2021). Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions. Ahi Evran Medical Journal, 5(1), 38-42. https://doi.org/10.46332/aemj.786090
AMA Özkaçmaz S, Dündar İ, Kankılıç N, Özgökçe M, Gül A, Aslan R. Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions. Ahi Evran Med J. April 2021;5(1):38-42. doi:10.46332/aemj.786090
Chicago Özkaçmaz, Sercan, İlyas Dündar, Nazım Kankılıç, Mesut Özgökçe, Abdullah Gül, and Rahmi Aslan. “Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions”. Ahi Evran Medical Journal 5, no. 1 (April 2021): 38-42. https://doi.org/10.46332/aemj.786090.
EndNote Özkaçmaz S, Dündar İ, Kankılıç N, Özgökçe M, Gül A, Aslan R (April 1, 2021) Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions. Ahi Evran Medical Journal 5 1 38–42.
IEEE S. Özkaçmaz, İ. Dündar, N. Kankılıç, M. Özgökçe, A. Gül, and R. Aslan, “Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions”, Ahi Evran Med J, vol. 5, no. 1, pp. 38–42, 2021, doi: 10.46332/aemj.786090.
ISNAD Özkaçmaz, Sercan et al. “Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions”. Ahi Evran Medical Journal 5/1 (April 2021), 38-42. https://doi.org/10.46332/aemj.786090.
JAMA Özkaçmaz S, Dündar İ, Kankılıç N, Özgökçe M, Gül A, Aslan R. Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions. Ahi Evran Med J. 2021;5:38–42.
MLA Özkaçmaz, Sercan et al. “Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions”. Ahi Evran Medical Journal, vol. 5, no. 1, 2021, pp. 38-42, doi:10.46332/aemj.786090.
Vancouver Özkaçmaz S, Dündar İ, Kankılıç N, Özgökçe M, Gül A, Aslan R. Effectiveness of Computed Tomography Density Value in the Differential Diagnosis of Benign and Malignant Renal Lesions. Ahi Evran Med J. 2021;5(1):38-42.

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