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Prostat Kanserinin Saptanması ve Derecelendirilmesinde Voksel İçi Tutarsız Hareket (IVIM) Parametrelerinin Tanısal Değeri

Yıl 2022, , 236 - 244, 30.06.2022
https://doi.org/10.31832/smj.1068740

Öz

Amaç: Voksel içi tutarsız hareket (IVIM) parametrelerinin, prostat kanseri (PK) ile normal prostat dokusu ve benign prostat lezyonlarından ayırmadaki başarısını ve PK’yi derecelendirmedeki yararını saptamak.
Gereç ve Yöntemler: Bu metodolojik araştırmaya 1,5 T cihaz kullanılarak prostata yönelik yapılan çok parametreli manyetik rezonans görüntüleme (Mp-MRG)’si ve doku tanısı olan toplam 68 hasta (21 prostatit, 19 benign prostat hiperplazisi, 27 PK) dahil edildi. Rutin Mp-MRG’ye, 0 ile 1200 s/mm2 arasında değişen 15 farklı b değeri içeren IVIM sekansı eklendi. Tüm b değerlerinden yapılan ölçümler baz alınarak; görünür difüzyon katsayısı (ADC), gerçek difüzyon katsayısı (D), kan akışıyla ilişkili yalancı difüzyon katsayısı (D*) ve perfüzyon fraksiyonu (f) parametreleri elde edildi. Kolmogorov-Smirnov testine göre tüm veriler normal dağılım göstermekte idi. Bu parametrelerin prostat lezyonlarını saptamadaki ve PK derecelendirmesindeki farklılıkları t testi ile analiz edildi, PK derecesi ile korelasyonu Pearson korelasyon testi ile saptandı. Parametrelerin tanısal performansını değerlendirmek için ROC analizi yapıldı. IVIM sekansının Mp-MRG’ye ek katkısının araştırılması amaçlı lineer diskriminant analizi (LDA) kullanıldı.
Bulgular: ADC, D, D* ve f parametrelerinin rutin Mp-MRG’ye eklenmesi ile duyarlılık, özgüllük ve doğruluk oranları sırası ile %87, %92 ve %90’dan %92, %95 ve %94’e yükseldi. Bu dört parametre de PK ile sağlıklı prostat dokusunu ayırmada faydalı idi (her biri için p<0,0001). ADC ve D parametreleri PK’yi benign lezyonlardan ayırt etmede başarılı iken (ikisi için de p<0,0001); D* ve f parametreleri başarısız idi (sırasıyla p=0,603 ve p=0,454). ADC, D, D* ve f parametrelerinin düşük ve orta/yüksek dereceli PK’yi ayırmadaki yararı istatiksel olarak anlamlı bulunmadı (sırasıyla p=0,314; p=0,413; p=0,619 ve p=0,628).
Sonuç: IVIM parametrelerinin PK’yi normal dokudan ayırmada başarılı olduğu ve rutin Mp-MRG’ye ek katkı sunduğu görülmüştür.

Destekleyen Kurum

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Proje Numarası

yok

Teşekkür

yok

Kaynakça

  • Referans 1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: Cancer J Clin 2018;68:394–424.
  • Referans 2. Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System. Am J Surg Pathol 2016;40:244-252.
  • Referans 3. Anwar SSM, Anwar Khan Z, Shoaib Hamid R, Haroon F, Sayani R, Beg M, et al. Assessment of Apparent Diffusion Coefficient Values as Predictor of Aggressiveness in Peripheral Zone Prostate Cancer: Comparison with Gleason Score. ISRN Radiology 2014;2014:1-7.
  • Referans 4. Ahmed HU, El-Shater BA, Brown LC, Gabe R, Kaplan R, Parmar MK, et al. Diagnostic accuracy of multiparametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 2017;389:815-22.
  • Referans 5. Rosenkrantz AB, Taneja SS. Prostate MRI Can Reduce Overdiagnosis and Overtreatment of Prostate Cancer. Acad Radiol 2015;22:1000-6.
  • Referans 6. Kurhanewicz J, Vigneron D, Carroll P, Coakley F. Multiparametric magnetic resonance imaging in prostate cancer: present and future. Curr Opin Urol 2008;18(1):71–7.
  • Referans 7. Mottet N, Bellmunt J, Bolla M, Briers E, Cumberbatch MG, De Santis M, et al. EAU–ESTRO–SIOG guidelines on prostate cancer. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol 2016;S0302–2838(16):30470–5.
  • Referans 8. Tan CH, Wei W, Johnson V, Kundra V. Diffusion-weighted MRI in the detection of prostate cancer: meta-analysis. Am J Roentgenol 2012;199:822–9.
  • Referans 9. Jin G, Su DK, Luo NB, Liu LD, Zhu X, Huang XY. Meta-analysis of diffusionweighted magnetic resonance imaging in detecting prostate cancer. J Comput Assis Tomography 2013;37:195–202.
  • Referans 10. Jie C, Rongbo L, Ping T. The value of diffusion-weighted imaging in the detection of prostate cancer: a meta-analysis. Eur Radiol 2014;24:1929–41.
  • Referans 11. Padhani AR, Liu G, Koh DM, Chenevert TL, Thoeny HC, Takahara T, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009;11(2):102–25.
  • Referans 12. Le BD, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 1988;168:497-505.
  • Referans 13. Valerio M, Zini C, Fierro D, Giura F, Colarieti A, Giuliani A, et al. 3T multiparametric MRI of the prostate: Does intravoxel incoherent motion diffusion imaging have a role in the detection and stratification of prostate cancer in the peripheral zone. Eur J Radiol 2016;85:790-794.
  • Referans 14. Shinmoto H, Tamura C, Soga S, Shiomi E, Yoshihara N, Kaji T, et al. An intravoxel incoherent motion diffusionweighted imaging study of prostate cancer. AJR Am J Roentgenol 2012;199:496-500.
  • Referans 15. Bao J, Wang X, Hu C, Hou J, Dong F, Guo L. Differentiation of prostate cancer lesions in the Transition Zone by diffusion- weighted MRI. Eur J Radiol Open 2017;4:123-128.
  • Referans 16. Pesapane F, Patella F, Fumarola EM, Panella S, Ierardi AM, Pompili GG, et al. Intravoxel Incoherent Motion (IVIM) Diffusion Weighted Imaging (DWI) in the Periferic Prostate Cancer Detection and Stratification. Med Oncol. 2017;34(3):35.
  • Referans 17. Le BD, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions:application to diffusion and perfusion in neurologic disorders. Radiology 1986;161:401-407.
  • Referans 18. Le BD. Intravoxel incoherent motion perfusion MR imaging: a wake-up call. Radiology 2008;249:748-752. Referans 19. Iima M, Le BD. Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future. Radiology 2016;278:13-32.
  • Referans 20. Koyuncu Sokmen B, Sabet S, Oz A, Server S, Namal E, Dayangaç M, et al. Value of Intravoxel Incoherent Motion for Hepatocellular Carcinoma Grading. Transplantation Proceedings 2019;51:1861-66.
  • Referans 21. Thai JN, Narayanan HA, George AK, Siddiqui MM, Shah P, Mertan FV, et al. Validation of PI-RADS Version 2 in Transition Zone Lesions for the Detection of Prostate Cancer. Radiology 2018;288:485-491.
  • Referans 22. Liu X, Zhou L, Peng W, Wang C, Wang H. Differentiation of central gland prostate cancer from benign prostatic hyperplasia using monoexponential and biexponential diffusion-weighted imaging. Magn Reson Imaging 2013;31:1318-1324.
  • Referans 23. Dennis LK, Lynch CF, Torner JC. Epidemiologic association between prostatitis and prostate cancer. Urology 2002;60:78–83.
  • Referans 24. Shan Y, Chen X, Liu K, Zeng M, Zhou J. Prostate cancer aggressive prediction: preponderant diagnostic performances of intravoxel incoherent motion (IVIM) imaging and diffusion kurtosis imaging (DKI) beyond ADC at 3.0 T scanner with gleason score at final pathology. Abdom Radiol (NY) 2019;44(10):3441-3452.

Diagnostic Value of Intravoxel Incoherent Motion Parameters in Differentiating and Grading Prostate Cancer

Yıl 2022, , 236 - 244, 30.06.2022
https://doi.org/10.31832/smj.1068740

Öz

Objective: To evaluate the value of intravoxel incoherent motion (IVIM) parameters in differentiating prostate cancer (PCa) and predicting PCa grading.
Material and Methods: Sixty-eight patients (21 prostatitis, 19 benign prostatic hyperplasia, 27 PCa) were enrolled in this methodological research. In addition to routine multiparametric magnetic resonance imaging (Mp-MRI), IVIM sequence including 15 different b values ranging from 0 to 1200 s/mm2 was taken. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f) parameters were obtained based on the measurements made from all b values. According to the Kolmogorov-Smirnov test, all data were normally distributed. The differences of these parameters in detecting prostate lesions and grading PCa were analyzed by t test, and correlation with PCa grade was determined by Pearson’s correlation test. ROC analysis was performed to evaluate the diagnostic performance of the parameters. Linear discriminant analysis was performed to investigate the additional value of the IVIM sequence to Mp-MRI.
Results: With the addition of IVIM parameters to routine Mp-MRI; the sensitivity, specificity, and accuracy rates increased from 87%, 92%, and 90% to 92%, 95%, and 94%, respectively. All of parameters showed good diagnostic performance in differentiating PCa from healthy prostate tissue (p<0.0001 for each). While ADC and D were significantly lower in PCa compared with benign lesions (p<0.0001 for both); there were no statistically differences in D* and f (p=0.603 and p=0.454, respectively). IVIM parameters were not successful in differentiating low and moderate/high grade PCa (p=0.314, p=0.413, p=0.619 and p=0.628, respectively).
Conclusion: IVIM parameters are useful in distinguishing PCa from healthy tissue and increase the diagnostic performance of conventional Mp-MRI.

Proje Numarası

yok

Kaynakça

  • Referans 1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: Cancer J Clin 2018;68:394–424.
  • Referans 2. Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System. Am J Surg Pathol 2016;40:244-252.
  • Referans 3. Anwar SSM, Anwar Khan Z, Shoaib Hamid R, Haroon F, Sayani R, Beg M, et al. Assessment of Apparent Diffusion Coefficient Values as Predictor of Aggressiveness in Peripheral Zone Prostate Cancer: Comparison with Gleason Score. ISRN Radiology 2014;2014:1-7.
  • Referans 4. Ahmed HU, El-Shater BA, Brown LC, Gabe R, Kaplan R, Parmar MK, et al. Diagnostic accuracy of multiparametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 2017;389:815-22.
  • Referans 5. Rosenkrantz AB, Taneja SS. Prostate MRI Can Reduce Overdiagnosis and Overtreatment of Prostate Cancer. Acad Radiol 2015;22:1000-6.
  • Referans 6. Kurhanewicz J, Vigneron D, Carroll P, Coakley F. Multiparametric magnetic resonance imaging in prostate cancer: present and future. Curr Opin Urol 2008;18(1):71–7.
  • Referans 7. Mottet N, Bellmunt J, Bolla M, Briers E, Cumberbatch MG, De Santis M, et al. EAU–ESTRO–SIOG guidelines on prostate cancer. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol 2016;S0302–2838(16):30470–5.
  • Referans 8. Tan CH, Wei W, Johnson V, Kundra V. Diffusion-weighted MRI in the detection of prostate cancer: meta-analysis. Am J Roentgenol 2012;199:822–9.
  • Referans 9. Jin G, Su DK, Luo NB, Liu LD, Zhu X, Huang XY. Meta-analysis of diffusionweighted magnetic resonance imaging in detecting prostate cancer. J Comput Assis Tomography 2013;37:195–202.
  • Referans 10. Jie C, Rongbo L, Ping T. The value of diffusion-weighted imaging in the detection of prostate cancer: a meta-analysis. Eur Radiol 2014;24:1929–41.
  • Referans 11. Padhani AR, Liu G, Koh DM, Chenevert TL, Thoeny HC, Takahara T, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 2009;11(2):102–25.
  • Referans 12. Le BD, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 1988;168:497-505.
  • Referans 13. Valerio M, Zini C, Fierro D, Giura F, Colarieti A, Giuliani A, et al. 3T multiparametric MRI of the prostate: Does intravoxel incoherent motion diffusion imaging have a role in the detection and stratification of prostate cancer in the peripheral zone. Eur J Radiol 2016;85:790-794.
  • Referans 14. Shinmoto H, Tamura C, Soga S, Shiomi E, Yoshihara N, Kaji T, et al. An intravoxel incoherent motion diffusionweighted imaging study of prostate cancer. AJR Am J Roentgenol 2012;199:496-500.
  • Referans 15. Bao J, Wang X, Hu C, Hou J, Dong F, Guo L. Differentiation of prostate cancer lesions in the Transition Zone by diffusion- weighted MRI. Eur J Radiol Open 2017;4:123-128.
  • Referans 16. Pesapane F, Patella F, Fumarola EM, Panella S, Ierardi AM, Pompili GG, et al. Intravoxel Incoherent Motion (IVIM) Diffusion Weighted Imaging (DWI) in the Periferic Prostate Cancer Detection and Stratification. Med Oncol. 2017;34(3):35.
  • Referans 17. Le BD, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions:application to diffusion and perfusion in neurologic disorders. Radiology 1986;161:401-407.
  • Referans 18. Le BD. Intravoxel incoherent motion perfusion MR imaging: a wake-up call. Radiology 2008;249:748-752. Referans 19. Iima M, Le BD. Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future. Radiology 2016;278:13-32.
  • Referans 20. Koyuncu Sokmen B, Sabet S, Oz A, Server S, Namal E, Dayangaç M, et al. Value of Intravoxel Incoherent Motion for Hepatocellular Carcinoma Grading. Transplantation Proceedings 2019;51:1861-66.
  • Referans 21. Thai JN, Narayanan HA, George AK, Siddiqui MM, Shah P, Mertan FV, et al. Validation of PI-RADS Version 2 in Transition Zone Lesions for the Detection of Prostate Cancer. Radiology 2018;288:485-491.
  • Referans 22. Liu X, Zhou L, Peng W, Wang C, Wang H. Differentiation of central gland prostate cancer from benign prostatic hyperplasia using monoexponential and biexponential diffusion-weighted imaging. Magn Reson Imaging 2013;31:1318-1324.
  • Referans 23. Dennis LK, Lynch CF, Torner JC. Epidemiologic association between prostatitis and prostate cancer. Urology 2002;60:78–83.
  • Referans 24. Shan Y, Chen X, Liu K, Zeng M, Zhou J. Prostate cancer aggressive prediction: preponderant diagnostic performances of intravoxel incoherent motion (IVIM) imaging and diffusion kurtosis imaging (DKI) beyond ADC at 3.0 T scanner with gleason score at final pathology. Abdom Radiol (NY) 2019;44(10):3441-3452.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Sağlık Kurumları Yönetimi
Bölüm Makaleler
Yazarlar

İbrahim Halil Sever 0000-0002-6549-7682

Furkan Ertürk Urfalı 0000-0002-4875-7761

Proje Numarası yok
Yayımlanma Tarihi 30 Haziran 2022
Gönderilme Tarihi 5 Şubat 2022
Yayımlandığı Sayı Yıl 2022

Kaynak Göster

AMA Sever İH, Urfalı FE. Prostat Kanserinin Saptanması ve Derecelendirilmesinde Voksel İçi Tutarsız Hareket (IVIM) Parametrelerinin Tanısal Değeri. Sakarya Tıp Dergisi. Haziran 2022;12(2):236-244. doi:10.31832/smj.1068740

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