Unveiling the diagnostic potential of diffusion kurtosis imaging and intravoxel incoherent motion for detecting and characterizing prostate cancer: a meta-analysis

被引:2
作者
Rajabi, Pouria [1 ]
Rezakhaniha, Bijan [2 ]
Galougahi, Mohammad H. Kazemi [3 ]
Mohammadimehr, Mojgan [4 ,5 ]
Sharifnia, Hesam [6 ]
Pakzad, Roshanak [7 ]
Niroomand, Hassan [8 ]
机构
[1] Univ Tehran Med Sci, Sch Med, Tehran, Iran
[2] AJA Univ Med Sci, Fac Med, Dept Urol, Tehran, Iran
[3] AJA Univ Med Sci, Fac Med, Dept Social Med, Tehran, Iran
[4] Aja Univ Med Sci, Infect Dis Res Ctr, Tehran, Iran
[5] Aja Univ Med Sci, Fac Paramedicine, Dept Lab Sci, Tehran, Iran
[6] AJA Univ Med Sci, Sch Med, Dept Hlth Management & Econ, Tehran, Iran
[7] Univ Tehran Med Sci, Imam Khomeini Hosp Complex, Dept Otorhinolaryngol Head & Neck Surg, Tehran, Iran
[8] AJA Univ Med Sci, Trauma Res Ctr, Shahid Etemadzadeh St,Fatemi St West, Tehran, Iran
关键词
Diffusion weighted imaging; Diffusion kurtosis imaging; Intravoxel incoherent motion; Prostate cancer; Diagnostic performance; Meta-analysis; MULTIPARAMETRIC MRI; WEIGHTED MRI; ACCURACY; PERFORMANCE; AGGRESSIVENESS; ZONE; PERFUSION; MODELS; TISSUE; DWI;
D O I
10.1007/s00261-024-04454-x
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
PurposeThis study aims to assess the diagnostic capabilities of Diffusion Kurtosis Imaging (DKI) and Intravoxel Incoherent Motion (IVIM) in prostate cancer (PCa) detection and characterization.MaterialsA comprehensive search was conducted across PubMed, Scopus, Web of Science, and the Cochrane Library for articles published up to September 10, 2023, that evaluated the diagnostic efficacy of MD, MK, Dt, f, and Dp parameters. Data were pooled using a bivariate mixed-effects regression model and analyzed with R software.ResultsIn total, 27 studies were included. The analysis revealed distinct diagnostic efficacies for DKI and IVIM. In the overall model, sensitivity and specificity were 0.807 and 0.797, respectively, with prospective studies showing higher specificity (0.858, p = 0.024). The detection model yielded increased sensitivity (0.845) and specificity (0.812), with DKI outperforming IVIM in both metrics (sensitivity: 0.87, p = 0.043; specificity: 0.837, p = 0.26); MD had high sensitivity (0.88) and specificity (0.82), while MK's specificity was significantly higher (0.854, p = 0.04); Dp's sensitivity was significantly lower (0.64, p = 0.016). In characterization, sensitivity and specificity were 0.708 and 0.735, respectively, with no significant differences between DKI and IVIM or Gleason Scores; MK had higher sensitivity (0.78, p = 0.039), and f's sensitivity was significantly lower (0.51, p = 0.019).ConclusionIn summary, the study underscores DKI's enhanced diagnostic accuracy over IVIM in detecting PCa, with MK standing out for its precision. Conversely, Dp and f lag in diagnostic performance. Despite these promising results, the study highlights the imperative for standardized protocols and study designs to achieve reliable and consistent outcomes.
引用
收藏
页码:319 / 335
页数:17
相关论文
共 53 条
[51]   Comparison of Diffusion Kurtosis Imaging and Amide Proton Transfer Imaging in the Diagnosis and Risk Assessment of Prostate Cancer [J].
Yin, Huijia ;
Wang, Dongdong ;
Yan, Ruifang ;
Jin, Xingxing ;
Hu, Ying ;
Zhai, Zhansheng ;
Duan, Jinhui ;
Zhang, Jian ;
Wang, Kaiyu ;
Han, Dongming .
FRONTIERS IN ONCOLOGY, 2021, 11
[52]   Differentiation of Prostate Cancer and Stromal Hyperplasia in the Transition Zone With Monoexponential, Stretched-Exponential Diffusion-Weighted Imaging and Diffusion Kurtosis Imaging in a Reduced Number of b Values: Correlation With Whole-Mount Pathology [J].
Zhou, Bingni ;
Liu, Xiaohang ;
Gan, Hualei ;
Gao, Hongbo ;
Zhang, Yong ;
Zhou, Liangping ;
Gu, Yajia .
JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 2022, 46 (04) :545-550
[53]   Comparison of Diffusion Kurtosis Imaging and Standard Mono-Exponential Apparent Diffusion Coefficient in Diagnosis of Significant Prostate Cancer-A Correlation with Gleason Score Assessed on Whole-Mount Histopathology Specimens [J].
Zurowska, Anna ;
Peksa, Rafal ;
Grzywinska, Malgorzata ;
Panas, Damian ;
Sowa, Marek ;
Skrobisz, Katarzyna ;
Matuszewski, Marcin ;
Szurowska, Edyta .
DIAGNOSTICS, 2023, 13 (02)