Min Fan1, Zhaoyu Xing1, Yanan Du2, Liang Pan2, Yangyang Sun1, Xiaozhou He1. 1. Department of Urology, the Third Affiliated Hospital of Soochow University, Changzhou 213003, China. 2. Department of Radiology, the Third Affiliated Hospital of Soochow University, Changzhou 213003, China.
Abstract
BACKGROUND: Diffusion-weighted imaging (DWI) can noninvasively assess renal allograft pathologic changes that provide useful information for clinical management and prognostication. However, it is still unknown whether the bi-exponential model analysis of DWI signals is superior to that of the mono-exponential model. METHODS: Pathologic and DWI data from a total of 47 allografts were prospectively collected and analyzed. Kidney transplant interstitial fibrosis was quantified digitally. The severity of acute and chronic pathologic changes was semi-quantified by calculating the acute composite scores (ACS) and chronic composite score (CCS). Mono-exponential total apparent diffusion coefficient (ADCT), and the bi-exponential parameters of true diffusion (D) and perfusion fraction (fp) were acquired. The diagnostic performances of both mono-exponential and bi-exponential parameters were assessed and compared by calculating the area under the curve (AUC) from receiver-operating characteristic (ROC) curve analysis. RESULTS: ADCT, D, and fp were all significantly correlated with interstitial fibrosis, ACS, and CCS. Cortical fp discriminated mild from moderate and severe ACS with the largest AUC of 0.89 [95% confidence interval (CI), 0.77-0.96]. Noticeably, only cortical fp could differentiate severe ACS from mild-to-moderate ACS (P<0.001) with an AUC of 0.80 (95% CI, 0.65-0.90) and a sensitivity of 100% (95% CI, 66.4-100%). Strikingly, the joint use of D and fp in either the cortex or the medulla could achieve a sensitivity of 100% for identifying either mild or severe interstitial fibrosis. Meanwhile, the serial use of cortical D and cortical fp showed the largest specificity for identifying both mild [88.9% (95% CI, 70.8-97.6%)] and severe [84.4% (95% CI, 67.2-94.7%)] interstitial fibrosis. For identifying mild CCS, the AUC of medullary ADCT (0.90, 95% CI, 0.78-0.97) was similar to that of cortical D (0.81, 95% CI, 0.67-0.91) and fp (0.86, 95% CI, 0.73-0.94), but statistically larger than that of medullary D (P=0.005) and fp (P=0.01). Furthermore, the parallel use of cortical D and cortical fp could increase the sensitivity to 95.0% (95% CI, 75.1-99.9%), whereas serial use of medullary D and medullary fp could increase the specificity to 100% (95% CI, 87.2-100%). The AUCs for differentiating severe from mild and moderate CCS were statistically insignificant among all parameters in the cortex and medulla (P≥0.15). CONCLUSIONS: Cortical fp was superior to the ADCT for identifying both mild and severe acute pathologic changes. Nevertheless, ADCT was equal to or better than single D or fp for evaluating chronic pathologic changes. Thus, both monoexponential and bi-exponential analysis of DWI images are complementary for evaluating kidney allograft pathologic changes, and the combined use of D and fp can increase the sensitivity and specificity for discriminating allograft pathologic changes severity. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.
BACKGROUND: Diffusion-weighted imaging (DWI) can noninvasively assess renal allograft pathologic changes that provide useful information for clinical management and prognostication. However, it is still unknown whether the bi-exponential model analysis of DWI signals is superior to that of the mono-exponential model. METHODS: Pathologic and DWI data from a total of 47 allografts were prospectively collected and analyzed. Kidney transplant interstitial fibrosis was quantified digitally. The severity of acute and chronic pathologic changes was semi-quantified by calculating the acute composite scores (ACS) and chronic composite score (CCS). Mono-exponential total apparent diffusion coefficient (ADCT), and the bi-exponential parameters of true diffusion (D) and perfusion fraction (fp) were acquired. The diagnostic performances of both mono-exponential and bi-exponential parameters were assessed and compared by calculating the area under the curve (AUC) from receiver-operating characteristic (ROC) curve analysis. RESULTS: ADCT, D, and fp were all significantly correlated with interstitial fibrosis, ACS, and CCS. Cortical fp discriminated mild from moderate and severe ACS with the largest AUC of 0.89 [95% confidence interval (CI), 0.77-0.96]. Noticeably, only cortical fp could differentiate severe ACS from mild-to-moderate ACS (P<0.001) with an AUC of 0.80 (95% CI, 0.65-0.90) and a sensitivity of 100% (95% CI, 66.4-100%). Strikingly, the joint use of D and fp in either the cortex or the medulla could achieve a sensitivity of 100% for identifying either mild or severe interstitial fibrosis. Meanwhile, the serial use of cortical D and cortical fp showed the largest specificity for identifying both mild [88.9% (95% CI, 70.8-97.6%)] and severe [84.4% (95% CI, 67.2-94.7%)] interstitial fibrosis. For identifying mild CCS, the AUC of medullary ADCT (0.90, 95% CI, 0.78-0.97) was similar to that of cortical D (0.81, 95% CI, 0.67-0.91) and fp (0.86, 95% CI, 0.73-0.94), but statistically larger than that of medullary D (P=0.005) and fp (P=0.01). Furthermore, the parallel use of cortical D and cortical fp could increase the sensitivity to 95.0% (95% CI, 75.1-99.9%), whereas serial use of medullary D and medullary fp could increase the specificity to 100% (95% CI, 87.2-100%). The AUCs for differentiating severe from mild and moderate CCS were statistically insignificant among all parameters in the cortex and medulla (P≥0.15). CONCLUSIONS: Cortical fp was superior to the ADCT for identifying both mild and severe acute pathologic changes. Nevertheless, ADCT was equal to or better than single D or fp for evaluating chronic pathologic changes. Thus, both monoexponential and bi-exponential analysis of DWI images are complementary for evaluating kidney allograft pathologic changes, and the combined use of D and fp can increase the sensitivity and specificity for discriminating allograft pathologic changes severity. 2020 Quantitative Imaging in Medicine and Surgery. All rights reserved.
Authors: Pottumarthi V Prasad; Lu-Ping Li; Jon M Thacker; Wei Li; Bradley Hack; Orly Kohn; Stuart M Sprague Journal: Am J Nephrol Date: 2019-01-22 Impact factor: 3.754
Authors: Mike Notohamiprodjo; Aivars Kalnins; Martin Andrassy; Manuel Kolb; Benjamin Ehle; Susanna Mueller; Michael N Thomas; Jens Werner; Markus Guba; Konstantin Nikolaou; Joachim Andrassy Journal: PLoS One Date: 2016-11-07 Impact factor: 3.240
Authors: A Loupy; M Haas; K Solez; L Racusen; D Glotz; D Seron; B J Nankivell; R B Colvin; M Afrouzian; E Akalin; N Alachkar; S Bagnasco; J U Becker; L Cornell; C Drachenberg; D Dragun; H de Kort; I W Gibson; E S Kraus; C Lefaucheur; C Legendre; H Liapis; T Muthukumar; V Nickeleit; B Orandi; W Park; M Rabant; P Randhawa; E F Reed; C Roufosse; S V Seshan; B Sis; H K Singh; C Schinstock; A Tambur; A Zeevi; M Mengel Journal: Am J Transplant Date: 2017-01 Impact factor: 8.086
Authors: Joāo S Periquito; Thomas Gladytz; Jason M Millward; Paula Ramos Delgado; Kathleen Cantow; Dirk Grosenick; Luis Hummel; Ariane Anger; Kaixuan Zhao; Erdmann Seeliger; Andreas Pohlmann; Sonia Waiczies; Thoralf Niendorf Journal: Quant Imaging Med Surg Date: 2021-07