title: How to measure renal artery stenosis--a retrospective comparison of morphological measurement approaches in relation to hemodynamic significance.
abstract: BACKGROUND
  Although it is well known that renal artery stenosis may cause renovascular hypertension, it is unclear how the degree of stenosis should best be measured in morphological images. The aim of this study was to determine which morphological measures from Computed Tomography Angiography (CTA) and Magnetic Resonance Angiography (MRA) are best in predicting whether a renal artery stenosis is hemodynamically significant or not.
  
  
  METHODS
  Forty-seven patients with hypertension and a clinical suspicion of renovascular hypertension were examined with CTA, MRA, captopril-enhanced renography (CER) and captopril test (Ctest). CTA and MRA images of the renal arteries were analyzed by two readers using interactive vessel segmentation software. The measures included minimum diameter, minimum area, diameter reduction and area reduction. In addition, two radiologists visually judged the diameter reduction without automated segmentation. The results were then compared using limits of agreement and intra-class correlation, and correlated with the results from CER combined with Ctest (which were used as standard of reference) using receiver operating characteristics (ROC) analysis.
  
  
  RESULTS
  A total of 68 kidneys had all three investigations (CTA, MRA and CER + Ctest), where 11 kidneys (16.2 %) got a positive result on the CER + Ctest. The greatest area under ROC curve (AUROC) was found for the area reduction on MRA, with a value of 0.91 (95 % confidence interval 0.82-0.99), excluding accessory renal arteries. As comparison, the AUROC for the radiologists' visual assessments on CTA and MRA were 0.90 (0.82-0.98) and 0.91 (0.83-0.99) respectively. None of the differences were statistically significant.
  
  
  CONCLUSIONS
  No significant differences were found between the morphological measures in their ability to predict hemodynamically significant stenosis, but a tendency of MRA having higher AUROC than CTA. There was no significant difference between measurements made by the radiologists and measurements made with fuzzy connectedness segmentation. Further studies are required to definitely identify the optimal measurement approach.
authors.affiliation: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. malin.j.andersson@regionostergotland.se.|Department of Radiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. malin.j.andersson@regionostergotland.se.
authors.forename: Malin
authors.initials: M
authors.lastname: Andersson
authors.affiliation: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. k.jagervall@gmail.com.|Department of Radiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. k.jagervall@gmail.com.
authors.forename: Karl
authors.initials: K
authors.lastname: Jägervall
authors.affiliation: Department of Nephrology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. per.eriksson@regionostergotland.se.
authors.forename: Per
authors.initials: P
authors.lastname: Eriksson
authors.affiliation: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. anders.persson@cmiv.liu.se.|Department of Radiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. anders.persson@cmiv.liu.se.
authors.forename: Anders
authors.initials: A
authors.lastname: Persson
authors.affiliation: Department of Clinical Physiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. goran.granerus@telia.com.
authors.forename: Göran
authors.initials: G
authors.lastname: Granerus
authors.affiliation: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. chunliang.wang@sth.kth.se.|Department of Radiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. chunliang.wang@sth.kth.se.|School of Technology and Health (STH), KTH Royal Institute of Technology, Stockholm, Sweden. chunliang.wang@sth.kth.se.
authors.forename: Chunliang
authors.initials: C
authors.lastname: Wang
authors.affiliation: Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden. orjan.smedby@sth.kth.se.|Department of Radiology and Department of Medical and Health Sciences, Linköping University, Linköping, Sweden. orjan.smedby@sth.kth.se.|School of Technology and Health (STH), KTH Royal Institute of Technology, Stockholm, Sweden. orjan.smedby@sth.kth.se.
authors.forename: Örjan
authors.initials: Ö
authors.lastname: Smedby
mesh_terms: D019540:Area Under Curve; D005260:Female; D017143:Fuzzy Logic; D006439:Hemodynamics; D006801:Humans; D006973:Hypertension / Q000150:complications*; D006978:Hypertension, Renovascular / Q000175:diagnosis*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008297:Male; D012372:ROC Curve; D011866:Radioisotope Renography / Q000379:methods*; D012078:Renal Artery Obstruction / Q000175:diagnosis*; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*