BACKGROUND AND PURPOSE: Early diagnosis of perfusion deficits in patients with acute stroke could guide treatment decisions and improve prognosis. We investigated the sensitivity of perfusion CT studies using parametric time-to-peak maps to assess ischemic brain tissue with respect to early infarct signs on native CT scans. METHODS: First-pass, single-section perfusion CT was performed in 20 patients who presented with symptoms of acute stroke within 6 hours of onset. Initial CT perfusion studies were compared with follow-up studies within 30 hours in 10 patients. A manual, region of interest (ROI)-based, local evaluation procedure was performed to determine delayed time-to-peak values and diminished peak amplitudes. In addition, time-to-peak parameter maps were processed off-line from the dynamic CT data sets to identify areas of perfusion deficits, which were expressed as hemispheric lesion areas (HLAs). Evolution of the ischemic regions was assessed by comparing the HLA on the initial and follow-up studies as well as on the native CT scan of the follow-up studies. RESULTS: Diagnostic time-to-peak maps were generated in 19 of 20 initial and in nine of 10 follow-up perfusion CT studies. The initial time-to-peak map showed perfusion deficits in 14 of 20 patients. Hemispheric territorial infarcts were diagnosed with a sensitivity of 93%. Perfusion deficits in two patients with brain stem infarctions and three patients with lacunar strokes were missed. Follow-up time-to-peak maps showed the extent of reperfusion after various therapeutic strategies. CONCLUSION: Perfusion CT is potentially useful for detecting cerebral perfusion deficits in acute ischemic stroke before morphologic changes are observable on native CT scans. Compared with a locally restricted ROI-based evaluation, time-to-peak maps provide sensitive, global indications of malperfused brain areas, facilitate lesion localization, and allow assessment of the evolution of the infarction during follow-up.
BACKGROUND AND PURPOSE: Early diagnosis of perfusion deficits in patients with acute stroke could guide treatment decisions and improve prognosis. We investigated the sensitivity of perfusion CT studies using parametric time-to-peak maps to assess ischemic brain tissue with respect to early infarct signs on native CT scans. METHODS: First-pass, single-section perfusion CT was performed in 20 patients who presented with symptoms of acute stroke within 6 hours of onset. Initial CT perfusion studies were compared with follow-up studies within 30 hours in 10 patients. A manual, region of interest (ROI)-based, local evaluation procedure was performed to determine delayed time-to-peak values and diminished peak amplitudes. In addition, time-to-peak parameter maps were processed off-line from the dynamic CT data sets to identify areas of perfusion deficits, which were expressed as hemispheric lesion areas (HLAs). Evolution of the ischemic regions was assessed by comparing the HLA on the initial and follow-up studies as well as on the native CT scan of the follow-up studies. RESULTS: Diagnostic time-to-peak maps were generated in 19 of 20 initial and in nine of 10 follow-up perfusion CT studies. The initial time-to-peak map showed perfusion deficits in 14 of 20 patients. Hemispheric territorial infarcts were diagnosed with a sensitivity of 93%. Perfusion deficits in two patients with brain stem infarctions and three patients with lacunar strokes were missed. Follow-up time-to-peak maps showed the extent of reperfusion after various therapeutic strategies. CONCLUSION: Perfusion CT is potentially useful for detecting cerebral perfusion deficits in acute ischemic stroke before morphologic changes are observable on native CT scans. Compared with a locally restricted ROI-based evaluation, time-to-peak maps provide sensitive, global indications of malperfused brain areas, facilitate lesion localization, and allow assessment of the evolution of the infarction during follow-up.
Authors: G Marchal; C Serrati; P Rioux; M C Petit-Taboué; F Viader; V de la Sayette; F Le Doze; P Lochon; J M Derlon; J M Orgogozo; J C Baron Journal: Lancet Date: 1993-04-10 Impact factor: 79.321
Authors: S Flacke; E Keller; A Hartmann; P Mürtz; J Textor; H Urbach; P Folkers; F Träber; J Gieseke; W Block; L Scheef; C Leutner; D Pauleit; H H Schild Journal: Rofo Date: 1998-05
Authors: W Hacke; M Kaste; C Fieschi; D Toni; E Lesaffre; R von Kummer; G Boysen; E Bluhmki; G Höxter; M H Mahagne Journal: JAMA Date: 1995-10-04 Impact factor: 56.272
Authors: H C Roberts; T P Roberts; W S Smith; T J Lee; N J Fischbein; W P Dillon Journal: AJNR Am J Neuroradiol Date: 2001 Jun-Jul Impact factor: 3.825
Authors: C M Strother; F Bender; Y Deuerling-Zheng; K Royalty; K A Pulfer; J Baumgart; M Zellerhoff; B Aagaard-Kienitz; D B Niemann; M L Lindstrom Journal: AJNR Am J Neuroradiol Date: 2010-02-18 Impact factor: 3.825