Timeliness of splenic time-to-peak affects liver tumor CT perfusion measurements

Aim In liver CT perfusion, the dual-input maximum slope (DI-MS) method is commonly used to estimate perfusion to aid diagnosis of tumors. The DI-MS method relies on a model that assumes the splenic time-to-peak (TTP) separates arterial and portal venous perfusion, and occurs prior to venous perfusion. In this preclinical study, we examined how the timeliness of splenic TTP affects DI-MS perfusion calculations of liver tumors. Materials and Methods We analyzed imaging data obtained from 11 New Zealand White rabbits bearing a single implanted VX2 tumor in liver. A liver 320-slice CT perfusion protocol (5,400 images per study) was used to generate images. Times for arterial and portal slopes were recorded, and hepatic arterial perfusion (HAP), portal perfusion (HPP) and perfusion index (HPI) for liver and tumor were separately calculated using manual and automated methods. T-test comparisons and Bland-Altman plot analyses were performed. Results Mean tumor TTP occurred at 9.79 s (SD=3.41) and splenic TTP at 9.75 s (SD=4.47, p=0.98). In 3/11 (27.27%) cases, tumor SP occurred prior to spleen (mean difference=1.33 s, SD=1.15 s). In these cases, mean automated HPP values were 43.8% (SD=52.48) higher compared to manually computed ones. There were statistically significant differences between automated and manual methods for normal liver and tumor HPI and HPP (p<0.01 and p<0.0001, respectively), but not HAP values (p=0.125 and p=0.78, respectively). There was also a statistically significant variation between methods for tumor HPP and HPI (p=0.001, respectively). Conclusion In 320-slice CT perfusion of liver in this preclinical model, we observed that tumor TTP occurred prior to splenic TTP in 27.27% of tumors in liver. This temporal relationship affects tumor perfusion calculations and should be identified to address potential deviations of model assumptions.

Preliminary Application of a Quantitative Collateral Assessment Method in Acute Ischemic Stroke Patients With Endovascular Treatments: A Single-Center Study

Objectives: To develop an efficient and quantitative assessment of collateral circulation on time maximum intensity projection CT angiography (tMIP CTA) in patients with acute ischemic stroke (AIS).Methods: Eighty-one AIS patients who underwent one-stop CTA-CT perfusion (CTP) from February 2016 to October 2020 were retrospectively reviewed. Single-phase CTA (sCTA) and tMIP CTA were developed from CTP data. Ischemic core (IC) volume, ischemic penumbra volume, and mismatch ratio were calculated. The Tan scale was used for the qualitative evaluation of collateral based on sCTA and tMIP CTA. Quantitative collateral circulation (CCq) parameters were calculated semi-automatically with software by the ratio of the vascular volume (V) on both hemispheres, including tMIP CTA VCCq and sCTA VCCq. Spearman correlation analysis was used to analyze the correlation of collateral-related parameters with final infarct volume (FIV). ROC and multivariable regression analysis were calculated to compare the significance of the above parameters in clinical outcome evaluation. The analysis time of the observers was also compared.Results: tMIP CTA VCCq (r = 0.61, p &lt; 0.01), IC volume (r = 0.66, p &lt; 0.01), Tan score on tMIP CTA (r = 0.52, p &lt; 0.01) and mismatch ratio (r = 0.60, p &lt; 0.01) showed moderate negative correlations with FIV. tMIP CTA VCCq showed the best prognostic value for clinical outcome (AUC = 0.93, p &lt; 0.001), and was an independent predictive factor of clinical outcome (OR = 0.14, p = 0.009). There was no difference in analysis time of tMIP CTA VCCq among observers (p = 0.079).Conclusion: The quantitative evaluation of collateral circulation on tMIP CTA is associated with clinical outcomes in AIS patients with endovascular treatments.

Role of diabetes in collateral status assessed in CT perfusion–derived dynamic CTA in anterior circulation stroke

Purpose Diabetes is associated with vascular dysfunction potentially impairing collateral recruitment in acute ischemic stroke. This retrospective study aimed at analyzing the impact of diabetes on collateralization assessed on dynamic CTA. Methods Collaterals were retrospectively assessed on CT perfusion–derived dynamic CTA according to the mCTA score by Menon in a cohort of patients with an acute occlusion of the M1 segment or carotid T. The extent of collateral circulation was related to the history of diabetes and to admission blood glucose and HbA1c levels. Results Two hundred thirty-nine patients were included. The mCTA collateral score was similar in patients with diabetes (median 3, interquartile range 3–4) and without diabetes (median 4, interquartile range 3–4) (P = 0.823). Diabetes was similarly frequent in patients with good (18.8%), intermediate (16.1%), and poor collaterals (16.0%) (P = 0.355). HbA1c was non-significantly higher in patients with poor collaterals (6.3 ± 1.5) compared to patients with intermediate (6.0 ± 0.9) and good collaterals (5.8 ± 0.9) (P = 0.061). Blood glucose levels were significantly higher in patients with poor compared to good collaterals (mean 141.6 vs. 121.8 mg/dl, P = 0.045). However, there was no significant difference between good and intermediate collaterals (mean 121.8 vs. 129.5 mg/dl, P = 0.161) as well as between intermediate and poor collaterals (129.5 vs. 141.6 mg/dl, P = 0.161). Conclusion There was no statistically significant difference among patients with good, intermediate, and poor collaterals regarding the presence of diabetes or HbA1c level on admission. However, stroke patients with poor collaterals tend to have higher blood glucose and HbA1c levels.

Whole-Brain Volume CT Angiography can Effectively Detect Early Ischemic Cerebrovascular Diseases

Objective: To investigate the role of whole-brain volume computed tomography (CT) perfusion in assessing early ischemic cerebrovascular diseases. Materials and Methods: Seventy-two patients with early ischemic cerebrovascular diseases who had undergone routine CT scan and 320-row volume CT whole-brain perfusion imaging within 8 h after admission were retrospectively enrolled in this one-center case-sectional study. The perfusion parameters of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), time to peak (TTP), and dynamic CT angiogram (4D-CTA) were obtained and analyzed. Results: Among 72 patients, 29 cases with 37 cerebral ischemic lesions were found in plain CT scan, whereas 51 cases with 76 lesions were found in whole-brain CT perfusion, with 30.6% more patients being detected. The CBF value was significantly lower in the abnormal than normal corresponding perfusion area in the healthy hemisphere (P<0.05), while the MTT and TTP values were significantly higher in the abnormal than the normal corresponding area (P<0.05). 4D-CTA image suggested that 59 cases had different degrees of stenosis or occlusion, including 11 mild, 18 moderate, 21 severe, and 9 occlusive cases. Four-D-CTA imaging could detect significantly (P<0.05) more patients with abnormal perfusion in severe cerebral vascular stenosis or occlusion than those with no, mild or moderate stenosis (93.33% vs. 16.67%) (P<0.05). The stenosis of intracranial and carotid arteries was positively correlated with MTT and TTP values (P<0.05). Conclusion: Whole-brain volume CT angiography can comprehensively display early cerebral ischemic lesions, cerebral blood perfusion status, and cerebral vascular stenosis, providing valuable information for early detection of ischemic cerebral diseases and appropriate treatment planning.

Telestroke Assessment With Perfusion CT Improves the Diagnostic Accuracy of Stroke vs. Mimic

Background and Purpose: CT perfusion (CTP) has been implemented widely in regional areas of Australia for telestroke assessment. The aim of this study was to determine if, as part of telestroke assessment, CTP provided added benefit to clinical features in distinguishing between strokes and mimic and between transient ischaemic attack (TIA) and mimic.Methods: We retrospectively analysed 1,513 consecutively recruited patients referred to the Northern New South Wales Telestroke service, where CTP is performed as a part of telestroke assessment. Patients were classified based on the final diagnosis of stroke, TIA, or mimic. Multivariate regression models were used to determine factors that could be used to differentiate between stroke and mimic and between TIA and mimic.Results: There were 693 strokes, 97 TIA, and 259 mimics included in the multivariate regression models. For the stroke vs. mimic model using symptoms only, the area under the curve (AUC) on the receiver operator curve (ROC) was 0.71 (95% CI 0.67–0.75). For the stroke vs. mimic model using the absence of ischaemic lesion on CTP in addition to clinical features, the AUC was 0.90 (95% CI 0.88–0.92). The multivariate regression model for predicting mimic from TIA using symptoms produced an AUC of 0.71 (95% CI 0.65–0.76). The addition of absence of an ischaemic lesion on CTP to clinical features for the TIA vs. mimic model had an AUC of 0.78 (95% CI 0.73–0.83)Conclusions: In the telehealth setting, the absence of an ischaemic lesion on CTP adds to the diagnostic accuracy in distinguishing mimic from stroke, above that from clinical features.