CT Perfusion Imaging Research Articles

RapidAI for Stroke Detection

What Is the Indication Under Review? The indication under review is the detection, using artificial intelligence (AI) software, of large vessel occlusion (LVO) (i.e., ischemic stroke) and intracranial hemorrhage (ICH) (i.e., hemorrhagic stroke) for people of any age with a suspected acute stroke. What Is RapidAI? RapidAI is an AI-enabled software platform that facilitates the viewing, processing, and analysis of CT imaging to aid clinicians in assessing patients, including those with suspected stroke. It builds on the original RAPID software, initially developed to automate and expedite the postprocessing of CT perfusion imaging. Currently, the platform also incorporates modules that perform AI-driven detection of LVO and ICH, which were the functionalities evaluated in this review. RapidAI is intended to complement, rather than replace, clinician interpretation of CT imaging and is to be used as a supportive tool rather than a standalone diagnostic intervention. What Is the Health Technology Expert Review Panel Recommendation for RapidAI? In locations where RapidAI has already been implemented for use in detecting suspected LVO and ICH, the Health Technology Expert Review Panel (HTERP) recommends RapidAI is used only as indicated, alongside clinician interpretation of CT imaging, to reduce the risk of incorrect results; and the generation of evidence to evaluate its value in health care systems, including its use in less-resourced centres with limited access to stroke care specialists. In locations considering the implementation of RapidAI for use in detecting suspected LVO and ICH, given the uncertainty and gaps in the evidence regarding clinical, economic, and equity value of RapidAI, HTERP cannot provide recommendations for or against its implementation.

The Los Angeles Motor Scale is independently associated with cerebral blood flow < 30% volume in large vessel occlusions.

Mechanical thrombectomy (MT) is the treatment standard for large vessel occlusion (LVO) stroke. Under current guidelines, only patients with smaller ischemic core volumes (ICV) are eligible for MT. Thus, it is of interest to quickly estimate ICV in stroke patients. The Los Angeles Motor Scale (LAMS) is a validated tool used to assess stroke severity directly in the field. This study aims to determine whether LAMS score is also associated with ICV, as defined by the CBF <30% volume on CT perfusion imaging. We performed a retrospective, multicenter cohort study of consecutive patients presenting with LVO stroke from 9/1/2017 to 10/1/2023. The inclusion criteria were patients with (1) stroke caused by large vessel occlusion confirmed on CTA and (2) diagnostically adequate, multimodal pretreatment CT imaging. Demographic, clinical, and imaging data was collected through manual chart review. Both univariate and multivariate analyses were applied to assess associations. A p-value <.05 was considered significant. A total of 283 patients (median age: 69, IQR: 61-78) were included in the study. On multivariate logistic regression analysis, we found that lower admission LAMS score (adjusted OR: 0.511, 95% CI: 0.313-0.834, p = .007) was independently associated with a CBF <30% volume of less than 50cc. Admission LAMS is an independent predictor of a CBF <30% volume of less than 50cc. This demonstrates that LAMS can be used to estimate ICV, which will aid in the early triaging of LVO patients to thrombectomy-capable centers.

Deep Learning Based Detection of Large Vessel Occlusions in Acute Ischemic Stroke Using High-Resolution Photon Counting Computed Tomography and Conventional Multidetector Computed Tomography.

Deep learning (DL) methods for detecting large vessel occlusion (LVO) in acute ischemic stroke (AIS) show promise, but the effect of computed tomography angiography (CTA) image quality on DL performance is unclear. Our study investigates the impact of improved image quality from Photon Counting Computed Tomography (PCCT) on LVO detection in AIS using aDL-based software prototype developed by acommercial vendor, which incorporates anovel deep learning architecture. 443 cases that underwent stroke diagnostics with CTA were included. Positive cases featured vascular occlusions in the Internal Carotid Artery (ICA), M1, and M2segments of the Middle Cerebral Artery (MCA). Negative cases showed no vessel occlusion on CTA. The performance of the DL-based LVO detection software prototype was assessed using Syngo.via version VB80. Our study included 267 non-occlusion cases and 176 cases. Among them, 150 cases were scanned via PCCT (no occlusion = 100, ICA and M1 = 41, M2 = 9), while 293 cases were scanned using conventional CT (no occlusion = 167, ICA and M1 = 89, M2 = 37). Independent of scanner type, the algorithm showed sensitivity and specificity of 70.5 and 98.9% for the detection of all occlusions. DL algorithm showed improved performance after excluding M2occlusions (sensitivity 86.2%). After stratification by scanner type, the algorithm showed significantly atrend towards better performance (p = 0.013) on PCCT CTA images for the detection of all occlusions (sensitivity 84.0%, specificity 99%) compared to CTA images from conventional CT scanner (sensitivity 65.1%, specificity 98.8%). The detection of M2occlusions was also better on PCCT CTA images (sensitivity 55.6%) compared to conventional scanner CTA images (sensitivity 18.9%), but the sample size for M2occlusions was limited, and further research is needed to confirm these findings. Our study suggests that PCCT CTA images may offer improved detection of large vessel occlusion, particularly for M2occlusions. However further research is needed to confirm these findings. One of the limitations of our study is the inability to exclude the presence of aperfusion deficit, despite ruling out vascular occlusion, due to the lack of CT perfusion (CTP) imaging data. Future research may investigate CNNs by leveraging both CTA and CTP images from PCCT for improved performance.

Fractional flow reserve measurement using dynamic CT perfusion imaging in patients with coronary artery disease

Fractional flow reserve measurement using dynamic CT perfusion imaging in patients with coronary artery disease

Evaluating the prognostic impact of hypoperfusion intensity ratio in acute ischemic stroke patients undergoing early-phase endovascular thrombectomy

This research aimed to assess the prognostic relevance of the hypoperfusion intensity ratio (HIR) concerning 90-day outcomes in patients with acute ischemic stroke (AIS) managed within the early intervention window. A retrospective review was conducted on AIS patients who received pretreatment computed tomography perfusion imaging and endovascular thrombectomy due to large vessel occlusions in the anterior circulation between January 2020 and September 2022. Clinical data, including the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) from non-contrast CT, along with perfusion metrics such as ischemic core, hypoperfusion extent, core-penumbra mismatch, and HIR, were analyzed. Patients were divided into groups with favorable (modified Rankin Scale score 0–2) and unfavorable outcomes (modified Rankin Scale score 3–6). Among the 187 patients evaluated, 95 (50.8%) had favorable outcomes. Univariate analysis showed significant associations between functional outcomes and variables like age, National Institutes of Health Stroke Scale score at admission, ASPECTS, HIR, ischemic core volume, and hypoperfusion volume (P &lt; .05). Multivariate analysis revealed that younger age (odds ratio [OR] 1.064; 95% confidence interval [CI] 1.025–1.106, P = .001), lower National Institutes of Health Stroke Scale score at admission (OR 1.116; 95% CI 1.038–1.199, P = .003), smaller ischemic core volume (OR 1.017; 95% CI 1.002–1.033, P = .029), higher ASPECTS (OR 0.800; 95% CI 0.662–0.967, P = .021), and reduced HIR (OR 1.516; 95% CI 1.230–1.869, P = .001) independently predicted favorable outcomes at 90 days. Lower HIR was independently linked to improved functional outcomes in AIS patients receiving endovascular thrombectomy within the early intervention timeframe.

Prognostic significance of stress dynamic myocardial CT perfusion: comparison with CT-FFR and CT angiography stenosis-the multicenter VALIDITY trial.

This study aimed to investigate the prognostic significance of stress dynamic myocardial CT perfusion imaging (CTP) and determine whether it has incremental advantages over coronary computed tomography angiography (CTA)-derived parameters. This prospective multicenter study included patients with suspected coronary artery disease who had undergone coronary CTA and CTP and were followed for 6 years. The endpoint was time-to-first major adverse cardiovascular event (MACE). MACEs included all-cause mortality, cardiac death, nonfatal myocardial infarction, unstable angina, late revascularization, and heart failure or aggravated angina symptoms requiring hospitalization. The CTP-derived absolute myocardial blood flow (MBF), relative MBF ratio (r-MBF), and the CTA-derived fractional flow reserve (CT-FFR) and stenosis were analyzed. The independent predictors, time-to-event distributions and the incremental prognostic value of CTP over CTA-derived parameters were assessed. A total of 226 patients (66.7 ± 11.3 years, 37.6% women) were enrolled with a median follow-up time of 1233 days. Twenty-one patients (9.29%) experienced MACEs and ten patients (4.4%) experienced hard MACEs. The r-MBF was the only independent predictor for MACEs in both all patients (hazard ratio [HR]: 0.82 (0.69-0.97), p = 0.01) and patients available for CTA stenosis (%) and CT-FFR calculation (HR: 0.72 (0.57-0.91), p = 0.006). The incremental prognostic significance of r-MBF over CT-FFR was confirmed after combining with CTA-derived parameters (concordance index: 0.919 vs. 0.811; p < 0.01). Patients with r-MBF < 0.77 were more likely to experience MACEs and have a lower average survival time (1565 vs. 1790 days; p < 0.01) after stent implantation. CTP-assessed r-MBF was independently correlated with MACEs and provided incremental prognostic significance. Question The prognostic significance of CT perfusion (CTP) lacks sufficient support from clinical research. Findings In this Chinese population, CTP has the strongest prognostic significance, over CT-Fractional Flow Reserve (FFR) and CTA stenosis in predicting major adverse cardiovascular events (MACEs). Clinical relevance Relative myocardial blood flow ratio had the strongest prognostic value and incremental advantages in predicting MACEs beyond CT-FFR and coronary CTA stenosis quantification, as well as advantages in patients with stents, aiding in personalized diagnosis and treatment plans.

Beyond conventional imaging: A systematic review and meta-analysis assessing the impact of computed tomography perfusion on ischemic stroke outcomes in the late window.

Non-contrast cranial computed tomography (NCCT) and CT angiogram (CTA) have become essential for endovascular treatment (EVT) in acute stroke. Patient selection may improve when CT perfusion (CTP) imaging is also added for patient selection. We aimed to analyze the effects of implementing CTP in acute ischemic stroke (AIS) patients' treatment to assess whether stroke outcomes differ in the late window. We searched the PubMed, Embase, and Web of Sciences databases to obtain articles related to CTA and CTP in EVT. Collected patient data were split into two groups: the CTP and control (NCCT + CTA) cohorts. Primary outcomes evaluated were modified Rankin Scale (mRS) scores, symptomatic intracranial hemorrhages (sICHs), mortality, and successful recanalization. There were 14 studies with 5809 total patients in the final analysis: 2602 received CTP and 3202 were in the control group. CTP/CTA patients showed significantly lower rates of 90-day stroke-related mortality (odds ratio (OR) = 0.72, 95% confidence interval (CI) = 0.60-0.87, p < 0.01) and significantly higher successful recanalization (OR = 1.42, 95% CI = 1.06-1.94, p < 0.01) compared with CTA-only patients. Analysis of other outcomes including functional independence (mRS = 0-2), critical times, and intracranial hemorrhages was non-significant (p > 0.05). The study highlights the usefulness of CTP-guided therapy as a supplementary tool in EVT selection in the late window. Although the addition of CTP resulted in lower mortality, the favorable outcomes did not improve. Further evidence is required to establish a clearer understanding of the potential advantages or limitations of incorporating CTP in stroke imaging.

Intra-arterial contrast administration: a confounding appearance on stroke CT imaging.

A female patient in her 70s presented with mild slurred speech. Clinical assessment revealed only minor dysarthria. A stroke protocol CT study was performed comprising a non-contrast CT head, CT angiogram (CTA) and CT perfusion (CTP) imaging. Despite a normal non-contrast CT head, CTP imaging demonstrated a large left anterior circulation territory abnormality compatible with core infarct. The CTA displayed absent left middle cerebral artery opacification and an abnormal pattern of thalamic and posterior fossa structure enhancement. Following a neuroradiology review, it was identified that the contrast bolus had been administered into the right brachial artery causing direct arterial opacification of the right vertebral/carotid arteries and their distal branches. No contrast was present in the left carotids or distal left intracranial anterior circulation giving the false impression of a large vessel occlusion. The patient was subsequently discharged without receiving inappropriate reperfusion therapy. This case highlights the role of technical factors influencing CT interpretation, particularly when performed by artificial intelligence/automated analysis.

Diagnostic performance of CCTA and CTP imaging for clinically suspected in-stent restenosis: A meta-analysis

AimsThe objective of this study is to conduct a meta-analysis to assess the diagnostic performance of Coronary Computed Tomography Angiography (CCTA) and a hybrid approach that incorporates Computed Tomography Perfusion (CTP) in addition to CCTA (CCTA ​+ ​CTP) for the detection of in-stent restenosis (ISR), as defined by angiography. MethodsA comprehensive search of articles identified 18,513 studies. After removing duplicates, title/abstract screening, and full-text review, 17 CCTA and 3 CCTA ​+ ​CTP studies were included. Only studies using ≥64-slices multidetector computed tomography (CT) were considered eligible. ResultsThe per-patient ISR prevalence was 43 ​%, with 92 ​% of stents fully interpretable with CCTA. Meta-analysis exhibited a per-stent CCTA (n ​= ​2674) sensitivity of 90 ​% (95 ​% CI; 84–94 ​%), specificity of 89 ​% (95 ​% CI; 86–92 ​%), positive likelihood ratio of 7.17 (95 ​% CI; 5.24–9.61), negative likelihood ratio of 0.17 (95 ​% CI; 0.10–0.25), and diagnostic odds ratio of 45.7 (95 ​% CI; 22.71–82.43). Additional sensitivity analyses revealed no influence of stent diameter or strut thickness on the diagnostic yield of CCTA. The per-stent diagnostic performance of CCTA ​+ ​CTP (n ​= ​752) did not show differences compared to CCTA. ConclusionsWith currently utilized scanners, CCTA and CCTA ​+ ​CTP demonstrated high diagnostic performance for in-stent restenosis evaluation. Consequently, a history of previous stent implantation should not be an argument to preclude using these methods in clinically suspected patients.

A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata

Acute ischemic stroke (AIS) remains a global health challenge, leading to long-term functional disabilities without timely intervention. Spatio-temporal (4D) Computed Tomography Perfusion (CTP) imaging is crucial for diagnosing and treating AIS due to its ability to rapidly assess the ischemic core and penumbra. Although traditionally used to assess acute tissue status in clinical settings, 4D CTP has also been explored in research for predicting stroke tissue outcomes. However, its potential for predicting functional outcomes, especially in combination with clinical metadata, remains unexplored. Thus, this work aims to develop and evaluate a novel multimodal deep learning model for predicting functional outcomes (specifically, 90-day modified Rankin Scale) in AIS patients by combining 4D CTP and clinical metadata. To achieve this, an intermediate fusion strategy with a cross-attention mechanism is introduced to enable a selective focus on the most relevant features and patterns from both modalities. Evaluated on a dataset comprising 70 AIS patients who underwent endovascular mechanical thrombectomy, the proposed model achieves an accuracy (ACC) of 0.77, outperforming conventional late fusion strategies (ACC = 0.73) and unimodal models based on either 4D CTP (ACC = 0.61) or clinical metadata (ACC = 0.71). The results demonstrate the superior capability of the proposed model to leverage complex inter-modal relationships, emphasizing the value of advanced multimodal fusion techniques for predicting functional stroke outcomes.

CT-perfusion quantitation of cardiac infarct size - a novel technique

Abstract Introduction Cardiac infarct size is associated with cardiac prognosis after AMI. Cardiac CT is able to delineate both coronary anatomy and myocardial pefusion. Thus far, CT identification of infarction has been qualitative. We describe a novel technique for quantitation of myocardial infarct size in CT-perfusion imaging. Methods Patient Population comprised 51 patients that were previously clinically diagnosed with myocardial infarction on the basis of clinical presentation, ECG findings and elevated cardiac enzymes. CTP Imaging All patients had undergone dynamic rest, vasodilator-stress, rest, delayed enhancement CT perfusion imaging performed on a dual-source, third generation scanner (FORCE, Siemens Healthcare). Image Analysis 2 trained investigators independently quantified the infarct volume in 51 patient studies using Siemens SmartSimulator software. Mean ± SD HU were taken from a 1cm² circular ROI of normal myocardium used in a thresholding method. The epicardium and endocardium of infarcted areas were manually contoured from apex to base. Volumetric measurements were obtained of the infarct and total myocardium. Interpolation of contours for segmentation objects was performed. Subtraction of left ventricle cavity from total left ventricle allowed volumetric measurements of total left ventricular myocardium. ROIs of the infarct were estimated using SDs above mean HU of normal myocardium (0.5, 1, 1.5 and 2 SDs) in delayed imaging. Selection of optimal threshold HU was based on visual assessment that best mapped the hyperenhanced infarct area. This allowed volumetric asessment of infarct and total myocardium. Inter-investigator variability was evaluated with Bland-Altman and Intra-Class Correlation Coefficient (ICC). Results Patient characteristics are follow: Age 60.20±11.35 years, 41(89%)male, BMI 25.41±4.17kg/m², Hypertension 23(50%), diabetes 10(22%), hyperlipidemia 40(87%), smoking 7(15%), family history of premature CAD 4(8.7%), previous PCI 45(97.8%). In 51 patients, 23(41%), 24 (46%) &amp; 5(10%) of the infarctions were quantitated as being medium-sized (10%-20%), large (20% -30%) and very large (&amp;gt;30%). Thirty-seven (70%), 6 (11%) &amp; 10(19%) involved the LAD, LCx and RCA territories respectively. 49 (94%) of infarctions were transmural. Identical thresholding was selected by both investigators for each SD above mean (mean 1.42; SD 0.46). 93% of the total cases were within a set threshold of 1 to 2 SDs above the mean HU for both. Interclass correlation coefficient was 0.95, CI range 0.90 – 0.97. Bland-Altman analysis did not demonstrate systemic variations or proportional bias from the plot. Conclusion The study suggests that a method of quantifying cardiac infarct size using a threshold technique and delayed hyperenhancement images with dynamic perfusion imaging is clinically feasible and consistent.Rest-Stress-Delayed Enhancement infarct

CCTA and CTP imaging for detecting clinically suspected in-stent restenosis: a meta-analysis

Abstract Background The evaluation of coronary artery stents via Coronary Computed Tomography Angiography (CCTA) can be compromised by artefacts, potentially undermining its diagnostic accuracy. The integration of CT Perfusion (CTP) with CCTA (CCTA+CTP) has been proposed to enhance the diagnostic yield in detecting in-stent restenosis (ISR). Purpose This meta-analysis aims to assess the diagnostic performance of CCTA and combined CCTA+CTP in detecting ISR. Methods A comprehensive literature search of studies from 2005 to 2022 identified 13,747 articles. Inclusion criteria comprised the utilization of multidetector CT scanners with ≥64 slices and invasive coronary angiography as the reference standard. Studies that systematically evaluated stent patency in asymptomatic patients as part of their protocol were excluded. Results After removing duplicates, screening titles and abstracts, and conducting full-text reviews, 20 studies met the inclusion criteria (17 CCTA, 3 CCTA+CTP). Data on 2,674 CCTA-assessed stents and 752 CCTA+CTP-assessed stents were analyzed. The meta-analysis revealed that CCTA alone achieved a sensitivity of 90% (95% CI; 84-94%) and a specificity of 89% (95% CI; 86-92%)(Figure 1). CCTA+CTP exhibited comparable diagnostic performance, with a per-stent sensitivity of 88% (95% CI; 80-94%) and a specificity of 88% (95% CI; 84-93%) (Figure 2). The summary Receiver Operating Characteristic (sROC) Area Under the Curve (AUC) was 0.96 (95% CI; 0.94-0.97) for CCTA and 0.96 (95% CI; 0.89-1.00) for CCTA+CTP, indicating a high overall performance for both diagnostic modalities. Conclusion Utilizing contemporary imaging hardware, both CCTA and CCTA+CTP demonstrate high diagnostic performance in evaluating ISR. The findings suggest that the presence of coronary artery stents should not preclude the use of these non-invasive diagnostic tests in clinical practice.Figure 1Figure 2

Diagnostic value of routine CT perfusion imaging for radiology residents

To evaluate whether incorporating CT perfusion imaging can significantly enhance diagnostic CT accuracy in stroke detection. Two 3rd-year residents (3rd of 5 years of residency) reviewed CT scans of 200 patients with suspected stroke, consisting of 104 patients with a proven stroke and a control group with 96 patients. They analyzed each patient in a blinded and randomized manner in two runs. In one session, they had only non-contrast CT and CT angiography available for diagnosis; in the other session at a later time point, an additional CT perfusion imaging was available. The performance achieved by the two readers was determined in terms of AUC (area under the curve), accuracy, sensitivity, specificity, positive and negative predictive value and Cohen’s Kappa. Reader 1 achieved an AUC of 87.64% with the basic stroke-protocol vs. an AUC of 97.4% with an additional CT-perfusion given. Based on the DeLong test, these values differ significantly (p-value: 0.00017). Reader 2 achieved an AUC of 91.23% in basic stroke-protocol vs. an AUC of 96.42% with an additional CT-perfusion. These values also differ significantly (p-value: 0.02612).. The performance gain achieved with CT-perfusion is most evident in the decrease in the number of false classified cases (Reader 1: 24 to 5; Reader 2: 18 or 14 to 7) and the significant increase in Cohen’s kappa. Our study shows that additional CT-perfusion imaging in stroke diagnosis significantly improves the diagnostic reliability of residents. Therefore, it should be further investigated whether perfusion imaging should be a general standard of initial stroke diagnosis no matter of the onset.

Relationship between microvascular status and diagnostic performance of stress dynamic CT perfusion imaging.

This study aimed to investigate the relationship between microvascular status in the non-ischemic myocardium and the diagnostic performance of stress dynamic CT perfusion imaging (CTP) in detecting hemodynamically significant stenosis. This study included 157 patients who underwent coronary computed tomography angiography (CTA), CTP, and invasive coronary angiography (ICA), including fractional flow reserve (FFR). Hemodynamically significant stenosis was defined by FFR and ICA. A relative myocardial blood flow (MBF) for each myocardial segment was normalized to the highest MBF (remote MBF) among 16 segments. The receiver operating characteristic curve analysis for detecting hemodynamically significant stenosis at the vessel level indicated that patients with lower, intermediate, and higher remote MBF had areas under the curve (AUC) of 0.66, 0.70, and 0.80, respectively, for absolute MBF and AUCs of 0.63, 0.70, and 0.83, respectively, for relative MBF. The optimal cut-off values for absolute MBF were proportional to the levels of remote MBFs, while the ones for relative MBF were more consistent across lower to higher remote MBFs. For the patients with high remote MBF, the relative MBF demonstrated a sensitivity of 69%, specificity of 88%, and accuracy of 85% in detecting hemodynamically significant stenosis. The microvascular status in the non-ischemic myocardium influenced the diagnostic performance of dynamic CTP and threshold values of absolute MBFs, suggesting the potential preference for relative MBF over absolute MBF in clinical settings. Dynamic CTP's quantification of MBF offers the benefit of indicating reliability in ischemia detection relative to microvascular status. Question The relationship between microvascular status and diagnostic performance of dynamic CTP imaging has not been fully investigated. Findings The diagnostic performance of dynamic CTP and threshold values of absolute MBF were impacted by microvascular status. Clinical relevance The differences in diagnostic accuracy of dynamic CTP related to varying remote MBF values necessitate a personalized evaluation of myocardial perfusion in dynamic CTP images.

Computed tomography perfusion as a predictor of gastric cancer grades

BackgroundGastric cancer stands as one of the most prevalent malignancies globally, conventional endoscopic specimens have been the primary means of diagnosing preoperative gastric histopathology, however, their limitations in capturing intra-tumor heterogeneity compromise their efficacy in evaluating angiogenesis. Perfusion Computed Tomography (P-CT) emerges as a pivotal functional imaging modality, facilitating objective assessment of tissue perfusion, serving as a marker of angiogenesis. So, our research objective was to evaluate the efficacy of CT perfusion imaging in the prediction of histological grades of gastric tumors using quantitative perfusion parameters such as permeability surface (PS), blood flow (BF), mean transient time (MTT), and blood volume (BV), in addition to the qualitative scoring system then comparing the findings with the histopathological results.ResultsPS and BF were statistically significant predictors of the grade of differentiation, their odds ratio (OR) was (1.05, 95% CI 1.02–1.09, for each of them) (P = 0.004, P = 0.009, respectively). MTT also emerged as a significant predictor of the grade of differentiation with an OR of 0.76 (95% CI 0.57–0.93, P = 0.025). Using multivariate logistic regression model, PS was the most potent individual P-CT predictor of differentiation of the grade and the diagnosis of poorly differentiated tumors at ≥ 39 mL/100 g/min cut off point, followed by BF at ≥ 82.2 mL/100 g/min, and MTT at < 8.4 s. Regarding the qualitative scoring system P-CT, poorly differentiated tumors generally received higher scores of PS (P < 0.001), BF (P < 0.001), and BV (P = 0.017), than well and moderately differentiated tumors, however, MTT showed that poorly differentiated tumors were more frequently scored as low compared to well and moderately differentiated tumors (P < 0.001).ConclusionsP-CT is an innovative, non-invasive biomarker for predicting gastric cancer grade by quantitative and qualitative assessment by P-CT parameters (PS, BF and MTT) with particular role of PS as the strongest individual P-CT predictor of differentiation grade followed by BF and MTT at specific cut off points.

CT Perfusion imaging as prognostic factor for outcome of lacunar stroke

BackgroundEarly neurological deterioration (END) affects 20–30% of patients with lacunar stroke within 48 h despite optimal treatment. Previously established markers included infection and infarct location on imaging. We studied the utility of measuring global cerebral blood flow (gCBF) measured by CT-Perfusion (CTP) as an early predictor of END in patients with lacunar strokes.Methods162 patients with lacunar stroke were measured for gCBF including both cerebral hemispheres and cerebellum. We stratified patients by normal gCBF (> 40 ml/100 mg/min) vs. low gCBF (< 40 ml/100 mg/min). Stroke location, vascular risk factors, age and gender were assessed. The primary outcome was the change in the NIHSS score after 48 h from index stroke.ResultsMean gCBF of the overall cohort was 37.72 ml/100 mg/min. Both groups had a baseline NIHSS score of 4.2 with similar standard deviations. The NIHSS score decreased by 1.3 points in normal gCBF group and increased by 1.1 points in the low gCBF group. All stroke sites deteriorated in the low gCBF group, particularly the capsula interna, corona radiata, and lateral pontine area. END occurred in 37.8% in low gCBF compared to 3.1% in the normal gCBF patients. In contrast, clinical improvement after 48 h occurred in 64.2% of patients with normal gCBF but only 6.1% with low gCBF.ConclusionOur study supports measurement of gCBF by CTP as a potential imaging biomarker for END. Additionally, it adds evidence to the body of supporting the vulnerability of capsula interna and pontine infarctions to END.

CT perfusion imaging in aneurysmal subarachnoid hemorrhage. State of the art.

CT perfusion (CTP) images can be easily and rapidly obtained on all modern CT scanners and have become part of the routine imaging protocol of patients with aneurysmal subarachnoid haemorrhage (aSAH). There is a growing body of evidence supporting the use of CTP imaging in these patients, however, there are significant differences in the software packages and methods of analysing CTP. In. addition, no quantitative threshold values for tissue at risk (TAR) have been validated in this patients' population. Here we discuss the contribution of the technique in the identification of patients at risk of aSAH-related delayed cerebral ischemia (DCI) and in the assessment of the response to endovascular rescue therapy (ERT). We also address the limitations and pitfalls of automated CTP postprocessing that are specific to aSAH patients as compared to acute ischemic stroke (AIS).

Utility of automated CT perfusion software in acute ischemic stroke with large and medium vessel occlusion.

Early diagnosis of large vessel occlusion (LVO) in acute stroke often requires CT angiography (CTA). Automated CT perfusion (CTP) software, which identifies blood flow abnormalities, enhances LVO diagnosis and patient selection for endovascular thrombectomy (EVT). This study evaluates the sensitivity of automated CTP images in detecting perfusion abnormalities in patients with acute ischemic stroke (AIS) and LVO or medium vessel occlusion (MeVO), compared to CTA. We screened acute ischemic stroke patients presenting within 24 h who underwent CT, CTA, and CTP as per institutional protocol. RAPID AI software processed CTP images, while neuroradiologists reviewed CTA for intracranial arterial occlusions. Sensitivity, specificity, and accuracy of automated CTP maps in detecting occlusions were assessed. Of 790 screened patients, 31 were excluded due to lack of RAPID CTP data or poor-quality scans, leaving 759 for analysis. The median age was 71 years (IQR: 61-81), with 47% female. Among them, 678 had AIS, and 81 had AIS ruled out. CTA identified arterial occlusion in 562 patients (74%), with corresponding CTP abnormalities in 537 patients (Tmax > 6 sec). In the 197 without occlusion, CTP was negative in 161. Automated CTP maps had a sensitivity of 95.55% (CI 95: 93.50-97.10%), specificity of 81.73% (CI 95: 75.61-86.86%), negative predictive value of 98.22% (CI 95: 97.39-98.79%), positive predictive value of 63.54% (CI 95: 56.46-70.09%), and overall accuracy of 85.18% (CI 95: 82.45-87.64%). Automated CTP maps demonstrated high sensitivity and negative predictive value for LVOs and MeVOs, suggesting their usefulness as a rapid diagnostic tool, especially in settings without expert neuroradiologists.

Deep Learning Denoising Improves CT Perfusion Image Quality in the Setting of Lower Contrast Dosing: A Feasibility Study.

Considering recent iodinated contrast shortages and a focus on reducing waste, developing protocols with lower contrast dosing while maintaining image quality through artificial intelligence is needed. This study compared reduced iodinated contrast media and standard dose CTP acquisitions, and the impact of deep learning denoising on CTP image quality in preclinical and clinical studies. The effect of reduced X-ray mAs dose was also investigated in preclinical studies. Twelve swine underwent 9 CTP examinations each, performed at combinations of 3 different x-ray (37, 67, and 127 mAs) and iodinated contrast media doses (10, 15, and 20 mL). Clinical CTP acquisitions performed before and during the iodinated contrast media shortage and protocol change (from 40 to 30 mL) were retrospectively included. Eleven patients with reduced iodinated contrast media dosages and 11 propensity-score-matched controls with the standard iodinated contrast media dosages were included. A residual encoder-decoder convolutional neural network (RED-CNN) was trained for CTP denoising using k-space-weighted image average filtered CTP images as the target. The standard, RED-CNN-denoised, and k-space-weighted image average noise-filtered images for animal and human studies were compared for quantitative SNR and qualitative image evaluation. The SNR of animal CTP images decreased with reductions in iodinated contrast media and milliampere-second doses. Contrast dose reduction had a greater effect on SNR than milliampere-second reduction. Noise-filtering by k-space-weighted image average and RED-CNN denoising progressively improved the SNR of CTP maps, with RED-CNN resulting in the highest SNR. The SNR of clinical CTP images was generally lower with a reduced iodinated contrast media dose, which was improved by the k-space-weighted image average and RED-CNN denoising (P < .05). Qualitative readings consistently rated RED-CNN denoised CTP as the best quality, followed by k-space-weighted image average and then standard CTP images. Deep learning-denoising can improve image quality for low iodinated contrast media CTP protocols, and could approximate standard iodinated contrast media dose CTP, in addition to potentially improving image quality for low milliampere-second acquisitions.

Baseline Blood Pressure Was Associated with Hemispheric Cerebral Blood Flow in Acute Small Subcortical Infarcts

Introduction: While increased baseline blood pressure (BP) is a prevalent comorbidity in the acute phase of ischemic stroke, the association between baseline BP and the state of hemispheric perfusion in patients with acute small subcortical infarcts (SSIs) has not been studied in detail. The aim of this study was to investigate the relationship between baseline BP and hemispheric cerebral blood flow (CBF) in acute SSIs. Methods: This retrospective study included 101 patients with acute SSIs. Baseline hemispheric CBF was assessed through co-registration of baseline CT perfusion imaging and follow-up diffusion-weighted imaging. The association between baseline BP, CBF, and different cerebral small vessel disease (CSVD) biomarkers was assessed. Results: Baseline systolic BP (SBP) and diastolic BP (DBP) were negatively associated with contralateral hemispheric CBF after multivariate-adjusted linear analysis (SBP: β = −0.001, 95% CI: −0.002 to 0.000, p = 0.030; DBP: β = −0.002, 95% CI: −0.003∼0.001, p = 0.006). Among other CSVD biomarkers, the presence of any cerebral microbleeds showed a significant association with lower CBF in the contralateral hemisphere of the infarct lesion (r = −0.270, p = 0.035). Conclusion: In patients with acute SSIs, increased baseline BP was associated with reduced CBF in the contralateral hemisphere of the infarct lesion, which probably could be interpreted by the exacerbation of the CSVD burden, suggesting a potential mechanistic link between BP autoregulation dysfunction and the aggravation of neurovascular impairment in SSIs.