Prognostic imaging variables for recurrent laryngeal and hypopharyngeal carcinoma treated with primary chemoradiotherapy: A systematic and meta-analysis

Background: In this systematic review, we aim to identify prognostic imaging variables of recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy. Methods: A systematic search was performed in PubMed and EMBASE (1990–2020). The crude data and effect estimates were extracted for each imaging variable. The level of evidence of each variable was assessed and pooled risk ratios (RRs) were calculated. Results: Twenty-two articles were included in this review, 17 on computed tomography (CT) and 5 on magnetic resonance imaging (MRI) variables. We found strong evidence for the prognostic value of tumor volume at various cut-off points (pooled RRs ranging from 2.09 to 3.03). Anterior commissure involvement (pooled RR 2.19), posterior commissure involvement (pooled RR 2.44), subglottic extension (pooled RR 2.25), and arytenoid cartilage extension (pooled RR 2.10) were also strong prognostic factors. Conclusion: Pretreatment tumor volume and involvement of several subsites are prognostic factors for recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy

Image Quality of Virtual Monochromatic Reconstructions of Noncontrast CT on a Dual-Source CT Scanner in Adult Patients

Rationale and Objectives To evaluate the image quality of virtual monochromatic images (VMI) reconstructed from dual-energy dual-source noncontrast head CT with different reconstruction kernels. Materials and Methods Twenty-five consecutive adult patients underwent noncontrast dual-energy CT. VMI were retrospectively reconstructed at 5-keV increments from 40 to 140 keV using quantitative and head kernels. CT-number, noise levels (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in the gray and white matter and artifacts using the posterior fossa artifact index (PFAI) were evaluated. Results CT-number increased with decreasing VMI energy levels, and SD was lowest at 85 keV. SNR was maximized at 80 keV and 85 keV for the head and quantitative kernels, respectively. CNR was maximum at 40 keV; PFAI was lowest at 90 (head kernel) and 100 (quantitative kernel) keV. Optimal VMI image quality was significantly better than conventional CT. Conclusion Optimal image quality of VMI energies can improve brain parenchymal image quality compared to conventional CT but are reconstruction kernel dependent and depend on indication for performing noncontrast CT

Non-contrast dual-energy CT virtual ischemia maps accurately estimate ischemic core size in large-vessel occlusive stroke

Dual-energy CT (DECT) material decomposition techniques may better detect edema within cerebral infarcts than conventional non-contrast CT (NCCT). This study compared if Virtual Ischemia Maps (VIM) derived from non-contrast DECT of patients with acute ischemic stroke due to large-vessel occlusion (AIS-LVO) are superior to NCCT for ischemic core estimation, compared against reference-standard DWI-MRI. Only patients whose baseline ischemic core was most likely to remain stable on follow-up MRI were included, defined as those with excellent post-thrombectomy revascularization or no perfusion mismatch. Twenty-four consecutive AIS-LVO patients with baseline non-contrast DECT, CT perfusion (CTP), and DWI-MRI were analyzed. The primary outcome measure was agreement between volumetric manually segmented VIM, NCCT, and automatically segmented CTP estimates of the ischemic core relative to manually segmented DWI volumes. Volume agreement was assessed using Bland–Altman plots and comparison of CT to DWI volume ratios. DWI volumes were better approximated by VIM than NCCT (VIM/DWI ratio 0.68 ± 0.35 vs. NCCT/DWI ratio 0.34 ± 0.35; P < 0.001) or CTP (CTP/DWI ratio 0.45 ± 0.67; P < 0.001), and VIM best correlated with DWI (r VIM = 0.90; r NCCT = 0.75; r CTP = 0.77; P < 0.001). Bland–Altman analyses indicated significantly greater agreement between DWI and VIM than NCCT core volumes (mean bias 0.60 [95%AI 0.39–0.82] vs. 0.20 [95%AI 0.11–0.30]). We conclude that DECT VIM estimates the ischemic core in AIS-LVO patients more accurately than NCCT

Virtual monochromatic dual-energy CT reconstructions improve detection of cerebral infarct in patients with suspicion of stroke

Purpose: Early infarcts are hard to diagnose on non-contrast head CT. Dual-energy CT (DECT) may potentially increase infarct differentiation. The optimal DECT settings for differentiation were identified and evaluated. Methods: One hundred and twenty-five consecutive patients who presented with suspected acute ischemic stroke (AIS) and underwent non-contrast DECT and subsequent DWI were retrospectively identified. The DWI was used as reference standard. First, virtual monochromatic images (VMI) of 25 patients were reconstructed from 40 to 140 keV and scored by two readers for acute infarct. Sensitivity, specificity, positive, and negative predictive values for infarct detection were compared and a subset of VMI energies were selected. Next, for a separate larger cohort of 100 suspected AIS patients, conventional non-contrast CT (NCT) and selected VMI were scored by two readers for the presence and location of infarct. The same statistics for infarct detection were calculated. Infarct location match was compared per vascular territory. Subgroup analyses were dichotomized by time from last-seen-well to CT imaging. Results: A total of 80–90 keV VMI were marginally more sensitive (36.3–37.3%) than NCT (32.4%; p > 0.680), with marginally higher specificity (92.2–94.4 vs 91.1%; p > 0.509) for infarct detection. Location match was superior for VMI compared with NCT (28.7–27.4 vs 19.5%; p < 0.010). Within 4.5 h from last-seen-well, 80 keV VMI more accurately detected infarct (58.0 vs 54.0%) and localized infarcts (27.1 vs 11.9%; p = 0.004) than NCT, whereas after 4.5 h, 90 keV VMI was more accurate (69.3 vs 66.3%). Conclusion: Non-contrast 80–90 keV VMI best differentiates normal from infarcted brain parenchyma

Detection of Cardioembolic Sources With Nongated Cardiac Computed Tomography Angiography in Acute Stroke: Results From the ENCLOSE Study

BACKGROUND: Identifying cardioembolic sources in patients with acute ischemic stroke is important for the choice of secondary prevention strategies. We prospectively investigated the yield of admission (spectral) nongated cardiac computed tomography angiography (CTA) to detect cardioembolic sources in stroke. METHODS: Participants of the ENCLOSE study (Improved Prediction of Recurrent Stroke and Detection of Small Volume Stroke) with transient ischemic attack or acute ischemic stroke with assessable nongated head-to-heart CTA at the University Medical Center Utrecht were included between June 2017 and March 2022. The presence of cardiac thrombus on cardiac CTA was based on a Likert scale and dichotomized into certainly or probably absent versus possibly, probably, or certainly present. The diagnostic certainty of cardiac thrombus was evaluated again on spectral computed tomography reconstructions. The likelihood of a cardioembolic source was determined post hoc by an expert panel in patients with cardiac thrombus on CTA. Parametric and nonparametric tests were used to compare the outcome groups. RESULTS: Forty four (12%) of 370 included patients had a cardiac thrombus on admission CTA: 35 (9%) in the left atrial appendage and 14 (4%) in the left ventricle. Patients with cardiac thrombus had more severe strokes (median National Institutes of Health Stroke Scale score, 10 versus 4; P=0.006), had higher clot burden (median clot burden score, 9 versus 10; P=0.004), and underwent endovascular treatment more often (43% versus 20%; P<0.001) than patients without cardiac thrombus. Left atrial appendage thrombus was present in 28% and 6% of the patients with and without atrial fibrillation, respectively ( P<0.001). The diagnostic certainty for left atrial appendage thrombus was higher for spectral iodine maps compared with the conventional CTA ( P<0.001). The presence of cardiac thrombus on CTA increased the likelihood of a cardioembolic source according to the expert panel ( P<0.001). CONCLUSIONS: Extending the stroke CTA to cover the heart increases the chance of detecting cardiac thrombi and helps to identify cardioembolic sources in the acute stage of ischemic stroke with more certainty. Spectral iodine maps provide additional value for detecting left atrial appendage thrombus. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT04019483

Advanced CT imaging in acute ischemic stroke

Acute ischemic stroke is one of the most prevalent causes of death and disability in the world. Patients with suspected stroke or transient ischemic attack usually undergo computed tomography (CT) imaging in the acute phase, including non-contrast CT, CT perfusion (CTP) and CT angiography (CTA). The aim of this thesis was to improve diagnostic (part 1) and prognostic (part 2) aspects of stroke care with advanced (dual-energy) CT imaging techniques. First, we demonstrated that a technique called CTA derived virtual non-contrast CT is non-inferior to conventional non-contrast CT for the detection of early signs of brain infarction. Second, we identified pitfalls of automated post-processing CTP images, which can lead to wrong treatment decisions. Third, we showed that the concordance between collateral circulation assessments on CT and invasive digital subtraction angiography (DSA) was poor, and that collateral circulation evaluated on CTP-derived CTA, but not on standard single-phase CTA or DSA, was predictive of functional outcome after ischemic stroke. Fourth, we found that extending the (dual-energy) CTA to cover the heart (head-to heart) increases the chance of detecting cardiac thrombi and helps to identify cardioembolic sources in the acute stage of ischemic stroke. Fifth, we found that the pattern of intracranial vessel wall calcifications has prognostic value for the outcome after intravenous thrombolysis. Sixth, we showed that the ratio between cerebrospinal fluid volume and intracranial volume is an important predictor of malignant edema. Last, predictors of recurrent ischemic stroke were systematically reviewed in the literature and we identified additional imaging predictors of recurrent ischemic stroke in a cohort study. In conclusion, this thesis showed that advanced (dual-energy) CT imaging techniques have diagnostic and prognostic value in patients with acute ischemic stroke

Prediction of long-term recurrent ischemic stroke: the added value of non-contrast CT, CT perfusion, and CT angiography

Purpose: The aim of this study was to evaluate whether the addition of brain CT imaging data to a model incorporating clinical risk factors improves prediction of ischemic stroke recurrence over 5 years of follow-up. Methods: A total of 638 patients with ischemic stroke from three centers were selected from the Dutch acute stroke study (DUST). CT-derived candidate predictors included findings on non-contrast CT, CT perfusion, and CT angiography. Five-year follow-up data were extracted from medical records. We developed a multivariable Cox regression model containing clinical predictors and an extended model including CT-derived predictors by applying backward elimination. We calculated net reclassification improvement and integrated discrimination improvement indices. Discrimination was evaluated with the optimism-corrected c-statistic and calibration with a calibration plot. Results: During 5 years of follow-up, 56 patients (9%) had a recurrence. The c-statistic of the clinical model, which contained male sex, history of hyperlipidemia, and history of stroke or transient ischemic attack, was 0.61. Compared with the clinical model, the extended model, which contained previous cerebral infarcts on non-contrast CT and Alberta Stroke Program Early CT score greater than 7 on mean transit time maps derived from CT perfusion, had higher discriminative performance (c-statistic 0.65, P = 0.01). Inclusion of these CT variables led to a significant improvement in reclassification measures, by using the net reclassification improvement and integrated discrimination improvement indices. Conclusion: Data from CT imaging significantly improved the discriminatory performance and reclassification in predicting ischemic stroke recurrence beyond a model incorporating clinical risk factors only