Elham Tavakkol

In patients with acute ischemic stroke (AIS), robust collaterals are associated with lower rates of infarct growth. Perfusion-based collateral matrices including hypoperfusion intensity ratio (HIR), relative cerebral blood volume index (rCBV-Index), and perfusion collateral index (PCI) have been used successfully to assess collaterals in AIS patients. We aimed to assess and compare the diagnostic ability of these perfusion-based collateral indices in prediction of infarct growth in AIS patients following successful reperfusion. In this retrospective multicenter study, anterior circulation large vessel occlusion patients were included if they had pretreatment perfusion (CT or MR), successful reperfusion (mTICI ≥2b), and follow up MRI within 24-48 hours from the date of treatment. The primary outcome assessed was substantial infarct growth which was defined as final infarct volume of ≥10 mL compared to baseline ischemic core volume. Perfusion-based collateral indices including HIR (volume of Tmax >10 sec/volume of Tmax >6 sec) and rCBV-Index (mean of rCBV values within the volume of Tmax > 6sec) were calculated using RAPID software (iSchemaView, version 5.0.4), and PCI (volume of delay ^2-6sec multiplied by its corresponding mean rCBV) was calculated using Olea software (Olea Medical, SP.23). The association between perfusion-based collateral indices, along with demographic and clinical variables for determination of infarct growth was tested using appropriate univariate analysis. Multivariable logistic regression using a stepwise backward selection approach was performed to identify independent predictors of infarct growth. Among 116 included patients, 58 (50%) had infarct growth ≥10 mL. Infarct growth volume (median, IQR) was: 11, 2.6-34.7 mL. Poor collaterals determined by PCI and rCBV index was significantly (p<0.01) associated with infarct growth while HIR was not (p=0.83). Following multivariate logistic regression, three variables remained as independent predictors of infarct growth: baseline NIHSS (OR=1.10, 95%CI: 1.02-1.15, p=0.005); rCBV-Index (OR=0.005, 95%CI: 0.00-0.14, p=0.002); and PCI (OR=0.99, 95%CI: 0.98-0.99, p=0.01). Perfusion-based collateral indices that integrate CBV (rCBV-Index and PCI) outperformed delay-based HIR in prediction of substantial infarct growth in AIS patients and hence may play an important role in treatment decision-making, patient transfer decisions, and prognostication.

BACKGROUND: In patients with acute ischemic stroke, infarct growth occurs despite successful reperfusion. Oxygen extraction fraction (OEF) has shown promising results in evaluating ischemic tissue viability and can now be quantified from routinely performed dynamic susceptibility contrast perfusion. We aimed to determine the association of OEF alterations within the ischemic tissue on pretreatment magnetic resonance imaging and infarct growth in patients who underwent successful reperfusion. METHODS: In this retrospective cohort study from the University of California, Los Angeles, between 2015 and 2020, patients were included if they had anterior circulation large vessel occlusion, achieved successful reperfusion (Thrombolysis in Cerebral Infarction ≥2b), had pretreatment dynamic susceptibility contrast perfusion and posttreatment magnetic resonance imaging within 48 hours from reperfusion. Dynamic susceptibility contrast-derived OEF values were quantified from the segmented ischemic core (apparent diffusion coefficient ≤620×10 ⁻⁶ mm ² /s) and penumbra tissue (time-to-maximum [Tmax] >6 s) on pretreatment magnetic resonance imaging and normalized to contralateral hemisphere (relative oxygen extraction fraction [OEF _r ]). Primary outcome was substantial infarct growth ≥10 mL, and secondary outcomes were continuous measures of infarct growth volume and penumbra-to-infarct conversion ratio. The associations between baseline clinical and imaging variables, including OEF _r and outcome measures, were tested by multivariate and regression analysis. RESULTS: Among 89 patients who met inclusion criteria, 33 (37%) patients had infarct growth ≥10 mL. Patients with infarct growth had significantly ( P r values compared with those without infarct growth. There was significant association between penumbra OEF _r and infarct growth (β=−2.9 [95% CI, −5.0 to −0.8]; P =0.007) and similarly for penumbra-to-infarct conversion ratio (β=−10.4 [95% CI, −19.6 to −1.2]; P =0.028). CONCLUSIONS: Our results showed penumbra-OEF _r is a promising imaging biomarker for predicting infarct growth in acute ischemic stroke following successful reperfusion. Although elevation of penumbra-OEF _r is protective, patients with lower penumbra-OEF _r values sustained further ischemic injury and infarct growth.

BACKGROUND AND PURPOSE: DWI-FLAIR mismatch is used to determine thrombolytic eligibility in patients with acute ischemic stroke (AIS) when time since stroke onset (TSS) is unknown. Commercial software packages have been developed for automated DWI-FLAIR classification. We aimed to use e-Stroke software (Brainomix, Oxford, UK) for automated classification of DWI-FLAIR mismatch in a cohort of patients with AIS and in a comparative analysis with two expert neuroradiologists. MATERIALS AND METHODS: In this retrospective study, patients with AIS who had MRI and known TSS were included. DWI-FLAIR mismatch was evaluated by two neuroradiologists blinded to TSS and automatically by e-Stroke software. After 4 weeks, the neuroradiologists reevaluated the MRIs, this time equipped with automated predicted e-Stroke results as a computer assisted tool (CAT). Diagnostic performances of e-Stroke software and neuroradiologists were evaluated for prediction of DWI-FLAIR mismatch status. RESULTS: A total of 157 patients met inclusion criteria. A total of 82 patients (52%) had TSS ≤ 4.5 hours. Using consensus reads, 81 patients (51.5%) had DWI-FLAIR mismatch. The diagnostic accuracy (AUC/sensitivity/specificity) of e-Stroke software for determination of DWI-FLAIR mismatch was 0.72/90.0/53.9. The diagnostic accuracy (AUC/sensitivity/specificity) for neuroradiologist 1 and 2 was 0.76/69.1/84.2 and was 0.82/91.4/73.7 respectively, both significantly (p<0.05) improved to 0.83/79.0/86.8 and 0.89/92.6/85.5 respectively following the use of e-Stroke predictions as CAT. The interrater agreement (K) for determination of DWI-FLAIR status was improved from 0.49 to 0.57 following the use of CAT. CONCLUSIONS: Automated quantitative approach for DWI-FLAIR mismatch provides comparable results to human experts and can improve diagnostic accuracies of expert neuroradiologists in determination of DWI-FLAIR status. ABBREVIATIONS: AIS: Acute ischemic stroke; CAT: Computer assisted tool; TSS: Time since stroke onset

BACKGROUND AND PURPOSE: Perfusion-based collateral indices such as the perfusion collateral index and the hypoperfusion intensity ratio have shown promise in the assessment of collaterals in patients with acute ischemic stroke. We aimed to compare the diagnostic performance of the perfusion collateral index and the hypoperfusion intensity ratio in collateral assessment compared with angiographic collaterals and outcome measures, including final infarct volume, infarct growth, and functional independence. MATERIALS AND METHODS: Consecutive patients with acute ischemic stroke with anterior circulation proximal arterial occlusion who underwent endovascular thrombectomy and had pre- and posttreatment MRI were included. Using pretreatment MR perfusion, we calculated the perfusion collateral index and the hypoperfusion intensity ratio for each patient. The angiographic collaterals obtained from DSA were dichotomized to sufficient (American Society of Interventional and Therapeutic Neuroradiology [ASITN] scale 3–4) versus insufficient (ASITN scale 0–2). The association of collateral status determined by the perfusion collateral index and the hypoperfusion intensity ratio was assessed against angiographic collaterals and outcome measures. RESULTS: A total of 98 patients met the inclusion criteria. Perfusion collateral index values were significantly higher in patients with sufficient angiographic collaterals (P < .001), while there was no significant (P = .46) difference in hypoperfusion intensity ratio values. Among patients with good (mRS 0–2) versus poor (mRS 3–6) functional outcome, the perfusion collateral index of ≥ 62 was present in 72% versus 31% (P = .003), while the hypoperfusion intensity ratio of ≤0.4 was present in 69% versus 56% (P = .52). The perfusion collateral index and the hypoperfusion intensity ratio were both significantly predictive of final infarct volume, but only the perfusion collateral index was significantly (P = .03) associated with infarct growth. CONCLUSIONS: Results show that the perfusion collateral index outperforms the hypoperfusion intensity ratio in the assessment of collateral status, infarct growth, and determination of functional outcomes.

Background: Breast cancer mainly affects women aged >50 years; however, younger women may also have advanced breast cancer, so early detection is important. Purpose: To collect and review the imaging findings of women aged <30 years with breast cancer to find better diagnostic approaches for the early diagnosis of breast cancer in young women. Material and Methods: In this study, 45 patients aged <30 years with a diagnosis of breast cancer were evaluated. Imaging assessments were performed based on ultrasound, mammography, and magnetic resonance imaging (MRI) findings. Finally, the findings were compared with the pathological results. Results: Predominant findings in ultrasound included irregular spiculated mass in 59.4%. In mammography, irregular high-density mass (46.5%) and suspicious micro calcification (42.8%) were the most common findings. In MRI, the predominant feature was a heterogeneous enhancing mass with an irregular shape and irregular margin (81%) with a 45% plateau and 36% washout kinetic pattern. In the pathology assessment, invasive ductal carcinoma was the most common finding (84.4%). All three modalities—MRI, ultrasonography, and mammography—are valuable, with sensitivities of 100%, 93.3%, and 90%, respectively. Conclusion: Ultrasound, mammography, and MRI are highly sensitive and accurate tools for detecting breast cancer lesions in young women. Regular clinical breast examination with breast self-examination, and in suspected cases, ultrasound as the first imaging modality followed by mammography and/or MRI are the preferred diagnostic approach.

Objectives. This study assessed the quality of endodontic treatment and the prevalence of procedural errors in permanent mandibular molars using cone-beam computed tomography (CBCT). Materials and Methods. This cross-sectional study was conducted on 328 CBCT scans (182 females and 146 males) of endodontically treated mandibular molars retrieved from the archives of two radiology centers in Ardabil city, Iran, in 2019. Mandibular molars were evaluated on sagittal, coronal, and axial sections regarding obturation length, obturation density (voids), missed canals, broken instruments, apical perforation, strip perforation, ledge formation, transportation, root fracture, root resorption, and periapical lesions by a senior dental student under the supervision of an oral and maxillofacial radiologist and an endodontist. Differences between the frequency of procedural errors and tooth type and gender were analyzed by the chi-square test. Results. The frequency of underfilling, missed canals, overfilling, voids, apical perforation, transportation, ledge formation, broken instruments, root fracture, strip perforation, root resorption, and periapical lesions was 34.8%, 17.4%, 16.8%, 14.3%, 7.3%, 6.1%, 4.3%, 3%, 1.2%, 0.6%, 5.5%, and 46%, respectively. The frequency of root fracture was significantly higher in females than in males . The prevalence of underfilling was the highest in right second molars (47.2%), followed by right first molars, left second molars, and left first molars . The frequency of transportation was maximum in right first molars (10%), followed by right second molars, left first molars, and left second molars . Conclusion. Underfilling, missed canals, and overfilling were the most prevalent procedural errors in mandibular molars in our study population.

A range of procedural errors can occur when performing endodontic treatment on posterior teeth. These errors may decrease the success rate in endodontic practice. This study assessed the prevalence of procedural errors and the quality of endodontic treatments in maxillary molars and premolars using cone‐beam computed tomography (CBCT). CBCT scans from two private radiology centers were assessed retrospectively to ensure the same calculated sample size of 327 teeth for each of the four maxillary posterior tooth types (a total of 1,308 endodontically treated teeth). Image sets were evaluated for procedural errors categorized as follows: obturation length (overfilling or underfilling by >2 mm short of the root apex), missed canals, perforations, strip perforations (with extrusion of material into the furcation area), separated instruments in the root canal space, and root fracture. Data were analyzed with SPSS version 20 (SPSS Inc., Chicago, IL, USA), and frequency data was assessed using the Monte Carlo test at the 0.05 level of significance. The procedural errors most commonly reported in the present study were from most frequent to least frequent: underfilled canals (50.0%), missed canals (27.5%), overfilled canals (12.5%), apical perforations (5.0%), separated instruments (3.1%), and root fractures (1.9%). No strip perforations (with extrusion of material into the furcation area) were seen in the study (0%). Underfilled and missed root canals were the most frequent procedural errors identified in the present study. These findings underline the importance of more consideration of critical working length management during all stages of root canal treatment, greater awareness of root canal anatomy, and the use of imaging and diagnostic devices that enhance the ability to identify and treat root canals both safely and effectively.