Quantitative pupillometry and radiographic markers of intracranial midline shift: A pilot study

BackgroundAsymmetric pupil reactivity or size can be early clinical indicators of midbrain compression due to supratentorial ischemic stroke or primary intraparenchymal hemorrhage (IPH). Radiographic midline shift is associated with worse functional outcomes and life-saving interventions. Better understanding of quantitative pupil characteristics would be a non–invasive, safe, and cost-effective way to improve identification of life-threatening mass effect and resource utilization of emergent radiographic imaging. We aimed to better characterize the association between midline shift at various anatomic levels and quantitative pupil characteristics.MethodsWe conducted a multicenter retrospective study of brain CT images within 75 min of a quantitative pupil observation from patients admitted to Neuro-ICUs between 2016 and 2020 with large (>1/3 of the middle cerebral artery territory) acute supratentorial ischemic stroke or primary IPH > 30 mm3. For each image, we measured midline shift at the septum pellucidum (MLS-SP), pineal gland shift (PGS), the ratio of the ipsilateral to contralateral midbrain width (IMW/CMW), and other exploratory markers of radiographic shift/compression. Pupil reactivity was measured using an automated infrared pupillometer (NeurOptics®, Inc.), specifically the proprietary algorithm for Neurological Pupil Index® (NPi). We used rank-normalization and linear mixed-effects models, stratified by diagnosis and hemorrhagic conversion, to test associations of radiographic markers of shift and asymmetric pupil reactivity (Diff NPi), adjusting for age, lesion volume, Glasgow Coma Scale, and osmotic medications.ResultsOf 53 patients with 74 CT images, 26 (49.1%) were female, and median age was 67 years. MLS-SP and PGS were greater in patients with IPH, compared to patients with ischemic stroke (6.2 v. 4.0 mm, 5.6 v. 3.4 mm, respectively). We found no significant associations between pupil reactivity and the radiographic markers of shift when adjusting for confounders. However, we found potentially relevant relationships between MLS-SP and Diff NPi in our IPH cohort (β = 0.11, SE 0.04, P = 0.01), and PGS and Diff NPi in the ischemic stroke cohort (β = 0.16, SE 0.09, P = 0.07).ConclusionWe found the relationship between midline shift and asymmetric pupil reactivity may differ between IPH and ischemic stroke. Our study may serve as necessary preliminary data to guide further prospective investigation into how clinical manifestations of radiographic midline shift differ by diagnosis and proximity to the midbrain

The predictive value of the preoperative diagnostic tests in mature cystic teratomas of the ovary

Aim: The aim of this study was to determine the sensitivity of the tumor markers and diagnostic methods used in the preoperative period for dermoid cysts, the most common benign neoplasm of the ovary. Material and Methods: 136 patients who were operated for any reason and reported as ovarian dermoid cyst in the Department of Obstetrics and Gynecology, Ankara Atatürk Training and Research Hospital between January 2004 and September 2005 were included in the study. The medical records of the cases were obtained retrospectively from Ankara-Atatürk Training and Research Hospital, HIS, archive files and patient numbers where necessary. Results: In the preoperative period, 119 patients underwent ultrasonographic examination, 33 underwent Computed Tomography, and 17 underwent Magnetic Resonance Imaging.10 of the cases only underwent CT, while 3 of the cases underwent only MRI 22 of them underwent both USG and CT, USG and MRI were performed on 13 cases and only 1 case underwent all three of the imaging methods. Tumor markers were CEA, CA 125, CA 19-9, CA 15-3 and AFP. Conclusions: The reviews of ultrasonography and / or computed tomography and / or magnetic resonance imaging (n = 132) revealed that 103 of the cases were put into operation and the sensitivity of the preoperative screening methods were calculated to be 75.5%. The sensitivity of the tumor marker CA 19-9 was calculated to be 31%

Abstract 1122‐000089: Characterization of Critical Sequelae in Ischemic Stroke Using Natural Language Processing

Introduction: Automated processing of electronic health data to classify complications of ischemic stroke serves numerous purposes, including improved electronic phenotyping for clinical research. Here, we present a natural language processing (NLP) approach to identify critical findings in acute ischemic stroke from unstructured radiology reports of computed tomography (CT) and magnetic resonance imaging (MRI). Methods: Text reports of CT and MRI scans taken from 2292 patients admitted for large (>1/2 middle cerebral artery territory), acute anterior circulation ischemic stroke were gathered from a single‐institution retrospective cohort. Reports were reviewed and labelled for the presence of hemorrhagic conversion, intracerebral edema, midline shift, intraventricular hemorrhage and parenchymal hematoma as defined by European Cooperative Acute Stroke Study PH1 and PH2 categories. For binary classifications, we quantified co‐occurrence of individual words within reports using two separate NLP methods: Bag‐of‐Words (BOW) and Term Frequency‐Inverse Document Frequency (TF‐IDF). We then trained Lasso regression, random forest, and neural network classifiers to predict all complications based on word co‐occurrence. Classifier performance was measured by area under receiver operating characteristic curves (AUC) using five separate folds of an internal test dataset. To predict midline shift as a continuous outcome, we developed a semantic rule‐based system (RBS) based on regular radiographic report expressions. This system was tested using an external validation dataset of 1472 acute large anterior circulation stroke reports from a separate hospital. Results: 2292 reports were fully labelled for the presence of all stroke complications. Lasso regression consistently displayed the best discrimination among all models. For BOW and TF‐IDF, Lasso yielded respective AUCs of 0.894 and 0.919 (hemorrhagic conversion), 0.935 and 0.950 (intracerebral edema), 0.968 and 0.963 (midline shift), 0.933 and 0.904 (intraventricular hemorrhage), and 0.873 and 0.879 (parenchymal hematoma). All models were well‐calibrated to underlying complication rates. The RBS also achieved strong performance in quantifying midline shift, achieving a mean absolute error (MAE) of 0.103 mm, sensitivity of 99.1% and specificity of 97.5% in the original cohort. In the external validation set of 1472 additional stroke reports, this same system achieved a MAE of 0.126 mm, sensitivity of 99.5% and specificity of 97.5% for midline shift. Wilcoxon rank sum testing on bootstrapped samples confirmed no statistically‐significant differences in RBS performance between institutions when comparing MAE (p = 0.918), sensitivity (p = 0.152), and specificity (p = 0.929). Conclusions: A machine learning pipeline based on Lasso regression successfully identified critical complications of large anterior circulation ischemic stroke from unstructured radiology reports, while our RBS quantified midline shift with a high degree of generalized accuracy between different institutions. We propose that these systems may warrant prospective validation in care settings and data mining for stroke research

Machine learning and natural language processing methods to identify ischemic stroke, acuity and location from radiology reports.

Accurate, automated extraction of clinical stroke information from unstructured text has several important applications. ICD-9/10 codes can misclassify ischemic stroke events and do not distinguish acuity or location. Expeditious, accurate data extraction could provide considerable improvement in identifying stroke in large datasets, triaging critical clinical reports, and quality improvement efforts. In this study, we developed and report a comprehensive framework studying the performance of simple and complex stroke-specific Natural Language Processing (NLP) and Machine Learning (ML) methods to determine presence, location, and acuity of ischemic stroke from radiographic text. We collected 60,564 Computed Tomography and Magnetic Resonance Imaging Radiology reports from 17,864 patients from two large academic medical centers. We used standard techniques to featurize unstructured text and developed neurovascular specific word GloVe embeddings. We trained various binary classification algorithms to identify stroke presence, location, and acuity using 75% of 1,359 expert-labeled reports. We validated our methods internally on the remaining 25% of reports and externally on 500 radiology reports from an entirely separate academic institution. In our internal population, GloVe word embeddings paired with deep learning (Recurrent Neural Networks) had the best discrimination of all methods for our three tasks (AUCs of 0.96, 0.98, 0.93 respectively). Simpler NLP approaches (Bag of Words) performed best with interpretable algorithms (Logistic Regression) for identifying ischemic stroke (AUC of 0.95), MCA location (AUC 0.96), and acuity (AUC of 0.90). Similarly, GloVe and Recurrent Neural Networks (AUC 0.92, 0.89, 0.93) generalized better in our external test set than BOW and Logistic Regression for stroke presence, location and acuity, respectively (AUC 0.89, 0.86, 0.80). Our study demonstrates a comprehensive assessment of NLP techniques for unstructured radiographic text. Our findings are suggestive that NLP/ML methods can be used to discriminate stroke features from large data cohorts for both clinical and research-related investigations

Natural language processing of radiology reports to detect complications of ischemic stroke

Background Abstraction of critical data from unstructured radiologic reports using natural language processing (NLP) is a powerful tool to automate the detection of important clinical features and enhance research efforts. We present a set of NLP approaches to identify critical findings in patients with acute ischemic stroke from radiology reports of computed tomography (CT) and magnetic resonance imaging (MRI). Methods We trained machine learning classifiers to identify categorical outcomes of edema, midline shift (MLS), hemorrhagic transformation, and parenchymal hematoma, as well as rule-based systems (RBS) to identify intraventricular hemorrhage (IVH) and continuous MLS measurements within CT/MRI reports. Using a derivation cohort of 2289 reports from 550 individuals with acute middle cerebral artery territory ischemic strokes, we externally validated our models on reports from a separate institution as well as from patients with ischemic strokes in any vascular territory. Results In all data sets, a deep neural network with pretrained biomedical word embeddings (BioClinicalBERT) achieved the highest discrimination performance for binary prediction of edema (area under precision recall curve [AUPRC] > 0.94), MLS (AUPRC > 0.98), hemorrhagic conversion (AUPRC > 0.89), and parenchymal hematoma (AUPRC > 0.76). BioClinicalBERT outperformed lasso regression (p  Conclusions Our study demonstrates robust performance and external validity of a core NLP tool kit for identifying both categorical and continuous outcomes of ischemic stroke from unstructured radiographic text data. Medically tailored NLP methods have multiple important big data applications, including scalable electronic phenotyping, augmentation of clinical risk prediction models, and facilitation of automatic alert systems in the hospital setting

Table_8_Quantitative pupillometry and radiographic markers of intracranial midline shift: A pilot study.docx

BackgroundAsymmetric pupil reactivity or size can be early clinical indicators of midbrain compression due to supratentorial ischemic stroke or primary intraparenchymal hemorrhage (IPH). Radiographic midline shift is associated with worse functional outcomes and life-saving interventions. Better understanding of quantitative pupil characteristics would be a non–invasive, safe, and cost-effective way to improve identification of life-threatening mass effect and resource utilization of emergent radiographic imaging. We aimed to better characterize the association between midline shift at various anatomic levels and quantitative pupil characteristics.MethodsWe conducted a multicenter retrospective study of brain CT images within 75 min of a quantitative pupil observation from patients admitted to Neuro-ICUs between 2016 and 2020 with large (>1/3 of the middle cerebral artery territory) acute supratentorial ischemic stroke or primary IPH > 30 mm3. For each image, we measured midline shift at the septum pellucidum (MLS-SP), pineal gland shift (PGS), the ratio of the ipsilateral to contralateral midbrain width (IMW/CMW), and other exploratory markers of radiographic shift/compression. Pupil reactivity was measured using an automated infrared pupillometer (NeurOptics®, Inc.), specifically the proprietary algorithm for Neurological Pupil Index® (NPi). We used rank-normalization and linear mixed-effects models, stratified by diagnosis and hemorrhagic conversion, to test associations of radiographic markers of shift and asymmetric pupil reactivity (Diff NPi), adjusting for age, lesion volume, Glasgow Coma Scale, and osmotic medications.ResultsOf 53 patients with 74 CT images, 26 (49.1%) were female, and median age was 67 years. MLS-SP and PGS were greater in patients with IPH, compared to patients with ischemic stroke (6.2 v. 4.0 mm, 5.6 v. 3.4 mm, respectively). We found no significant associations between pupil reactivity and the radiographic markers of shift when adjusting for confounders. However, we found potentially relevant relationships between MLS-SP and Diff NPi in our IPH cohort (β = 0.11, SE 0.04, P = 0.01), and PGS and Diff NPi in the ischemic stroke cohort (β = 0.16, SE 0.09, P = 0.07).ConclusionWe found the relationship between midline shift and asymmetric pupil reactivity may differ between IPH and ischemic stroke. Our study may serve as necessary preliminary data to guide further prospective investigation into how clinical manifestations of radiographic midline shift differ by diagnosis and proximity to the midbrain.</p

Table_3_Quantitative pupillometry and radiographic markers of intracranial midline shift: A pilot study.docx

BackgroundAsymmetric pupil reactivity or size can be early clinical indicators of midbrain compression due to supratentorial ischemic stroke or primary intraparenchymal hemorrhage (IPH). Radiographic midline shift is associated with worse functional outcomes and life-saving interventions. Better understanding of quantitative pupil characteristics would be a non–invasive, safe, and cost-effective way to improve identification of life-threatening mass effect and resource utilization of emergent radiographic imaging. We aimed to better characterize the association between midline shift at various anatomic levels and quantitative pupil characteristics.MethodsWe conducted a multicenter retrospective study of brain CT images within 75 min of a quantitative pupil observation from patients admitted to Neuro-ICUs between 2016 and 2020 with large (>1/3 of the middle cerebral artery territory) acute supratentorial ischemic stroke or primary IPH > 30 mm3. For each image, we measured midline shift at the septum pellucidum (MLS-SP), pineal gland shift (PGS), the ratio of the ipsilateral to contralateral midbrain width (IMW/CMW), and other exploratory markers of radiographic shift/compression. Pupil reactivity was measured using an automated infrared pupillometer (NeurOptics®, Inc.), specifically the proprietary algorithm for Neurological Pupil Index® (NPi). We used rank-normalization and linear mixed-effects models, stratified by diagnosis and hemorrhagic conversion, to test associations of radiographic markers of shift and asymmetric pupil reactivity (Diff NPi), adjusting for age, lesion volume, Glasgow Coma Scale, and osmotic medications.ResultsOf 53 patients with 74 CT images, 26 (49.1%) were female, and median age was 67 years. MLS-SP and PGS were greater in patients with IPH, compared to patients with ischemic stroke (6.2 v. 4.0 mm, 5.6 v. 3.4 mm, respectively). We found no significant associations between pupil reactivity and the radiographic markers of shift when adjusting for confounders. However, we found potentially relevant relationships between MLS-SP and Diff NPi in our IPH cohort (β = 0.11, SE 0.04, P = 0.01), and PGS and Diff NPi in the ischemic stroke cohort (β = 0.16, SE 0.09, P = 0.07).ConclusionWe found the relationship between midline shift and asymmetric pupil reactivity may differ between IPH and ischemic stroke. Our study may serve as necessary preliminary data to guide further prospective investigation into how clinical manifestations of radiographic midline shift differ by diagnosis and proximity to the midbrain.</p

Table_9_Quantitative pupillometry and radiographic markers of intracranial midline shift: A pilot study.docx

BackgroundAsymmetric pupil reactivity or size can be early clinical indicators of midbrain compression due to supratentorial ischemic stroke or primary intraparenchymal hemorrhage (IPH). Radiographic midline shift is associated with worse functional outcomes and life-saving interventions. Better understanding of quantitative pupil characteristics would be a non–invasive, safe, and cost-effective way to improve identification of life-threatening mass effect and resource utilization of emergent radiographic imaging. We aimed to better characterize the association between midline shift at various anatomic levels and quantitative pupil characteristics.MethodsWe conducted a multicenter retrospective study of brain CT images within 75 min of a quantitative pupil observation from patients admitted to Neuro-ICUs between 2016 and 2020 with large (>1/3 of the middle cerebral artery territory) acute supratentorial ischemic stroke or primary IPH > 30 mm3. For each image, we measured midline shift at the septum pellucidum (MLS-SP), pineal gland shift (PGS), the ratio of the ipsilateral to contralateral midbrain width (IMW/CMW), and other exploratory markers of radiographic shift/compression. Pupil reactivity was measured using an automated infrared pupillometer (NeurOptics®, Inc.), specifically the proprietary algorithm for Neurological Pupil Index® (NPi). We used rank-normalization and linear mixed-effects models, stratified by diagnosis and hemorrhagic conversion, to test associations of radiographic markers of shift and asymmetric pupil reactivity (Diff NPi), adjusting for age, lesion volume, Glasgow Coma Scale, and osmotic medications.ResultsOf 53 patients with 74 CT images, 26 (49.1%) were female, and median age was 67 years. MLS-SP and PGS were greater in patients with IPH, compared to patients with ischemic stroke (6.2 v. 4.0 mm, 5.6 v. 3.4 mm, respectively). We found no significant associations between pupil reactivity and the radiographic markers of shift when adjusting for confounders. However, we found potentially relevant relationships between MLS-SP and Diff NPi in our IPH cohort (β = 0.11, SE 0.04, P = 0.01), and PGS and Diff NPi in the ischemic stroke cohort (β = 0.16, SE 0.09, P = 0.07).ConclusionWe found the relationship between midline shift and asymmetric pupil reactivity may differ between IPH and ischemic stroke. Our study may serve as necessary preliminary data to guide further prospective investigation into how clinical manifestations of radiographic midline shift differ by diagnosis and proximity to the midbrain.</p

Table_1_Quantitative pupillometry and radiographic markers of intracranial midline shift: A pilot study.docx

BackgroundAsymmetric pupil reactivity or size can be early clinical indicators of midbrain compression due to supratentorial ischemic stroke or primary intraparenchymal hemorrhage (IPH). Radiographic midline shift is associated with worse functional outcomes and life-saving interventions. Better understanding of quantitative pupil characteristics would be a non–invasive, safe, and cost-effective way to improve identification of life-threatening mass effect and resource utilization of emergent radiographic imaging. We aimed to better characterize the association between midline shift at various anatomic levels and quantitative pupil characteristics.MethodsWe conducted a multicenter retrospective study of brain CT images within 75 min of a quantitative pupil observation from patients admitted to Neuro-ICUs between 2016 and 2020 with large (>1/3 of the middle cerebral artery territory) acute supratentorial ischemic stroke or primary IPH > 30 mm3. For each image, we measured midline shift at the septum pellucidum (MLS-SP), pineal gland shift (PGS), the ratio of the ipsilateral to contralateral midbrain width (IMW/CMW), and other exploratory markers of radiographic shift/compression. Pupil reactivity was measured using an automated infrared pupillometer (NeurOptics®, Inc.), specifically the proprietary algorithm for Neurological Pupil Index® (NPi). We used rank-normalization and linear mixed-effects models, stratified by diagnosis and hemorrhagic conversion, to test associations of radiographic markers of shift and asymmetric pupil reactivity (Diff NPi), adjusting for age, lesion volume, Glasgow Coma Scale, and osmotic medications.ResultsOf 53 patients with 74 CT images, 26 (49.1%) were female, and median age was 67 years. MLS-SP and PGS were greater in patients with IPH, compared to patients with ischemic stroke (6.2 v. 4.0 mm, 5.6 v. 3.4 mm, respectively). We found no significant associations between pupil reactivity and the radiographic markers of shift when adjusting for confounders. However, we found potentially relevant relationships between MLS-SP and Diff NPi in our IPH cohort (β = 0.11, SE 0.04, P = 0.01), and PGS and Diff NPi in the ischemic stroke cohort (β = 0.16, SE 0.09, P = 0.07).ConclusionWe found the relationship between midline shift and asymmetric pupil reactivity may differ between IPH and ischemic stroke. Our study may serve as necessary preliminary data to guide further prospective investigation into how clinical manifestations of radiographic midline shift differ by diagnosis and proximity to the midbrain.</p

Table_2_Quantitative pupillometry and radiographic markers of intracranial midline shift: A pilot study.docx

BackgroundAsymmetric pupil reactivity or size can be early clinical indicators of midbrain compression due to supratentorial ischemic stroke or primary intraparenchymal hemorrhage (IPH). Radiographic midline shift is associated with worse functional outcomes and life-saving interventions. Better understanding of quantitative pupil characteristics would be a non–invasive, safe, and cost-effective way to improve identification of life-threatening mass effect and resource utilization of emergent radiographic imaging. We aimed to better characterize the association between midline shift at various anatomic levels and quantitative pupil characteristics.MethodsWe conducted a multicenter retrospective study of brain CT images within 75 min of a quantitative pupil observation from patients admitted to Neuro-ICUs between 2016 and 2020 with large (>1/3 of the middle cerebral artery territory) acute supratentorial ischemic stroke or primary IPH > 30 mm3. For each image, we measured midline shift at the septum pellucidum (MLS-SP), pineal gland shift (PGS), the ratio of the ipsilateral to contralateral midbrain width (IMW/CMW), and other exploratory markers of radiographic shift/compression. Pupil reactivity was measured using an automated infrared pupillometer (NeurOptics®, Inc.), specifically the proprietary algorithm for Neurological Pupil Index® (NPi). We used rank-normalization and linear mixed-effects models, stratified by diagnosis and hemorrhagic conversion, to test associations of radiographic markers of shift and asymmetric pupil reactivity (Diff NPi), adjusting for age, lesion volume, Glasgow Coma Scale, and osmotic medications.ResultsOf 53 patients with 74 CT images, 26 (49.1%) were female, and median age was 67 years. MLS-SP and PGS were greater in patients with IPH, compared to patients with ischemic stroke (6.2 v. 4.0 mm, 5.6 v. 3.4 mm, respectively). We found no significant associations between pupil reactivity and the radiographic markers of shift when adjusting for confounders. However, we found potentially relevant relationships between MLS-SP and Diff NPi in our IPH cohort (β = 0.11, SE 0.04, P = 0.01), and PGS and Diff NPi in the ischemic stroke cohort (β = 0.16, SE 0.09, P = 0.07).ConclusionWe found the relationship between midline shift and asymmetric pupil reactivity may differ between IPH and ischemic stroke. Our study may serve as necessary preliminary data to guide further prospective investigation into how clinical manifestations of radiographic midline shift differ by diagnosis and proximity to the midbrain.</p