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Șerban CA, Barborică A, Roceanu AM, Mîndruță IR, Ciurea J, Stancu M, Pâslaru AC, Zăgrean AM, Zăgrean L, Moldovan M. Towards an electroencephalographic measure of awareness based on the reactivity of oscillatory macrostates to hearing a subject's own name. Eur J Neurosci 2024; 59:771-785. [PMID: 37675619 DOI: 10.1111/ejn.16138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 08/09/2023] [Accepted: 08/16/2023] [Indexed: 09/08/2023]
Abstract
We proposed that the brain's electrical activity is composed of a sequence of alternating states with repeating topographic spectral distributions on scalp electroencephalogram (EEG), referred to as oscillatory macrostates. The macrostate showing the largest decrease in the probability of occurrence, measured as a percentage (reactivity), during sensory stimulation was labelled as the default EEG macrostate (DEM). This study aimed to assess the influence of awareness on DEM reactivity (DER). We included 11 middle cerebral artery ischaemic stroke patients with impaired awareness having a median Glasgow Coma Scale (GCS) of 6/15 and a group of 11 matched healthy controls. EEG recordings were carried out during auditory 1 min stimulation epochs repeating either the subject's own name (SON) or the SON in reverse (rSON). The DEM was identified across three SON epochs alternating with three rSON epochs. Compared with the patients, the DEM of controls contained more posterior theta activity reflecting source dipoles that could be mapped in the posterior cingulate cortex. The DER was measured from the 1 min quiet baseline preceding each stimulation epoch. The difference in mean DER between the SON and rSON epochs was measured by the salient EEG reactivity (SER) theoretically ranging from -100% to 100%. The SER was 12.4 ± 2.7% (Mean ± standard error of the mean) in controls and only 1.3 ± 1.9% in the patient group (P < 0.01). The patient SER decreased with the Glasgow Coma Scale. Our data suggest that awareness increases DER to SON as measured by SER.
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Affiliation(s)
- Cosmin-Andrei Șerban
- Physics Department, University of Bucharest, Bucharest, Romania
- Termobit Prod SRL, Bucharest, Romania
- FHC Inc, Bowdoin, Maine, USA
| | - Andrei Barborică
- Physics Department, University of Bucharest, Bucharest, Romania
- Termobit Prod SRL, Bucharest, Romania
- FHC Inc, Bowdoin, Maine, USA
| | | | | | - Jan Ciurea
- Department of Neurosurgery, Bagdasar-Arseni Emergency Hospital, Bucharest, Romania
| | - Mihai Stancu
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Division of Neurobiology, Faculty of Biology, Ludwig Maximilian University, Munich, Germany
| | - Alexandru C Pâslaru
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Ana-Maria Zăgrean
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Leon Zăgrean
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Mihai Moldovan
- Termobit Prod SRL, Bucharest, Romania
- Division of Physiology and Neuroscience, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
- Clinical Neurophysiology and Neurology, Rigshospitalet, Copenhagen, Denmark
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Serban CA, Barborica A, Roceanu AM, Mindruta I, Ciurea J, Pâslaru AC, Zăgrean AM, Zăgrean L, Moldovan M. A method to assess the default EEG macrostate and its reactivity to stimulation. Clin Neurophysiol 2021; 134:50-64. [PMID: 34973517 DOI: 10.1016/j.clinph.2021.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Revised: 08/23/2021] [Accepted: 12/04/2021] [Indexed: 11/16/2022]
Abstract
OBJECTIVE The default mode network (DMN) is deactivated by stimulation. We aimed to assess the DMN reactivity impairment by routine EEG recordings in stroke patients with impaired consciousness. METHODS Binocular light flashes were delivered at 1 Hz in 1-minute epochs, following a 1-minute baseline (PRE). The EEG was decomposed in a series of binary oscillatory macrostates by topographic spectral clustering. The most deactivated macrostate was labeled the default EEG macrostate (DEM). Its reactivity (DER) was quantified as the decrease in DEM occurrence probability during stimulation. A normalized DER index (DERI) was calculated as DER/PRE. The measures were compared between 14 healthy controls and 32 comatose patients under EEG monitoring following an acute stroke. RESULTS The DEM was mapped to the posterior DMN hubs. In the patients, these DEM source dipoles were 3-4 times less frequent and were associated with an increased theta activity. Even in a reduced 6-channel montage, a DER below 6.26% corresponding to a DERI below 0.25 could discriminate the patients with sensitivity and specificity well above 80%. CONCLUSION The method detected the DMN impairment in post-stroke coma patients. SIGNIFICANCE The DEM and its reactivity to stimulation could be useful to monitor the DMN function at bedside.
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Affiliation(s)
- Cosmin-Andrei Serban
- Physics Department, University of Bucharest, Romania; Termobit Prod SRL, Bucharest, Romania; FHC Inc, Bowdoin, ME, USA.
| | - Andrei Barborica
- Physics Department, University of Bucharest, Romania; Termobit Prod SRL, Bucharest, Romania; FHC Inc, Bowdoin, ME, USA.
| | | | - Ioana Mindruta
- Neurology Department, University Emergency Hospital, Bucharest, Romania.
| | - Jan Ciurea
- Department of Neurosurgery, Bagdasar-Arseni Emergency Hospital, Bucharest, Romania.
| | - Alexandru C Pâslaru
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Ana-Maria Zăgrean
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Leon Zăgrean
- Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania
| | - Mihai Moldovan
- Termobit Prod SRL, Bucharest, Romania; Division of Physiology and Neuroscience, "Carol Davila" University of Medicine and Pharmacy, Bucharest, Romania; Neuroscience, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Neurophysiology, Rigshospitalet, Copenhagen, Denmark.
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Bagher Ebadian H, Siddiqui F, Ghanem A, Zhu S, Lu M, Movsas B, Chetty IJ. Radiomics outperforms clinical factors in characterizing human papilloma virus (HPV) for patients with oropharyngeal squamous cell carcinomas. Biomed Phys Eng Express 2021; 8. [PMID: 34781281 DOI: 10.1088/2057-1976/ac39ab] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 11/15/2021] [Indexed: 11/11/2022]
Abstract
Purpose:To utilize radiomic features extracted from CT images to characterize Human Papilloma Virus (HPV) for patients with oropharyngeal cancer squamous cell carcinoma (OPSCC).Methods:One hundred twenty-eight OPSCC patients with known HPV-status (60-HPV+ and 68-HPV-, confirmed by immunohistochemistry-P16-protein testing) were retrospectively studied. Radiomic features (11 feature-categories) were extracted in 3D from contrast-enhanced (CE)-CT images of gross-tumor-volumes using 'in-house' software ('ROdiomiX') developed and validated following the image-biomarker-standardization-initiative (IBSI) guidelines. Six clinical factors were investigated: Age-at-Diagnosis, Gender, Total-Charlson, Alcohol-Use, Smoking-History, and T-Stage. A Least-Absolute-Shrinkage-and-Selection-Operation (Lasso) technique combined with a Generalized-Linear-Model (Lasso-GLM) were applied to perform regularization in the radiomic and clinical feature spaces to identify the ranking of optimal feature subsets with most representative information for prediction of HPV. Lasso-GLM models/classifiers based on clinical factors only, radiomics only, and combined clinical and radiomics (ensemble/integrated) were constructed using random-permutation-sampling. Tests of significance (One-way ANOVA), average Area-Under-Receiver-Operating-Characteristic (AUC), and Positive and Negative Predictive values (PPV and NPV) were computed to estimate the generalization-error and prediction performance of the classifiers.Results:Five clinical factors, including T-stage, smoking status, and age, and 14 radiomic features, including tumor morphology, and intensity contrast were found to be statistically significant discriminators between HPV positive and negative cohorts. Performances for prediction of HPV for the 3 classifiers were: Radiomics-Lasso-GLM: AUC/PPV/NPV=0.789/0.755/0.805; Clinical-Lasso-GLM: 0.676/0.747/0.672, and Integrated/Ensemble-Lasso-GLM: 0.895/0.874/0.844. Results imply that the radiomics-based classifier enabled better characterization and performance prediction of HPV relative to clinical factors, and that the combination of both radiomics and clinical factors yields even higher accuracy characterization and predictive performance.Conclusion:Albeit subject to confirmation in a larger cohort, this pilot study presents encouraging results in support of the role of radiomic features towards characterization of HPV in patients with OPSCC.
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Affiliation(s)
- Hassan Bagher Ebadian
- Department of Radiation Oncology , Henry Ford Hospital, 2799 West Grand Blvd., Detroit, Detroit, Michigan, 48202, UNITED STATES
| | - Farzan Siddiqui
- Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd., Detroit, Michigan, 48202, UNITED STATES
| | - Ahmed Ghanem
- Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd., Detroit, Michigan, 48202, UNITED STATES
| | - Simeng Zhu
- Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd., Detroit, Michigan, 48202, UNITED STATES
| | - Mei Lu
- Henry Ford Hospital, 2799 West Grand Blvd., Detroit, Michigan, 48202, UNITED STATES
| | - Benjamin Movsas
- Dept of Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd., Detroit, 48202, UNITED STATES
| | - Indrin J Chetty
- Dept of Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd, Detroit, MI 48202-2689, USA, Detroit, Michigan, 48202, UNITED STATES
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Bagher-Ebadian H, Zhu S, Siddiqui F, Lu M, Movsas B, Chetty IJ. Technical Note: On the development of an outcome-driven frequency filter for improving Radiomics-based modeling of Human Papilloma Virus (HPV) in patients with oropharyngeal squamous cell carcinomas. Med Phys 2021; 48:7552-7562. [PMID: 34390003 DOI: 10.1002/mp.15159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/08/2021] [Accepted: 08/03/2021] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To implement an outcome-driven frequency filter for improving radiomics-based modeling of human papilloma virus (HPV) for patients with oropharyngeal squamous cell carcinoma (OPSCC). METHODS AND MATERIALS One hundred twenty-eight OPSCC patients with known HPV status (60-HPV+ and 68-HPV-, confirmed by immunohistochemistry-P16 protein testing) were retrospectively studied. A 3D Discrete Fourier Transform was applied on contrast-enhanced CT images of patient gross tumor volumes (GTV's) to transform intensity distributions to the frequency domain and estimate frequency power spectrums of HPV- and HPV+ patient cohorts. Statistical analyses were performed to rank frequency bands contributing towards prediction of HPV status. An outcome-driven frequency filter was designed accordingly and applied to GTV frequency information. 3D Inverse-Discrete-Fourier-Transform was applied to reconstruct HPV-related frequency-filtered images. Radiomics features (11 feature-categories) were extracted from pre- and post- frequency filtered images using our previously published 'ROdiomiX' software. Least-Absolute-Shrinkage-and-Selection-Operation (Lasso) combined with a Generalized-Linear-Model (Lasso-GLM) was developed to identify and rank feature subsets with optimal information for prediction of HPV+/-. Radiomics-based Lasso-GLM classifiers (pre- and post-frequency filtered) were constructed and validated using a random permutation sampling and nested cross-validation techniques. Average Area Under Receiver Operating Characteristic (AUC), and Positive and Negative Predictive values (PPV, NPV) were computed to estimate generalization error and prediction performance. RESULTS Among 192 radiomic features, 15 features were found to be statistically significant discriminators between HPV+/- cohorts on post-frequency filtered CE-CT images; 14 such radiomic features were observed on pre-frequency filtered datasets. Discriminant features included tumor morphology and intensity contrast. Performances for prediction of HPV for the pre- and post-frequency filtered Lasso-GLM classifiers were: AUC/PPV/NPV = 0.789/0.755/0.805 and 0.850/0.808/0.877 respectively. Nested-CV performances for prediction of HPV for the pre- and post-frequency filtered Lasso-GLM classifiers were: AUC/PPV/NPV = 0.814/0.725/0.877 and 0.890/0.820/0.911 respectively. CONCLUSION Albeit subject to confirmation in a larger cohort, this pilot study presents encouraging results on the importance of frequency analysis prior to radiomic feature extraction toward enhancement of model performance for characterizing HPV in patients with OPSCC. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Hassan Bagher-Ebadian
- Department of Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd, Detroit, MI, 48202, USA
| | - Simeng Zhu
- Department of Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd, Detroit, MI, 48202, USA
| | - Farzan Siddiqui
- Department of Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd, Detroit, MI, 48202, USA
| | - Mei Lu
- Department of Public Health, Henry Ford Health System, Michigan, MI, 48202, USA
| | - Benjamin Movsas
- Department of Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd, Detroit, MI, 48202, USA
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Hospital, 2799 West Grand Blvd, Detroit, MI, 48202, USA
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Liu H, Jin IH, Zhang Z, Yuan Y. Social Network Mediation Analysis: A Latent Space Approach. PSYCHOMETRIKA 2021; 86:272-298. [PMID: 33346886 DOI: 10.1007/s11336-020-09736-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Accepted: 11/24/2020] [Indexed: 06/12/2023]
Abstract
A social network comprises both actors and the social connections among them. Such connections reflect the dependence among social actors, which is essential for individuals' mental health and social development. In this article, we propose a mediation model with a social network as a mediator to investigate the potential mediation role of a social network. In the model, the dependence among actors is accounted for by a few mutually orthogonal latent dimensions which form a social space. The individuals' positions in such a latent social space are directly involved in the mediation process between an independent and dependent variable. After showing that all the latent dimensions are equivalent in terms of their relationship to the social network and the meaning of each dimension is arbitrary, we propose to measure the whole mediation effect of a network. Although individuals' positions in the latent space are not unique, we rigorously articulate that the proposed network mediation effect is still well defined. We use a Bayesian estimation method to estimate the model and evaluate its performance through an extensive simulation study under representative conditions. The usefulness of the network mediation model is demonstrated through an application to a college friendship network.
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Affiliation(s)
- Haiyan Liu
- Psychological Sciences, University of California, Merced, 5200 N. Lake Road, Merced, CA, 95343, USA.
| | - Ick Hoon Jin
- Department of Applied Statistics, Department of Statistics and Data Science, Yonsei University, Seoul, South Korea
| | - Zhiyong Zhang
- Department of Psychology, University of Notre Dame, Notre Dame, USA
| | - Ying Yuan
- Department of Biostatistics, The University of Texas MD, Anderson Cancer Center, Houston, USA
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Howes OD, Whitehurst T, Shatalina E, Townsend L, Onwordi EC, Mak TLA, Arumuham A, O’Brien O, Lobo M, Vano L, Zahid U, Butler E, Osugo M. The clinical significance of duration of untreated psychosis: an umbrella review and random-effects meta-analysis. World Psychiatry 2021; 20:75-95. [PMID: 33432766 PMCID: PMC7801839 DOI: 10.1002/wps.20822] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The idea that a longer duration of untreated psychosis (DUP) leads to poorer outcomes has contributed to extensive changes in mental health ser-vices worldwide and has attracted considerable research interest over the past 30 years. However, the strength of the evidence underlying this notion is unclear. To address this issue, we conducted an umbrella review of available meta-analyses and performed a random-effects meta-analysis of primary studies. MEDLINE, Web of Science, PsycINFO and EMBASE were searched from inception to September 3, 2020 to identify relevant meta-analyses of studies including patients with schizophrenia spectrum disorders, first-episode psychosis, or affective and non-affective psychosis. Thirteen meta-analyses were included, corresponding to 129 individual studies with a total sample size of 25,657 patients. We detected potential violations of statistical assumptions in some of these meta-analyses. We therefore conducted a new random-effects meta-analysis of primary studies. The association between DUP and each outcome was graded according to a standardized classification into convincing, highly suggestive, suggestive, weak, or non-significant. At first presentation, there was suggestive evidence for a relationship between longer DUP and more severe negative symptoms (beta=-0.07, p=3.6×10-5 ) and higher chance of previous self-harm (odds ratio, OR=1.89, p=1.1×10-5 ). At follow-up, there was highly suggestive evidence for a relationship between longer DUP and more severe positive symptoms (beta=-0.16, p=4.5×10-8 ), more severe negative symptoms (beta=-0.11, p=3.5×10-10 ) and lower chance of remission (OR=2.16, p=3.0×10-10 ), and suggestive evidence for a relationship between longer DUP and poorer overall functioning (beta=-0.11, p=2.2×10-6 ) and more severe global psychopathology (beta=-0.16, p=4.7×10-6 ). Results were unchanged when analysis was restricted to prospective studies. These effect sizes are clinically meaningful, with a DUP of four weeks predicting >20% more severe symptoms at follow-up relative to a DUP of one week. We conclude that DUP is an important prognostic factor at first presentation and predicts clinically relevant outcomes over the course of illness. We discuss conceptual issues in DUP research and methodological limitations of current evidence, and provide recommendations for future research.
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Affiliation(s)
- Oliver D. Howes
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK,MRC London Institute of Medical SciencesHammersmith HospitalLondonUK,Institute of Clinical Sciences, Faculty of MedicineImperial College LondonLondonUK,South London and Maudsley Foundation NHS TrustMaudsley HospitalLondonUK
| | - Thomas Whitehurst
- MRC London Institute of Medical SciencesHammersmith HospitalLondonUK,Institute of Clinical Sciences, Faculty of MedicineImperial College LondonLondonUK
| | - Ekaterina Shatalina
- MRC London Institute of Medical SciencesHammersmith HospitalLondonUK,Institute of Clinical Sciences, Faculty of MedicineImperial College LondonLondonUK
| | - Leigh Townsend
- MRC London Institute of Medical SciencesHammersmith HospitalLondonUK,Institute of Clinical Sciences, Faculty of MedicineImperial College LondonLondonUK
| | - Ellis Chika Onwordi
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK,MRC London Institute of Medical SciencesHammersmith HospitalLondonUK,Institute of Clinical Sciences, Faculty of MedicineImperial College LondonLondonUK,South London and Maudsley Foundation NHS TrustMaudsley HospitalLondonUK
| | | | - Atheeshaan Arumuham
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK,MRC London Institute of Medical SciencesHammersmith HospitalLondonUK,Institute of Clinical Sciences, Faculty of MedicineImperial College LondonLondonUK,South London and Maudsley Foundation NHS TrustMaudsley HospitalLondonUK
| | - Oisín O’Brien
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK
| | - Maria Lobo
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK
| | - Luke Vano
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK
| | - Uzma Zahid
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK
| | - Emma Butler
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK,South London and Maudsley Foundation NHS TrustMaudsley HospitalLondonUK
| | - Martin Osugo
- Institute of Psychiatry, Psychology and NeuroscienceKing’s College LondonLondonUK,MRC London Institute of Medical SciencesHammersmith HospitalLondonUK,Institute of Clinical Sciences, Faculty of MedicineImperial College LondonLondonUK
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Luck S. Nonoverlap proportion and the representation of point-biserial variation. PLoS One 2020; 15:e0244517. [PMID: 33370394 PMCID: PMC7769483 DOI: 10.1371/journal.pone.0244517] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 12/10/2020] [Indexed: 11/18/2022] Open
Abstract
We consider the problem of constructing a complete set of parameters that account for all of the degrees of freedom for point-biserial variation. We devise an algorithm where sort as an intrinsic property of both numbers and labels, is used to generate the parameters. Algebraically, point-biserial variation is represented by a Cartesian product of statistical parameters for two sets of [Formula: see text] data, and the difference between mean values (δ) corresponds to the representation of variation in the center of mass coordinates, (δ, μ). The existence of alternative effect size measures is explained by the fact that mathematical considerations alone do not specify a preferred coordinate system for the representation of point-biserial variation. We develop a novel algorithm for estimating the nonoverlap proportion (ρpb) of two sets of [Formula: see text] data. ρpb is obtained by sorting the labeled [Formula: see text] data and analyzing the induced order in the categorical data using a diagonally symmetric 2 × 2 contingency table. We examine the correspondence between ρpb and point-biserial correlation (rpb) for uniform and normal distributions. We identify the [Formula: see text], [Formula: see text], and [Formula: see text] representations for Pearson product-moment correlation, Cohen's d, and rpb. We compare the performance of rpb versus ρpb and the sample size proportion corrected correlation (rpbd), confirm that invariance with respect to the sample size proportion is important in the formulation of the effect size, and give an example where three parameters (rpbd, μ, ρpb) are needed to distinguish different forms of point-biserial variation in CART regression tree analysis. We discuss the importance of providing an assessment of cost-benefit trade-offs between relevant system parameters because 'substantive significance' is specified by mapping functional or engineering requirements into the effect size coordinates. Distributions and confidence intervals for the statistical parameters are obtained using Monte Carlo methods.
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Affiliation(s)
- Stanley Luck
- Vector Analytics, LLC, Wilmington, DE, United States of America
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Bagher-Ebadian H, Lu M, Siddiqui F, Ghanem AI, Wen N, Wu Q, Liu C, Movsas B, Chetty IJ. Application of radiomics for the prediction of HPV status for patients with head and neck cancers. Med Phys 2020; 47:563-575. [PMID: 31853980 DOI: 10.1002/mp.13977] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Revised: 10/28/2019] [Accepted: 11/22/2019] [Indexed: 12/19/2022] Open
Abstract
PURPOSE To perform radiomic analysis of primary tumors extracted from pretreatment contrast-enhanced computed tomography (CE-CT) images for patients with oropharyngeal cancers to identify discriminant features and construct an optimal classifier for the characterization and prediction of human papilloma virus (HPV) status. MATERIALS AND METHODS One hundred and eighty seven patients with oropharyngeal cancers with known HPV status (confirmed by immunohistochemistry-p16 protein testing) were retrospectively studied as follows: Group A: 95 patients (19HPV- and 76HPV+) from the MICAII grand challenge. Group B: 92 patients (52HPV- and 40HPV+) from our institution. Radiomic features (172) were extracted from pretreatment diagnostic CE-CT images of the gross tumor volume (GTV). Levene and Kolmogorov-Smirnov's tests with absolute biserial correlation (>0.48) were used to identify the discriminant features between the HPV+ and HPV- groups. The discriminant features were used to train and test eight different classifiers. Area under receiver operating characteristic (AUC), positive predictive and negative predictive values (PPV and NPV, respectively) were used to evaluate the performance of the classifiers. Principal component analysis (PCA) was applied on the discriminant feature set and seven PCs were used to train and test a generalized linear model (GLM) classifier. RESULTS Among 172 radiomic features only 12 radiomic features (from 3 categories) were significantly different (P < 0.05, |BSC| > 0.48) between the HPV+ and HPV- groups. Among the eight classifiers trained and applied for prediction of HPV status, the GLM showed the highest performance for each discriminant feature and the combined 12 features: AUC/PPV/NPV = 0.878/0.834/0.811. The GLM high prediction power was AUC/PPV/NPV = 0.849/0.731/0.788 and AUC/PPV/NPV = 0.869/0.807/0.870 for unseen test datasets for groups A and B, respectively. After eliminating the correlation among discriminant features by applying PCA analysis, the performance of the GLM was improved by 3.3%, 2.2%, and 1.8% for AUC, PPV, and NPV, respectively. CONCLUSIONS Results imply that GTV's for HPV+ patients exhibit higher intensities, smaller lesion size, greater sphericity/roundness, and higher spatial intensity-variation/heterogeneity. Results are suggestive that radiomic features primarily associated with the spatial arrangement and morphological appearance of the tumor on contrast-enhanced diagnostic CT datasets may be potentially used for classification of HPV status.
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Affiliation(s)
| | - Mei Lu
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - Farzan Siddiqui
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Ahmed I Ghanem
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA.,Department of Clinical Oncology, Alexandria University, Alexandria, Egypt
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Qixue Wu
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Chang Liu
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Benjamin Movsas
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA
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de Souza RB, Farinha-Arcieri LE, Catroxo MHB, Martins AMCRPDF, Tedesco RC, Alonso LG, Koh IHJ, Pereira LV. Association of thoracic spine deformity and cardiovascular disease in a mouse model for Marfan syndrome. PLoS One 2019; 14:e0224581. [PMID: 31725753 PMCID: PMC6855660 DOI: 10.1371/journal.pone.0224581] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2019] [Accepted: 10/16/2019] [Indexed: 12/18/2022] Open
Abstract
Aims Cardiovascular manifestations are a major cause of mortality in Marfan syndrome (MFS). Animal models that mimic the syndrome and its clinical variability are instrumental for understanding the genesis and risk factors for cardiovascular disease in MFS. This study used morphological and ultrastructural analysis to the understanding of the development of cardiovascular phenotypes of the the mgΔloxPneo model for MFS. Methods and results We studied 6-month-old female mice of the 129/Sv background, 6 wild type (WT) and 24 heterozygous animals from the mgΔloxPneo model. Descending thoracic aortic aneurysm and/or dissection (dTAAD) were identified in 75% of the MFS animals, defining two subgroups: MFS with (MFS+) and without (MFS-) dTAAD. Both subgroups showed increased fragmentation of elastic fibers, predominance of type I collagen surrounding the elastic fiber and fragmentation of interlaminar fibers when compared to WT. However, only MFS animals with spine tortuosity developed aortic aneurysm/dissection. The aorta of MFS+ animals were more tortuous compared to those of MFS- and WT mice, possibly causing perturbations of the luminal blood flow. This was evidenced by the detection of diminished aorta-blood flow in MFS+. Accordingly, only MFS+ animals presented a process of concentric cardiac hypertrophy and a significantly decreased ratio of left and right ventricle lumen area. Conclusions We show that mgΔloxPneo model mimics the vascular disease observed in MFS patients. Furthermore, the study indicates role of thoracic spine deformity in the development of aorta diseases. We suggest that degradation of support structures of the aortic wall; deficiency in the sustenance of the thoracic vertebrae; and their compression over the adjacent aorta resulting in disturbed blood flow is a triad of factors involved in the genesis of dissection/aneurysm of thoracic aorta.
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Affiliation(s)
| | | | | | | | - Roberto Carlos Tedesco
- Federal University of São Paulo, Department of Morphological and Genetics, São Paulo, SP, Brazil
| | - Luis Garcia Alonso
- Federal University of São Paulo, Department of Morphological and Genetics, São Paulo, SP, Brazil
| | - Ivan Hong Jun Koh
- Federal University of São Paulo, Department of Surgery, São Paulo, SP, Brazil
| | - Lygia V. Pereira
- University of São Paulo, Department of Genetics and Evolutionary Biology, São Paulo, SP, Brazil
- * E-mail:
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