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Fath L, Simon F, Levy R, Boccara O, Couloigner V. Dangers and therapeutic difficulties of intracranial hemangioma in infants: A CARE case report. Eur Ann Otorhinolaryngol Head Neck Dis 2024; 141:227-230. [PMID: 38395664 DOI: 10.1016/j.anorl.2024.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2024]
Abstract
INTRODUCTION Description of neurological complications induced by intracranial hemangioma in infants and by the initiation of beta-blocker treatment (propranolol). OBSERVATION A 2-month-old infant was referred for grade 5 non-congenital unilateral peripheral facial palsy. Work-up revealed ipsilateral profound hearing loss and two intracranial hemangiomas: one in the ipsilateral internal auditory canal (IAC), the other in the cerebellum opposite the nodule of vermis. Initial treatment with a beta-blocker (propranolol 1mg/kg/day for 1month, then 3mg/kg/day) resulted in disappearance of symptoms and regression of lesions within 8weeks. At 20months after introduction of maintenance therapy (propranolol 3mg/kg/day), two asthma attacks occurred, leading to initiation of fluticasone and continuation of the beta-blocker. Thirty months after discontinuation of treatment, no further progression was noted. DISCUSSION Unilateral facial palsy in an infant suggests a number of diagnoses. MRI revealed IAC hemangioma. The choice of dosage and duration of treatment was based on a review of the literature and a strategy defined in multidisciplinary consultation.
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Affiliation(s)
- Léa Fath
- Service d'ORL et Chirurgie Cervicofaciale Pédiatrique, Hôpital Necker-Enfants-Malades, Assistance publique-Hôpitaux de Paris, Université Paris Descartes, Paris, France.
| | - François Simon
- Service d'ORL et Chirurgie Cervicofaciale Pédiatrique, Hôpital Necker-Enfants-Malades, Assistance publique-Hôpitaux de Paris, Université Paris Descartes, Paris, France
| | - Raphaël Levy
- Service de Radiologie Pédiatrique, Hôpital Necker-Enfants-Malades, Assistance publique-Hôpitaux de Paris, Université Paris Descartes, Paris, France
| | - Olivia Boccara
- Service de Dermatologie Pédiatrique, Hôpital Necker-Enfants-Malades, Assistance publique-Hôpitaux de Paris, Université Paris Descartes, Paris, France
| | - Vincent Couloigner
- Service d'ORL et Chirurgie Cervicofaciale Pédiatrique, Hôpital Necker-Enfants-Malades, Assistance publique-Hôpitaux de Paris, Université Paris Descartes, Paris, France
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Aghakhanyan G, Filidei T, Febi M, Fanni SC, Marciano A, Francischello R, Caputo FP, Tumminello L, Cioni D, Neri E, Volterrani D. Advancing Pediatric Sarcomas through Radiomics: A Systematic Review and Prospective Assessment Using Radiomics Quality Score (RQS) and Methodological Radiomics Score (METRICS). Diagnostics (Basel) 2024; 14:832. [PMID: 38667477 PMCID: PMC11049622 DOI: 10.3390/diagnostics14080832] [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: 03/13/2024] [Revised: 04/12/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
Pediatric sarcomas, rare malignancies of mesenchymal origin, pose diagnostic and therapeutic challenges. In this review, we explore the role of radiomics in reshaping our understanding of pediatric sarcomas, emphasizing methodological considerations and applications such as diagnostics and predictive modeling. A systematic review conducted up to November 2023 identified 72 papers on radiomics analysis in pediatric sarcoma from PubMed/MEDLINE, Web of Knowledge, and Scopus. Following inclusion and exclusion criteria, 10 reports were included in this review. The studies, predominantly retrospective, focus on Ewing sarcoma and osteosarcoma, utilizing diverse imaging modalities, including CT, MRI, PET/CT, and PET/MRI. Manual segmentation is common, with a median of 35 features extracted. Radiomics Quality Score (RQS) and Methodological Radiomics Score (METRICS) assessments reveal a consistent emphasis on non-radiomic features, validation criteria, and improved methodological rigor in recent publications. Diagnostic applications dominate, with innovative studies exploring prognostic and treatment response aspects. Challenges include feature heterogeneity and sample size variations. The evolving landscape underscores the need for standardized methodologies. Despite challenges, the diagnostic and predictive potential of radiomics in pediatric oncology is evident, paving the way for precision medicine advancements.
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Affiliation(s)
- Gayane Aghakhanyan
- Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, 56126 Pisa, Italy
| | - Tommaso Filidei
- Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, 56126 Pisa, Italy
| | - Maria Febi
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Salvatore C. Fanni
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Andrea Marciano
- Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, 56126 Pisa, Italy
| | - Roberto Francischello
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Francesca Pia Caputo
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Lorenzo Tumminello
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Dania Cioni
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Emanuele Neri
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Duccio Volterrani
- Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, 56126 Pisa, Italy
- Regional Center of Nuclear Medicine, University Hospital of Pisa, 56126 Pisa, Italy
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Alanezi ST, Almutairi WM, Cronin M, Gobbo O, O'Mara SM, Sheppard D, O'Connor WT, Gilchrist MD, Kleefeld C, Colgan N. Whole-brain traumatic controlled cortical impact to the left frontal lobe: Magnetic resonance image-based texture analysis. J Neuropathol Exp Neurol 2024; 83:94-106. [PMID: 38164986 DOI: 10.1093/jnen/nlad110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2024] Open
Abstract
This research assesses the capability of texture analysis (TA) derived from high-resolution (HR) T2-weighted magnetic resonance imaging to identify primary sequelae following 1-5 hours of controlled cortical impact mild or severe traumatic brain injury (TBI) to the left frontal cortex (focal impact) and secondary (diffuse) sequelae in the right frontal cortex, bilateral corpus callosum, and hippocampus in rats. The TA technique comprised first-order (histogram-based) and second-order statistics (including gray-level co-occurrence matrix, gray-level run length matrix, and neighborhood gray-level difference matrix). Edema in the left frontal impact region developed within 1 hour and continued throughout the 5-hour assessments. The TA features from HR images confirmed the focal injury. There was no significant difference among radiomics features between the left and right corpus callosum or hippocampus from 1 to 5 hours following a mild or severe impact. The adjacent corpus callosum region and the distal hippocampus region (s), showed no diffuse injury 1-5 hours after mild or severe TBI. These results suggest that combining HR images with TA may enhance detection of early primary and secondary sequelae following TBI.
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Affiliation(s)
- Saleh T Alanezi
- Physics Department, Faculty of Science, Northern Border University, ArAr, Saudi Arabia
- School of Natural Sciences, College of Science and Engineering, University of Galway, Galway, Ireland
| | - Waleed M Almutairi
- Medical Imaging Department, King Abdullah bin Abdulaziz University Hospital, Riyadh, Saudi Arabia
- Department of Physics, College of Science, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia
| | - Michelle Cronin
- Conway Institute, University College Dublin, Belfield, Dublin, Ireland
| | - Oliviero Gobbo
- School of Pharmacy and Pharmaceutical Sciences & Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Shane M O'Mara
- Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Declan Sheppard
- Department of Radiology, University Hospital Galway, Galway, Ireland
| | - William T O'Connor
- University of Limerick School of Medicine, Castletroy, Limerick, Ireland
| | - Michael D Gilchrist
- School of Mechanical & Materials Engineering, University College Dublin, Belfield, Dublin, Ireland
| | - Christoph Kleefeld
- School of Natural Sciences, College of Science and Engineering, University of Galway, Galway, Ireland
| | - Niall Colgan
- School of Natural Sciences, College of Science and Engineering, University of Galway, Galway, Ireland
- Department of Engineering, Technological University of the Shannon, Athlone, Ireland
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Neumane S, Lesage A, Dangouloff-Ros V, Levy R, Roux CJ, Robert MP, Bremond-Gignac D, Boddaert N. Arterial Spin-Labeling in the Assessment of Pediatric Nontraumatic Orbital Lesions. AJNR Am J Neuroradiol 2023; 44:1219-1223. [PMID: 37652581 PMCID: PMC10549944 DOI: 10.3174/ajnr.a7977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/02/2023] [Indexed: 09/02/2023]
Abstract
Benign and malignant pediatric orbital lesions can sometimes have overlapping features on conventional MR imaging sequences. MR imaging of 27 children was retrospectively reviewed to describe the signal of some common pediatric extraocular orbital lesions on arterial spin-labeling and to evaluate whether this sequence helps to discriminate malignant from benign masses, with or without ADC value measurements. Qualitative and quantitative assessments of arterial spin-labeling CBF and ADC were performed. All lesions were classified into 3 arterial spin-labeling perfusion patterns: homogeneous hypoperfusion (pattern 1, n = 15; benign lesions), heterogeneous hyperperfusion (pattern 2, n = 9; cellulitis, histiocytosis, malignant tumors), and homogeneous intense hyperperfusion (pattern 3, n = 3; infantile hemangiomas). Arterial spin-labeling can be a valuable tool to improve the diagnostic confidence of some orbital lesions, including infantile hemangioma. An algorithm is proposed.
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Affiliation(s)
- S Neumane
- From the Department of Pediatric Radiology (S.N., A.L., V.D.-R., R.L., C.-J.R., N.B.), Hôpital Universitaire Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France
- NeuroSpin, UNIACT (S.N.), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA), Université Paris-Saclay, Gif-sur-Yvette, France
| | - A Lesage
- From the Department of Pediatric Radiology (S.N., A.L., V.D.-R., R.L., C.-J.R., N.B.), Hôpital Universitaire Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France
- Department of Pediatric Radiology (A.L.), Centre Hospitalier Universitaire Saint-Justine, Montréal, Quebec, Canada
| | - V Dangouloff-Ros
- From the Department of Pediatric Radiology (S.N., A.L., V.D.-R., R.L., C.-J.R., N.B.), Hôpital Universitaire Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France
- Institut Imagine (V.D.-R., R.L., C.-J.R., N.B.), Institut National de la Santé et de la Recherche Médicale (INSERM) U1163 and U1299, Université Paris Cité, Paris, France
| | - R Levy
- From the Department of Pediatric Radiology (S.N., A.L., V.D.-R., R.L., C.-J.R., N.B.), Hôpital Universitaire Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France
- Institut Imagine (V.D.-R., R.L., C.-J.R., N.B.), Institut National de la Santé et de la Recherche Médicale (INSERM) U1163 and U1299, Université Paris Cité, Paris, France
| | - C-J Roux
- From the Department of Pediatric Radiology (S.N., A.L., V.D.-R., R.L., C.-J.R., N.B.), Hôpital Universitaire Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France
- Institut Imagine (V.D.-R., R.L., C.-J.R., N.B.), Institut National de la Santé et de la Recherche Médicale (INSERM) U1163 and U1299, Université Paris Cité, Paris, France
| | - M P Robert
- Department of Ophthalmology (M.P.R., D.B.-G.), Hôpital Universitaire Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France
- Centre Borelli UMR 9010 (M.P.R.), Université Paris Cité, Université Paris-Saclay, ENS Paris-Saclay, CNRS, SSA, Institut National de la Santé et de la Recherche Médicale (INSERM), Paris, France
| | - D Bremond-Gignac
- Department of Ophthalmology (M.P.R., D.B.-G.), Hôpital Universitaire Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France
- Team 17 (D.B.-G.), Institut National de la Santé et de la Recherche Médicale, UMRS1138, Université Paris Cité, Paris, France
| | - N Boddaert
- From the Department of Pediatric Radiology (S.N., A.L., V.D.-R., R.L., C.-J.R., N.B.), Hôpital Universitaire Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Université Paris Cité, Paris, France
- Institut Imagine (V.D.-R., R.L., C.-J.R., N.B.), Institut National de la Santé et de la Recherche Médicale (INSERM) U1163 and U1299, Université Paris Cité, Paris, France
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Zheng M, Chen Q, Ge Y, Yang L, Tian Y, Liu C, Wang P, Deng K. Development and validation of CT-based radiomics nomogram for the classification of benign parotid gland tumors. Med Phys 2023; 50:947-957. [PMID: 36273307 DOI: 10.1002/mp.16042] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 10/27/2022] [Accepted: 10/27/2022] [Indexed: 11/13/2022] Open
Abstract
PURPOSE Accurate preoperative diagnosis of parotid tumor is essential for the formulation of optimal individualized surgical plans. The study aims to investigate the diagnostic performance of radiomics nomogram based on contrast-enhanced computed tomography (CT) images in the differentiation of the two most common benign parotid gland tumors. METHODS One hundred and ten patients with parotid gland tumors including 76 with pleomorphic adenoma (PA) and 34 with adenolymphoma (AL) confirmed by histopathology were included in this study. Radiomics features were extracted from contrast-enhanced CT images of venous phase. A radiomics model was established and a radiomics score (Rad-score) was calculated. Clinical factors including clinical data and CT features were assessed to build a clinical factor model. Finally, a nomogram incorporating the Rad-score and independent clinical factors was constructed. Receiver operator characteristics (ROC) curve was generated and the area under the ROC curve (AUC) was calculated to quantify the discriminative performance of each model on both the training and validation cohorts. Decision curve analysis (DCA) was conducted to evaluate the clinical usefulness of each model. RESULTS The radiomics model showed good discrimination in the training cohort [AUC, 0.89; 95% confidence interval (CI), 0.80-0.98] and validation cohort (AUC, 0.89; 95% CI, 0.77-1.00). The radiomics nomogram showed excellent discrimination in the training cohort (AUC, 0.98; 95% CI, 0.96-1.00) and validation cohort (AUC, 0.95; 95% CI, 0.88-1.00) and displayed better discrimination efficacy compared with the clinical factor model (AUC, 0.93; 95% CI, 0.88-0.99) in the training cohort (p < 0.05). The DCA demonstrated that the combined radiomics nomogram provided superior clinical usefulness than clinical factor model and radiomics model. CONCLUSIONS The CT-based radiomics nomogram combining Rad-score and clinical factors exhibits excellent predictive capability for differentiating parotid PA from AL, which might hold promise in assisting radiologists and clinicians in the exact differential diagnosis and formulation of appropriate treatment strategy.
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Affiliation(s)
- Menglong Zheng
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Qi Chen
- Department of Radiology, Kunshan Third People's Hospital, Kunshan, Jiangsu, China
| | | | - Liping Yang
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Yulong Tian
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Chang Liu
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Peng Wang
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Kexue Deng
- Department of Radiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
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Bekci T, Cakir IM, Aslan S. Differentiation of affected and nonaffected ovaries in ovarian torsion with magnetic resonance imaging texture analysis. Rev Assoc Med Bras (1992) 2022; 68:641-646. [DOI: 10.1590/1806-9282.20211369] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 01/03/2022] [Indexed: 11/22/2022] Open
Affiliation(s)
- Tumay Bekci
- Giresun University Faculty of Medicine, Turkey
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Cui Z, Ren G, Cai R, Wu C, Shi H, Wang X, Zhu M. MRI-based texture analysis for differentiate between pediatric posterior fossa ependymoma type A and B. Eur J Radiol 2022; 152:110288. [DOI: 10.1016/j.ejrad.2022.110288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 01/01/2022] [Accepted: 03/28/2022] [Indexed: 11/03/2022]
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Sarioglu FC, Sarioglu O, Guleryuz H, Deliloglu B, Tuzun F, Duman N, Ozkan H. The role of MRI-based texture analysis to predict the severity of brain injury in neonates with perinatal asphyxia. Br J Radiol 2022; 95:20210128. [PMID: 34919441 PMCID: PMC9153720 DOI: 10.1259/bjr.20210128] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE To evaluate the efficacy of the MRI-based texture analysis (TA) of the basal ganglia and thalami to distinguish moderate-to-severe hypoxic-ischemic encephalopathy (HIE) from mild HIE in neonates. METHODS This study included 68 neonates (15 with mild, 20 with moderate-to-severe HIE, and 33 control) were born at 37 gestational weeks or later and underwent MRI in first 10 days after birth. The basal ganglia and thalami were delineated for TA on the apparent diffusion coefficient (ADC) maps, T1-, and T2 weighted images. The basal ganglia, thalami, and the posterior limb of the internal capsule (PLIC) were also evaluated visually on diffusion-weighted imaging and T1 weighted sequence. Receiver operating characteristic curve and logistic regression analyses were used. RESULTS Totally, 56 texture features for the basal ganglia and 46 features for the thalami were significantly different between the HIE groups on the ADC maps, T2-, and T2 weighted sequences. Using a Histogram_entropy log-10 value as >1.8 from the basal ganglia on the ADC maps (p < 0.001; OR, 266) and the absence of hyperintensity of the PLIC on T1 weighted images (p = 0.012; OR, 17.11) were found as independent predictors for moderate-to-severe HIE. Using only a Histogram_entropy log-10 value had an equal diagnostic yield when compared to its combination with other texture features and imaging findings. CONCLUSION The Histogram_entropy log-10 value can be used as an indicator to differentiate from moderate-to-severe to mild HIE. ADVANCES IN KNOWLEDGE MRI-based TA may provide quantitative findings to indicate different stages in neonates with perinatal asphyxia.
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Affiliation(s)
- Fatma Ceren Sarioglu
- Division of Pediatric Radiology, Department of Radiology, Dokuz Eylul University School of Medicine, İzmir, Turkey
| | - Orkun Sarioglu
- Department of Radiology, Izmir Democracy University School of Medicine, Izmir, Turkey
| | - Handan Guleryuz
- Division of Pediatric Radiology, Department of Radiology, Dokuz Eylul University School of Medicine, İzmir, Turkey
| | - Burak Deliloglu
- Division of Neonatology, Department of Pediatrics, Dokuz Eylul University School of Medicine, Izmir, Turkey
| | - Funda Tuzun
- Division of Neonatology, Department of Pediatrics, Dokuz Eylul University School of Medicine, Izmir, Turkey
| | - Nuray Duman
- Division of Neonatology, Department of Pediatrics, Dokuz Eylul University School of Medicine, Izmir, Turkey
| | - Hasan Ozkan
- Division of Neonatology, Department of Pediatrics, Dokuz Eylul University School of Medicine, Izmir, Turkey
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Abstract
Artificial intelligence (AI) algorithms, particularly deep learning, have developed to the point that they can be applied in image recognition tasks. The use of AI in medical imaging can guide radiologists to more accurate image interpretation and diagnosis in radiology. The software will provide data that we cannot extract from the images. The rapid development in computational capabilities supports the wide applications of AI in a range of cancers. Among those are its widespread applications in head and neck cancer.
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Radiomics for Everyone: A New Tool Simplifies Creating Parametric Maps for the Visualization and Quantification of Radiomics Features. Tomography 2021; 7:477-487. [PMID: 34564303 PMCID: PMC8482265 DOI: 10.3390/tomography7030041] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 09/05/2021] [Accepted: 09/14/2021] [Indexed: 12/16/2022] Open
Abstract
Aim was to develop a user-friendly method for creating parametric maps that would provide a comprehensible visualization and allow immediate quantification of radiomics features. For this, a self-explanatory graphical user interface was designed, and for the proof of concept, maps were created for CT and MR images and features were compared to those from conventional extractions. Especially first-order features were concordant between maps and conventional extractions, some even across all examples. Potential clinical applications were tested on CT and MR images for the differentiation of pulmonary lesions. In these sample applications, maps of Skewness enhanced the differentiation of non-malignant lesions and non-small lung carcinoma manifestations on CT images and maps of Variance enhanced the differentiation of pulmonary lymphoma manifestations and fungal infiltrates on MR images. This new and simple method for creating parametric maps makes radiomics features visually perceivable, allows direct feature quantification by placing a region of interest, can improve the assessment of radiological images and, furthermore, can increase the use of radiomics in clinical routine.
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Sarioglu O, Sarioglu FC, Capar AE, Sokmez DF, Mete BD, Belet U. Clot-based radiomics features predict first pass effect in acute ischemic stroke. Interv Neuroradiol 2021; 28:160-168. [PMID: 34000866 DOI: 10.1177/15910199211019176] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
PURPOSE Our aim was to evaluate the performance of clot-based radiomics features (RFs) for predicting first pass effect (FPE) in patients with acute ischemic stroke (AIS). The secondary purpose was to search for any other variables associated with FPE. MATERIALS AND METHODS Patients who underwent mechanical thrombectomy (MT) for anterior circulation large vessel stroke in a single center were retrospectively reviewed. Patients were divided into two groups: FPE and non-FPE. Two observers extracted RFs from the clot on pretreatment noncontrast computed tomography (NCCT) images. Demographic, clinical, periprocedural, and RFs were compared between the groups and receiver operating characteristic (ROC) curves were constructed. Logistic regression analysis was used to determine the independent predictors of FPE. RESULTS Fifty-two patients (27 female, 25 male; mean age 64.50 ± 15.15) who were treated by stent retrievers as the first option were included in the study. FPE was achieved in 25 patients (25/52, 48.1%). Twelve RFs were significantly different between patients with FPE and non-FPE. The long-run low gray-level emphasis (odds ratio = 44.24, p = 0.003) and the zone percentage (odds ratio = 16.88, p = 0.017) were found as independent predictors of FPE. Female sex and a baseline ASPECT score of >8.5 were the other independent variables to predict FPE. The diagnostic accuracy to predict FPE was observed as 83% when using all independent predictors in our predictive model. CONCLUSIONS Clot-based RFs on NCCT may help to estimate the success of the intended outcome of MT in patients with AIS.
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Affiliation(s)
- Orkun Sarioglu
- Department of Radiology, Izmir Democracy University, Izmir, Turkey
| | - Fatma C Sarioglu
- Department of Radiology, Health Sciences University, Tepecik Educational and Research Hospital, Izmir, Turkey
| | - Ahmet E Capar
- Department of Radiology, Health Sciences University, Tepecik Educational and Research Hospital, Izmir, Turkey
| | - Demet Fb Sokmez
- Department of Neurology, Health Sciences University, Tepecik Educational and Research Hospital, Izmir, Turkey
| | - Berna D Mete
- Department of Radiology, Izmir Democracy University, Izmir, Turkey
| | - Umit Belet
- Department of Radiology, Health Sciences University, Tepecik Educational and Research Hospital, Izmir, Turkey
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12
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Sarioglu O, Sarioglu FC, Capar AE, Sokmez DFB, Topkaya P, Belet U. The role of CT texture analysis in predicting the clinical outcomes of acute ischemic stroke patients undergoing mechanical thrombectomy. Eur Radiol 2021; 31:6105-6115. [PMID: 33559698 DOI: 10.1007/s00330-021-07720-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Revised: 12/19/2020] [Accepted: 01/27/2021] [Indexed: 12/13/2022]
Abstract
OBJECTIVES To evaluate the performance of CT-based texture analysis (TA) for predicting clinical outcomes of mechanical thrombectomy (MT) in acute ischemic stroke (AIS). METHODS This single-center, retrospective study contained 64 consecutive patients with AIS who underwent MT for large anterior circulation occlusion between December 2016 and January 2020. Patients were divided into 2 groups according to the modified Rankin scale (mRS) scores at 3 months as good outcome (mRS ≤ 2) and bad outcome (mRS > 2). Two observers examined the early ischemic changes for TA on baseline non-contrast CT images independently. Demographic, clinical, periprocedural, and texture variables were compared between the groups and ROC curves were made. Logistic regression analysis was used and a model was created to determine the independent predictors of a bad outcome. RESULTS Sixty-four patients (32 female, 32 male; mean age 63.03 ± 14.42) were included in the study. Fourteen texture parameters were significantly different between patients with good and bad outcomes. The long-run high gray-level emphasis (LRHGE), which is a gray-level run-length matrix (GLRLM) feature, showed the highest sensitivity (80%) and specificity (70%) rates to predict disability. The GLRLM_LRHGE value of > 4885.0 and the time from onset to puncture of > 237.5 mi were found as independent predictors of the bad outcome. The diagnostic rate was 80.0% when using the combination of the GLRLM_LRHGE and the time from onset to puncture cutoff values. CONCLUSION CT-based TA might be a promising modality to predict clinical outcome after MT in patients with AIS. KEY POINTS • The gray-level run-length matrix parameters displayed higher diagnostic performance among the texture features. • The long-run high gray-level emphasis showed the highest sensitivity and specificity rates for predicting a bad outcome in stroke patients undergoing mechanical thrombectomy. • The gray-level run-length matrix_long-run high gray-level emphasis value of > 4885.0 (OR = 11.06; 95% CI = 2.51 - 48.77; p = 0.001) and the time from onset to puncture of > 237.5 min (OR = 8.55; 95% CI = 1.96 - 37.21; p = 0.004) were found as independent predictors of the bad outcome.
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Affiliation(s)
- Orkun Sarioglu
- Department of Radiology, Health Sciences University, Tepecik Educational and Research Hospital, 35180 Yenisehir, Konak, Izmir, Turkey.
| | - Fatma Ceren Sarioglu
- Department of Radiology, Dokuz Eylul University School of Medicine, Izmir, Turkey
| | - Ahmet Ergin Capar
- Department of Radiology, Health Sciences University, Tepecik Educational and Research Hospital, 35180 Yenisehir, Konak, Izmir, Turkey
| | - Demet Funda Bas Sokmez
- Department of Neurology, Health Sciences University, Tepecik Educational and Research Hospital, Izmir, Turkey
| | - Pelin Topkaya
- Department of Neurology, Health Sciences University, Tepecik Educational and Research Hospital, Izmir, Turkey
| | - Umit Belet
- Department of Radiology, Health Sciences University, Tepecik Educational and Research Hospital, 35180 Yenisehir, Konak, Izmir, Turkey
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