1
|
Luo D, Qiu C, Zhou R, Shan T, Yan W, Yang J. Clinical study of magnetic resonance imaging-based texture analysis and fasciculation of the lateral pterygoid muscle in young patients with temporomandibular disorder. Oral Surg Oral Med Oral Pathol Oral Radiol 2023; 136:382-393. [PMID: 37357069 DOI: 10.1016/j.oooo.2023.05.002] [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: 12/07/2022] [Revised: 04/19/2023] [Accepted: 05/06/2023] [Indexed: 06/27/2023]
Abstract
OBJECTIVE We aimed to evaluate the effectiveness of clinical examination combined with texture analysis of magnetic resonance imaging (MRI) and fasciculation patterns of the lateral pterygoid muscle (LPM) in distinguishing among the different anatomic causes of temporomandibular disorder. METHODS We divided the patients into four groups: healthy control (HC), disk without displacement (DWoD), disk displacement with reduction (DDWR), and disk displacement without reduction (DDWoR). Demographic information and clinical symptoms of patients in each group were recorded. LPM textures were compared among groups. LPM fasciculation was examined. P<0.05 indicated significant difference. RESULTS Several clinical symptoms and signs, but not age or sex, differed significantly among groups. Oblique sagittal planar MRI revealed significant differences in the parameters of Angular Second Moment, Contrast, Correlation, Inverse Difference Moment, and Entropy between the healthy controls and the 3 patient groups. MRI of the patients, both without and with disk displacement, demonstrated relative uniformity in gray distribution and correlation of gray values, with greater complexity but an unclear texture and no obvious regularity. The proportion of type B LPM fascicles was significantly higher in the DDWR and DDWoR groups CONCLUSION: Temporomandibular disorder, without and with disk displacement, is associated with clinical symptoms and texture analysis values that differ from healthy muscle. The types of LPM fascicles are related to the position of the articular disk.
Collapse
Affiliation(s)
- Dan Luo
- Department of Oral and Maxillofacial Surgery, The Affiliated Hospital of Qingdao University, Shandong, China; School of Stomatology of Qingdao University, Shandong, China; Dental Digital Medicine and 3D Printing Engineering Laboratory of Qingdao University, Shandong, China
| | - Cheng Qiu
- Department of Orthopaedic Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Shandong, China; Cheeloo College of Medicine, Shandong University, Shandong, China
| | - Ruizhi Zhou
- Department of Radiology, The Affiliated Hospital of Qingdao University, Shandong, China
| | - Tao Shan
- School of Basic Medicine, Qingdao University, Shandong, China
| | - Wenjing Yan
- Department of Neurology, The Affiliated Hospital of Qingdao University, Shandong, China
| | - Jianjun Yang
- Department of Oral and Maxillofacial Surgery, The Affiliated Hospital of Qingdao University, Shandong, China.
| |
Collapse
|
2
|
Fischer M, Küstner T, Pappa S, Niendorf T, Pischon T, Kröncke T, Bette S, Schramm S, Schmidt B, Haubold J, Nensa F, Nonnenmacher T, Palm V, Bamberg F, Kiefer L, Schick F, Yang B. Identification of radiomic biomarkers in a set of four skeletal muscle groups on Dixon MRI of the NAKO MR study. BMC Med Imaging 2023; 23:104. [PMID: 37553619 PMCID: PMC10408104 DOI: 10.1186/s12880-023-01056-9] [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: 02/15/2023] [Accepted: 07/18/2023] [Indexed: 08/10/2023] Open
Abstract
In this work, we propose a processing pipeline for the extraction and identification of meaningful radiomics biomarkers in skeletal muscle tissue as displayed using Dixon-weighted MRI. Diverse and robust radiomics features can be identified that may be of aid in the accurate quantification e.g. varying degrees of sarcopenia in respective muscles of large cohorts. As such, the approach comprises the texture feature extraction from raw data based on well established approaches, such as a nnU-Net neural network and the Pyradiomics toolbox, a subsequent selection according to adequate conditions for the muscle tissue of the general population, and an importance-based ranking to further narrow the amount of meaningful features with respect to auxiliary targets. The performance was investigated with respect to the included auxiliary targets, namely age, body mass index (BMI), and fat fraction (FF). Four skeletal muscles with different fiber architecture were included: the mm. glutaei, m. psoas, as well as the extensors and adductors of the thigh. The selection allowed for a reduction from 1015 available texture features to 65 for age, 53 for BMI, and 36 for FF from the available fat/water contrast images considering all muscles jointly. Further, the dependence of the importance rankings calculated for the auxiliary targets on validation sets (in a cross-validation scheme) was investigated by boxplots. In addition, significant differences between subgroups of respective auxiliary targets as well as between both sexes were shown to be present within the ten lowest ranked features by means of Kruskal-Wallis H-tests and Mann-Whitney U-tests. The prediction performance for the selected features and the ranking scheme were verified on validation sets by a random forest based multi-class classification, with strong area under the curve (AUC) values of the receiver operator characteristic (ROC) of 73.03 ± 0.70 % and 73.63 ± 0.70 % for the water and fat images in age, 80.68 ± 0.30 % and 88.03 ± 0.89 % in BMI, as well as 98.36 ± 0.03 % and 98.52 ± 0.09 % in FF.
Collapse
Affiliation(s)
- Marc Fischer
- Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany
| | - Thomas Küstner
- Medical Image and Data Analysis (MIDAS.lab), University Hospital Tübingen, Tübingen, Germany.
| | - Sofia Pappa
- Section on Experimental Radiology, University Hospital Tübingen, Tübingen, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück-Center for Molecular Medicine, Berlin, Germany
| | - Tobias Pischon
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrück-Center for Molecular Medicine, Berlin, Germany
| | - Thomas Kröncke
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Augsburg, Germany
- Centre for Advanced Analytics and Predictive Sciences (CAAPS), University Augsburg, Augsburg, Germany
| | - Stefanie Bette
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Augsburg, Germany
| | - Sara Schramm
- Institute for Medical Informatics, Biometry and Epidemiology, Essen University Hospital, Essen, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, Essen University Hospital, Essen, Germany
| | | | | | | | | | | | - Lena Kiefer
- Department of Radiology, University Hospital Tübingen, Tübingen, Germany
| | - Fritz Schick
- Section on Experimental Radiology, University Hospital Tübingen, Tübingen, Germany
| | - Bin Yang
- Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany
| |
Collapse
|
3
|
Astrea G, Morrow JM, Manzur A, Gunny R, Battini R, Mercuri E, Reilly MM, Muntoni F, Yousry TA. Muscle "islands": An MRI signature distinguishing neurogenic from myopathic causes of early onset distal weakness. Neuromuscul Disord 2021; 32:142-149. [PMID: 35033413 DOI: 10.1016/j.nmd.2021.11.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 10/12/2021] [Accepted: 11/10/2021] [Indexed: 10/19/2022]
Abstract
Muscle MRI has an increasing role in diagnosis of inherited neuromuscular diseases, but no features are known which reliably differentiate myopathic and neurogenic conditions. Using patients presenting with early onset distal weakness, we aimed to identify an MRI signature to distinguish myopathic and neurogenic conditions. We identified lower limb MRI scans from patients with either genetically (n = 24) or clinically (n = 13) confirmed diagnoses of childhood onset distal myopathy or distal spinal muscular atrophy. An initial exploratory phase reviewed 11 scans from genetically confirmed patients identifying a single potential discriminatory marker concerning the pattern of fat replacement within muscle, coined "islands". This pattern comprised small areas of muscle tissue with normal signal intensity completely surrounded by areas with similar intensity to subcutaneous fat. In the subsequent validation phase, islands correctly classified scans from all 12 remaining genetically confirmed patients, and 12/13 clinically classified patients. In the genetically confirmed patients MRI classification of neurogenic/myopathic aetiology had 100% accuracy (24/24) compared with 65% accuracy (15/23) for EMG, and 79% accuracy (15/19) for muscle biopsy. Future studies are needed in other clinical contexts, however the presence of islands appears to highly suggestive of a neurogenic aetiology in patients presenting with early onset distal motor weakness.
Collapse
Affiliation(s)
- Guja Astrea
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy; Dubowitz Neuromuscular Center, UCL GOS Institute of Child Health, UK
| | - Jasper M Morrow
- Queen Square Center for Neuromuscular Diseases, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK.
| | - Adnan Manzur
- Dubowitz Neuromuscular Center, UCL GOS Institute of Child Health, UK
| | - Roxana Gunny
- Paediatric neuroradiology, Sidra Medicine, Qatar
| | - Roberta Battini
- Department of Developmental Neuroscience, IRCCS Stella Maris, Calambrone, Pisa, Italy; Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Eugenio Mercuri
- Department of Pediatric Neurology, Catholic University, Rome, Italy; Centro Clinico Nemo, Policlinico Universitario A Gemelli IRCCS, Rome, Italy
| | - Mary M Reilly
- Queen Square Center for Neuromuscular Diseases, National Hospital for Neurology and Neurosurgery, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Francesco Muntoni
- NIHR Great Ormond Street Hospital Biomedical Research Center, Great Ormond Street Institute of Child Health University College London and Great Ormond Street Hospital Trust, London, UK
| | - Tarek A Yousry
- Neuroradiological Academic Unit, Queen Square UCL Institute of Neurology and Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, UCLH, London, UK
| |
Collapse
|
4
|
Gómez-Andrés D, Oulhissane A, Quijano-Roy S. Two decades of advances in muscle imaging in children: from pattern recognition of muscle diseases to quantification and machine learning approaches. Neuromuscul Disord 2021; 31:1038-1050. [PMID: 34736625 DOI: 10.1016/j.nmd.2021.08.006] [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: 07/27/2021] [Revised: 07/30/2021] [Accepted: 08/01/2021] [Indexed: 11/29/2022]
Abstract
Muscle imaging has progressively gained popularity in the neuromuscular field. Together with detailed clinical examination and muscle biopsy, it has become one of the main tools for deep phenotyping and orientation of etiological diagnosis. Even in the current era of powerful new generation sequencing, muscle MRI has arisen as a tool for prioritization of certain genetic entities, supporting the pathogenicity of variants of unknown significance and facilitating diagnosis in cases with an initially inconclusive genetic study. Although the utility of muscle imaging is increasingly clear, it has not reached its full potential in clinical practice. Pattern recognition is known for a number of diseases and will certainly be enhanced by the use of machine learning approaches. For instance, MRI heatmap representations might be confronted with molecular results by obtaining a probabilistic diagnosis based in each disease "MRI fingerprints". Muscle ultrasound as a screening tool and quantified techniques such as Dixon MRI seem still underdeveloped. In this paper, we aim to appraise the advances in recent years in pediatric muscle imaging and try to define areas of uncertainty and potential advances that might become standardized to be widely used in the future.
Collapse
Affiliation(s)
- David Gómez-Andrés
- Pediatric Neurology, Vall d'Hebron Institut de Recerca (VHIR), Hospital Universitari Vall d'Hebron, ERN-RND - EURO-NMD, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain; European Network for Reference Centers on Neuromuscular Disorders (Euro-NMD ERN)
| | - Amal Oulhissane
- Université Paris-Saclay, APHP, Neuromuscular Unit, Pediatric Neurology and ICU Department, Raymond Poincaré Hospital, 92390 Garches, France
| | - Susana Quijano-Roy
- Université Paris-Saclay, APHP, Neuromuscular Unit, Pediatric Neurology and ICU Department, Raymond Poincaré Hospital, 92390 Garches, France; UMR 1179, Laboratoire handicap neuromusculaire: physiopathologie biothérapie pharmacologie appliquées (END-ICAP), UFR Simone Veil, Montigny Le Bretonneux, France; French Network of Neuromuscular Reference Centers (FILNEMUS), France.
| |
Collapse
|
5
|
Akinci D'Antonoli T, Santini F, Deligianni X, Garcia Alzamora M, Rutz E, Bieri O, Brunner R, Weidensteiner C. Combination of Quantitative MRI Fat Fraction and Texture Analysis to Evaluate Spastic Muscles of Children With Cerebral Palsy. Front Neurol 2021; 12:633808. [PMID: 33828520 PMCID: PMC8019698 DOI: 10.3389/fneur.2021.633808] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 03/01/2021] [Indexed: 12/24/2022] Open
Abstract
Background: Cerebral palsy (CP) is the most common cause of physical disability in childhood. Muscle pathologies occur due to spasticity and contractures; therefore, diagnostic imaging to detect pathologies is often required. Imaging has been used to assess torsion or estimate muscle volume, but additional methods for characterizing muscle composition have not thoroughly been investigated. MRI fat fraction (FF) measurement can quantify muscle fat and is often a part of standard imaging in neuromuscular dystrophies. To date, FF has been used to quantify muscle fat and assess function in CP. In this study, we aimed to utilize a radiomics and FF analysis along with the combination of both methods to differentiate affected muscles from healthy ones. Materials and Methods: A total of 9 patients (age range 8-15 years) with CP and 12 healthy controls (age range 9-16 years) were prospectively enrolled (2018-2020) after ethics committee approval. Multi-echo Dixon acquisition of the calf muscles was used for FF calculation. The images of the second echo (TE = 2.87 ms) were used for feature extraction from the soleus, gastrocnemius medialis, and gastrocnemius lateralis muscles. The least absolute shrinkage and selection operator (LASSO) regression was employed for feature selection. RM, FF model (FFM), and combined model (CM) were built for each calf muscle. The receiver operating characteristic (ROC) curve and their respective area under the curve (AUC) values were used to evaluate model performance. Results: In total, the affected legs of 9 CP patients and the dominant legs of 12 healthy controls were analyzed. The performance of RM for soleus, gastrocnemius medialis, and gastrocnemius lateralis (AUC 0.92, 0.92, 0.82, respectively) was better than the FFM (AUC 0.88, 0.85, 0.69, respectively). The combination of both models always had a better performance than RM or FFM (AUC 0.95, 0.93, 0.83). FF was higher in the patient group (FFS 9.1%, FFGM 8.5%, and FFGL 10.2%) than control group (FFS 3.3%, FFGM 4.1%, FFGL 6.6%). Conclusion: The combination of MRI quantitative fat fraction analysis and texture analysis of muscles is a promising tool to evaluate muscle pathologies due to CP in a non-invasive manner.
Collapse
Affiliation(s)
- Tugba Akinci D'Antonoli
- Department of Pediatric Radiology, University Children's Hospital Basel, Basel, Switzerland
- Department of Radiology, University Hospital of Basel, Basel, Switzerland
| | - Francesco Santini
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Xeni Deligianni
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Meritxell Garcia Alzamora
- Department of Radiology, University Hospital of Basel, Basel, Switzerland
- Division of Diagnostic and Interventional Neuroradiology, University Hospital of Basel, Basel, Switzerland
| | - Erich Rutz
- Pediatric Orthopedic Department, Murdoch Children's Research Institute, The Royal Children's Hospital, MCRI the University of Melbourne, Melbourne, VIC, Australia
- Faculty of Medicine, The University of Basel, Basel, Switzerland
| | - Oliver Bieri
- Department of Pediatric Radiology, University Children's Hospital Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland
| | - Reinald Brunner
- University Children's Hospital Basel, Basel, Switzerland
- Department of Orthopedic Surgery, University Children's Hospital Basel, Basel, Switzerland
| | - Claudia Weidensteiner
- Division of Radiological Physics, Department of Radiology, University Hospital of Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| |
Collapse
|
6
|
Lee JH, Yoon YC, Kim HS, Kim JH, Choi BO. Texture analysis using T1-weighted images for muscles in Charcot-Marie-Tooth disease patients and volunteers. Eur Radiol 2020; 31:3508-3517. [PMID: 33125561 DOI: 10.1007/s00330-020-07435-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 09/08/2020] [Accepted: 10/15/2020] [Indexed: 01/30/2023]
Abstract
OBJECTIVES To explore whether texture features using T1-weighted images correlate with fat fraction, and whether they differ between Charcot-Marie-Tooth (CMT) disease patients and volunteers. METHODS The institutional review board approved this retrospective study, and the requirement for informed consent was waived; data of eighteen CMT patients and eighteen healthy volunteers from a previous study was used. Texture features of the muscles including mean, standard deviation (SD), skewness, kurtosis, and entropy of the signal intensity were derived from T1-weighted images. Spearman's correlation analysis was used to assess the relationship between texture features and fat fraction measured by 3D multiple gradient echo Dixon-based sequence. Mann-Whitney U test was used to compare the texture features between CMT patients and volunteers. Intraobserver and interobserver agreements for the texture features were assessed using the intraclass correlation coefficient. RESULTS The SD (ρ = 0.256, p < 0.001) and entropy (ρ = 0.263, p < 0.001) were significantly and positively correlated with fat fraction; skewness (ρ = - 0.110, p = 0.027) and kurtosis (ρ = - 0.149, p = 0.003) were significantly and inversely correlated with fat fraction. The CMT patients showed a significantly higher SD (63.45 vs. 49.26; p < 0.001), skewness (1.06 vs. 0.56; p < 0.001), kurtosis (4.00 vs. 1.81; p < 0.001), and entropy (3.20 vs. 3.02; p < 0.001) than did the volunteers. Intraobserver and interobserver agreements were almost perfect for mean, SD, and entropy. CONCLUSIONS Texture features using T1-weighted images correlated with fat fraction and differed between CMT patients and volunteers. KEY POINTS • Standard deviation and entropy of muscles derived from T1-weighted images were significantly and positively correlated with the muscle fat fraction. • Mean, standard deviation, and entropy were considered highly reliable in muscle analyses. • Texture features may have the potential to diagnose early stage of intramuscular fatty infiltration.
Collapse
Affiliation(s)
- Ji Hyun Lee
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-Ro, Gangnam-gu, Seoul, 06351, South Korea
| | - Young Cheol Yoon
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-Ro, Gangnam-gu, Seoul, 06351, South Korea.
| | - Hyun Su Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-Ro, Gangnam-gu, Seoul, 06351, South Korea
| | - Jae-Hun Kim
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-Ro, Gangnam-gu, Seoul, 06351, South Korea
| | - Byung-Ok Choi
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Ilwon-Ro, Gangnam-gu, Seoul, 06351, South Korea
| |
Collapse
|
7
|
MRI radiomics for the prediction of recurrence in patients with clinically non-functioning pituitary macroadenomas. Comput Biol Med 2020; 124:103966. [DOI: 10.1016/j.compbiomed.2020.103966] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 07/31/2020] [Accepted: 08/08/2020] [Indexed: 11/21/2022]
|
8
|
Paoletti M, Pichiecchio A, Cotti Piccinelli S, Tasca G, Berardinelli AL, Padovani A, Filosto M. Advances in Quantitative Imaging of Genetic and Acquired Myopathies: Clinical Applications and Perspectives. Front Neurol 2019; 10:78. [PMID: 30804884 PMCID: PMC6378279 DOI: 10.3389/fneur.2019.00078] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 01/21/2019] [Indexed: 12/11/2022] Open
Abstract
In the last years, magnetic resonance imaging (MRI) has become fundamental for the diagnosis and monitoring of myopathies given its ability to show the severity and distribution of pathology, to identify specific patterns of damage distribution and to properly interpret a number of genetic variants. The advances in MR techniques and post-processing software solutions have greatly expanded the potential to assess pathological changes in muscle diseases, and more specifically of myopathies; a number of features can be studied and quantified, ranging from composition, architecture, mechanical properties, perfusion, and function, leading to what is known as quantitative MRI (qMRI). Such techniques can effectively provide a variety of information beyond what can be seen and assessed by conventional MR imaging; their development and application in clinical practice can play an important role in the diagnostic process and in assessing disease course and treatment response. In this review, we briefly discuss the current role of muscle MRI in diagnosing muscle diseases and describe in detail the potential and perspectives of the application of advanced qMRI techniques in this field.
Collapse
Affiliation(s)
- Matteo Paoletti
- Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Anna Pichiecchio
- Neuroradiology Department, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Stefano Cotti Piccinelli
- Unit of Neurology, Center for Neuromuscular Diseases, ASST Spedali Civili and University of Brescia, Brescia, Italy
| | - Giorgio Tasca
- Neurology Department, Dipartimento di Scienze dell'Invecchiamento, Neurologiche, Ortopediche e della Testa-Collo, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy
| | | | - Alessandro Padovani
- Unit of Neurology, Center for Neuromuscular Diseases, ASST Spedali Civili and University of Brescia, Brescia, Italy
| | - Massimiliano Filosto
- Unit of Neurology, Center for Neuromuscular Diseases, ASST Spedali Civili and University of Brescia, Brescia, Italy
| |
Collapse
|
9
|
Désert R, Nieto N, Musso O. Dimensions of hepatocellular carcinoma phenotypic diversity. World J Gastroenterol 2018; 24:4536-4547. [PMID: 30386103 PMCID: PMC6209578 DOI: 10.3748/wjg.v24.i40.4536] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 08/31/2018] [Accepted: 10/05/2018] [Indexed: 02/06/2023] Open
Abstract
Hepatocellular carcinoma (HCC) is the 3rd leading cause of cancer-related death worldwide. More than 80% of HCCs arise within chronic liver disease resulting from viral hepatitis, alcohol, hemochromatosis, obesity and metabolic syndrome or genotoxins. Projections based on Western lifestyle and its metabolic consequences anticipate a further increase in incidence, despite recent breakthroughs in the management of viral hepatitis. HCCs display high heterogeneity of molecular phenotypes, which challenges clinical management. However, emerging molecular classifications of HCCs have not yet formed a unified corpus translatable to the clinical practice. Thus, patient management is currently based upon tumor number, size, vascular invasion, performance status and functional liver reserve. Nonetheless, an impressive body of molecular evidence emerged within the last 20 years and is becoming increasingly available to medical practitioners and researchers in the form of repositories. Therefore, the aim this work is to review molecular data underlying HCC classifications and to organize this corpus into the major dimensions explaining HCC phenotypic diversity. Major efforts have been recently made worldwide toward a unifying “clinically-friendly” molecular landscape. As a result, a consensus emerges on three major dimensions explaining the HCC heterogeneity. In the first dimension, tumor cell proliferation and differentiation enabled allocation of HCCs to two major classes presenting profoundly different clinical aggressiveness. In the second dimension, HCC microenvironment and tumor immunity underlie recent therapeutic breakthroughs prolonging patients’ survival. In the third dimension, metabolic reprogramming, with the recent emergence of subclass-specific metabolic profiles, may lead to adaptive and combined therapeutic approaches. Therefore, here we review recent molecular evidence, their impact on tumor histopathological features and clinical behavior and highlight the remaining challenges to translate our cognitive corpus into patient diagnosis and allocation to therapeutic options.
Collapse
Affiliation(s)
- Romain Désert
- Institut NuMeCan, Université de Rennes 1, Institut national de la recherche agronomique (INRA), Institut national de la santé et de la recherche médicale (INSERM), Rennes F-35000, France
- Department of Pathology, Department of Medicine (Gastroenterology and Hepatology), University of Illinois at Chicago, IL 60612, United States
| | - Natalia Nieto
- Department of Pathology, Department of Medicine (Gastroenterology and Hepatology), University of Illinois at Chicago, IL 60612, United States
| | - Orlando Musso
- Institut NuMeCan, Université de Rennes 1, Institut national de la recherche agronomique (INRA), Institut national de la santé et de la recherche médicale (INSERM), Rennes F-35000, France
| |
Collapse
|
10
|
Correlation of texture analysis of paraspinal musculature on MRI with different clinical endpoints: Lumbar Stenosis Outcome Study (LSOS). Eur Radiol 2018; 29:22-30. [DOI: 10.1007/s00330-018-5552-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Revised: 05/09/2018] [Accepted: 05/21/2018] [Indexed: 01/03/2023]
|
11
|
Chen Z, Chen X, Liu M, Liu S, Yu S, Ma L. Magnetic Resonance Image Texture Analysis of the Periaqueductal Gray Matter in Episodic Migraine Patients without T2-Visible Lesions. Korean J Radiol 2018; 19:85-92. [PMID: 29354004 PMCID: PMC5768512 DOI: 10.3348/kjr.2018.19.1.85] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 07/16/2017] [Indexed: 01/03/2023] Open
Abstract
Objective The periaqueductal gray matter (PAG), a small midbrain structure, presents dysfunction in migraine. However, the precise neurological mechanism is still not well understood. Herein, the aim of this study was to investigate the texture characteristics of altered PAG in episodic migraine (EM) patients based on high resolution brain structural magnetic resonance (MR) images. Materials and Methods The brain structural MR images were obtained from 18 normal controls (NC), 18 EM patients and 16 chronic migraine (CM) patients using a 3T MR system. A PAG template was created using the International Consortium Brain Mapping 152 gray matter model, and the individual PAG segment was developed by applying the deformation field from the structural image segment to the PAG template. A grey level co-occurrence matrix was used to calculate the texture parameters including the angular second moment (ASM), contrast, correlation, inverse difference moment (IDM) and entropy. Results There was a significant difference for ASM, IDM and entropy in the EM group (998.629 ± 0.162 × 10−3, 999.311 ± 0.073 × 10−3, 916.354 ± 0.947 × 10−5) compared to that found in the NC group (998.760 ± 0.110 × 10−3, 999.358 ± 0.037 × 10−3 and 841.198 ± 0.575 × 10−5) (p < 0.05). The entropy was significantly lower among the patients with CM (864.116 ± 0.571 × 10−5) than that found among patients with EM (p < 0.05). The area under the receiver operating characteristic curve was 0.776 and 0.750 for ASM and entropy in the distinction of the EM from NC groups, respectively. ASM was negatively related to disease duration (DD) and the Migraine Disability Assessment Scale (MIDAS) scores in the EM group, and entropy was positively related to DD and MIDAS in the EM group (p < 0.05). Conclusion The present study identified altered MR image texture characteristics of the PAG in EM. The identified texture characteristics could be considered as imaging biomarkers for EM.
Collapse
Affiliation(s)
- Zhiye Chen
- Department of Radiology, Chinese PLA General Hospital, Beijing 100853, China.,Department of Neurology, Chinese PLA General Hospital, Beijing 100853, China.,Department of Radiology, Hainan Branch of Chinese PLA General Hospital, Sanya 572013, China
| | - Xiaoyan Chen
- Department of Neurology, Chinese PLA General Hospital, Beijing 100853, China
| | - Mengqi Liu
- Department of Radiology, Chinese PLA General Hospital, Beijing 100853, China.,Department of Radiology, Hainan Branch of Chinese PLA General Hospital, Sanya 572013, China
| | - Shuangfeng Liu
- Department of Radiology, Chinese PLA General Hospital, Beijing 100853, China
| | - Shengyuan Yu
- Department of Neurology, Chinese PLA General Hospital, Beijing 100853, China
| | - Lin Ma
- Department of Radiology, Chinese PLA General Hospital, Beijing 100853, China
| |
Collapse
|
12
|
Chen Z, Chen X, Liu M, Liu S, Ma L, Yu S. Texture features of periaqueductal gray in the patients with medication-overuse headache. J Headache Pain 2017; 18:14. [PMID: 28155029 PMCID: PMC5289934 DOI: 10.1186/s10194-017-0727-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2017] [Accepted: 01/20/2017] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND Periaqueductal gray (PAG) is the descending pain modulatory center, and PAG dysfunction had been recognized in migraine. Here we propose to investigate altered PAG texture features (quantitative approach for extracting texture descriptors for images) in the patients with medication-overuse headache (MOH) based on high resolution brain structural image to understand the MOH pathogenesis. METHODS The brain structural images were obtained from 32 normal controls (NC) and 44 MOH patients on 3.0 T MR system. PAG template was created based on the ICBM152 gray matter template, and the individual PAG segment was performed by applying the deformation field to the PAG template after structural image segment. Grey-level co-occurrence matrix (GLCM) was performed to measure the texture parameters including angular second moment (ASM), Contrast, Correlation, inverse difference moment (IDM) and Entropy. RESULTS Contrast was increased in MOH patients (9.28 ± 3.11) compared with that in NC (7.94 ± 0.65) (P < 0.05), and other texture features showed no significant difference between MOH and NC (P > 0.05). The area under the ROC curve was 0.697 for Contrast in the distinction of MOH from NC, and the cut-off value of Contrast was 8.11 with sensitivity 70.5% and specificity 62.5%. The contrast was negatively with the sleep scores (r = -0.434, P = 0.003). CONCLUSION Texture Contrast could be used to identify the altered MR imaging characteristics in MOH in understanding the MOH pathogenesis, and it could also be considered as imaging biomarker in for MOH diagnosis.
Collapse
Affiliation(s)
- Zhiye Chen
- Department of Radiology, Chinese PLA General Hospital, Beijing, 100853, China.,Department of Neurology, Chinese PLA General Hospital, Beijing, 100853, China.,Department of Radiology, Hainan Branch of Chinese PLA General Hospital, Beijing, 100853, China
| | - Xiaoyan Chen
- Department of Neurology, Chinese PLA General Hospital, Beijing, 100853, China
| | - Mengqi Liu
- Department of Radiology, Chinese PLA General Hospital, Beijing, 100853, China.,Department of Radiology, Hainan Branch of Chinese PLA General Hospital, Beijing, 100853, China
| | - Shuangfeng Liu
- Department of Radiology, Chinese PLA General Hospital, Beijing, 100853, China
| | - Lin Ma
- Department of Radiology, Chinese PLA General Hospital, Beijing, 100853, China.
| | - Shengyuan Yu
- Department of Neurology, Chinese PLA General Hospital, Beijing, 100853, China.
| |
Collapse
|
13
|
Santos TA, Maistro CEB, Silva CB, Oliveira MS, França MC, Castellano G. MRI Texture Analysis Reveals Bulbar Abnormalities in Friedreich Ataxia. AJNR Am J Neuroradiol 2015; 36:2214-8. [PMID: 26359147 PMCID: PMC7964265 DOI: 10.3174/ajnr.a4455] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Accepted: 05/18/2015] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND PURPOSE Texture analysis is an image processing technique that can be used to extract parameters able to describe meaningful features of an image or ROI. Texture analysis based on the gray level co-occurrence matrix gives a second-order statistical description of the image or ROI. In this work, the co-occurrence matrix texture approach was used to extract information from brain MR images of patients with Friedreich ataxia and a control group, to see whether texture parameters were different between these groups. A longitudinal analysis was also performed. MATERIALS AND METHODS Twenty patients and 21 healthy controls participated in the study. Both groups had 2 sets of T1-weighted MR images obtained 1 year apart for every subject. ROIs chosen for analysis were the medulla oblongata and pons. Texture parameters were obtained for these ROIs for every subject, for the 2 sets of images. These parameters were compared longitudinally within groups and transversally between groups. RESULTS The comparison between patients and the control group showed a significant differences for the medulla oblongata (t test, P < .05, Bonferroni-corrected) but did not show a statistically significant difference for the pons. Longitudinal comparison of images obtained 1 year apart did not show differences for either patients or for controls, in any of the analyzed structures. CONCLUSIONS Gray level co-occurrence matrix-based texture analysis showed statistically significant differences for the medulla oblongata of patients with Friedreich ataxia compared with controls. These results highlight the medulla as an important site of damage in Friedreich ataxia.
Collapse
Affiliation(s)
- T A Santos
- From the Neurophysics Group (T.A.S., C.E.B.M., M.S.O., G.C.), Gleb Wataghin Physics Institute Brazilian Institute of Neuroscience and Neurotechnology (BRAINN) (São Paulo Research Foundation) (T.A.S., C.E.B.M., C.B.S., M.S.O., M.C.F., G.C.), Campinas, São Paulo, Brazil
| | - C E B Maistro
- From the Neurophysics Group (T.A.S., C.E.B.M., M.S.O., G.C.), Gleb Wataghin Physics Institute Brazilian Institute of Neuroscience and Neurotechnology (BRAINN) (São Paulo Research Foundation) (T.A.S., C.E.B.M., C.B.S., M.S.O., M.C.F., G.C.), Campinas, São Paulo, Brazil
| | - C B Silva
- Department of Neurology (C.B.S., M.C.F.), Medical Sciences School, University of Campinas, Brazil Brazilian Institute of Neuroscience and Neurotechnology (BRAINN) (São Paulo Research Foundation) (T.A.S., C.E.B.M., C.B.S., M.S.O., M.C.F., G.C.), Campinas, São Paulo, Brazil
| | - M S Oliveira
- From the Neurophysics Group (T.A.S., C.E.B.M., M.S.O., G.C.), Gleb Wataghin Physics Institute Brazilian Institute of Neuroscience and Neurotechnology (BRAINN) (São Paulo Research Foundation) (T.A.S., C.E.B.M., C.B.S., M.S.O., M.C.F., G.C.), Campinas, São Paulo, Brazil
| | - M C França
- Department of Neurology (C.B.S., M.C.F.), Medical Sciences School, University of Campinas, Brazil Brazilian Institute of Neuroscience and Neurotechnology (BRAINN) (São Paulo Research Foundation) (T.A.S., C.E.B.M., C.B.S., M.S.O., M.C.F., G.C.), Campinas, São Paulo, Brazil
| | - G Castellano
- From the Neurophysics Group (T.A.S., C.E.B.M., M.S.O., G.C.), Gleb Wataghin Physics Institute Brazilian Institute of Neuroscience and Neurotechnology (BRAINN) (São Paulo Research Foundation) (T.A.S., C.E.B.M., C.B.S., M.S.O., M.C.F., G.C.), Campinas, São Paulo, Brazil.
| |
Collapse
|