scholarly journals Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lee Curtin ◽  
Paula Whitmire ◽  
Haylye White ◽  
Kamila M. Bond ◽  
Maciej M. Mrugala ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Tumor Location ◽  
Primary Brain Tumor ◽  
Resonance Imaging ◽  
Significant Relationships ◽  
Biological Phenomena ◽  
Microenvironmental Factors ◽  
Magnetic Resonance Imaging Mri ◽  
The Relationship ◽  
Standard Magnetic Resonance Imaging

AbstractLacunarity, a quantitative morphological measure of how shapes fill space, and fractal dimension, a morphological measure of the complexity of pixel arrangement, have shown relationships with outcome across a variety of cancers. However, the application of these metrics to glioblastoma (GBM), a very aggressive primary brain tumor, has not been fully explored. In this project, we computed lacunarity and fractal dimension values for GBM-induced abnormalities on clinically standard magnetic resonance imaging (MRI). In our patient cohort (n = 402), we connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension on necrotic regions (n = 390), all abnormalities present on T1Gd MRI (n = 402), and abnormalities present on T2/FLAIR MRI (n = 257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome for all three imaging regions that we tested, with the shape of T2/FLAIR abnormalities that are typically associated with edema showing the strongest relationship with overall survival. This link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.

scholarly journals NIMG-07. LACUNARITY AND FRACTAL DIMENSION ACT AS PRETREATMENT IMAGING BIOMARKERS FOR SURVIVAL IN GLIOBLASTOMA PATIENTS

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi162-vi163
Author(s):  
Lee Curtin ◽  
Paula Whitmire ◽  
Haylye White ◽  
Maciej Mrugala ◽  
Leland Hu ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Progression Free Survival ◽  
Standard Of Care ◽  
Primary Brain Tumor ◽  
Imaging Biomarkers ◽  
Free Survival ◽  
Patient Cohort ◽  
Biological Phenomena ◽  
Microenvironmental Factors ◽  
Standard Of Care Treatment

Abstract Glioblastoma (GBM) is the most aggressive primary brain tumor with a median survival of only 15 months with standard of care treatment. Lacunarity, a quantitative morphological measure of how shapes fill space, and fractal dimension, another morphological measure of the complexity of pixel arrangement, of segmented necrotic regions on gadolinium-enhanced T1 weighted (T1gd) MRI have previously been shown to distinguish both overall survival (OS) and progression free survival (PFS) in GBM (n = 95). In our larger patient cohort (n = 389), we sought to validate or refute previously published results connecting morphological metrics and patient survival. We identified pretreatment necrotic regions of our retrospective first-diagnosis GBM patient cohort using segmented T1gd MRI enhancing regions. We calculated lacunarity and fractal dimension across all T1gd MRI slices with enhancing tumor, and used the median lacunarity and fractal dimension values for our analysis. We find that a lacunarity threshold can significantly distinguish OS (14 months vs 19 months median, log-rank p = 0.015, n = 389) and a fractal dimension threshold can significantly distinguish PFS (8 months vs 11 months median, log-rank p = 0.015, n = 123). We believe that morphological metrics such as lacunarity and fractal dimension could play a role in standard-of-care prognostic considerations at tumor presentation. This link between morphological and survival metrics could be driven by underlying biological phenomena or microenvironmental factors that should be further explored.

scholarly journals Morphological Metrics of Magnetic Resonance Imaging of Glioblastoma as Biomarkers of Prognosis

2021 ◽  
Author(s):  
Lee Curtin ◽  
Paula Whitmire ◽  
Haylye White ◽  
Maciej M. Mrugala ◽  
Leland S. Hu ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Fractal Dimension ◽  
Magnetic Resonance ◽  
Morphological Characteristics ◽  
Standard Of Care ◽  
Tumor Location ◽  
Primary Brain Tumor ◽  
Resonance Imaging ◽  
Current Standard ◽  
Fluid Attenuated Inversion Recovery

AbstractMorphological characteristics have been linked to outcomes across a variety of cancers. Lacunarity is a quantitative morphological measure of how shapes fill space while fractal dimension is a morphological measure of the complexity of pixel arrangement. Glioblastoma is the most aggressive primary brain tumor with a short expected survival given the current standard-of-care treatment. Due to the sensitive location of the tumor, there is a heavy reliance on imaging to assess the state of the disease in the clinic. In this project, we computed lacunarity and fractal dimension values for glioblastoma-induced abnormalities on gadolinium-enhanced T1-weighted magnetic resonance imaging (T1Gd MRI) as well as T2-weighted (T2) and fluid-attenuated inversion recovery (FLAIR) MRIs. In our patient cohort (n=402), we aim to connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension across all MRI slices on necrotic regions (n=390) and abnormalities on T1Gd MRI (n=402), as well as on enhancing abnormalities present on T2/FLAIR MRI (n=257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome across all three imaging subtypes, with the shape of T2/FLAIR abnormalities showing the strongest relationship with overall survival. The link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.

Bone-related disorders of the jaw: A clinico-radiological diagnostic algorithm

2021 ◽  
pp. 197140092199896
Author(s):  
Ahmed Abdel Khalek Abdel Razek
Keyword(s):  
Diagnostic Algorithm ◽  
Imaging Features ◽  
Resonance Imaging ◽  
Specific Diagnosis ◽  
Clinical Presentations ◽  
Neoplastic Lesions ◽  
Lesion Extension ◽  
Magnetic Resonance Imaging Mri ◽  
The Relationship ◽  
Ct And Mri

Bone-related disorders of the jaw (BRDJ) include a spectrum of non-neoplastic and neoplastic lesions of the maxillofacial region that have been recently classified into fibro-osseous lesions, giant cell lesions and osseous tumours. The histopathological features of BRDJ can be similar and overlie each other. Imaging is important in order to reach a specific diagnosis. However, the appearance of BRDJ on imaging is non-specific in some cases. Computed tomography (CT) and magnetic resonance imaging (MRI) are used for accurate localisation, characterisation of the tumour matrix, delineation of the lesion extension and establishment of the relation of BRDJ to the surrounding structures. Imaging is usually done to detect the relationship with the adjacent surrounding vital structures and to diagnose aggressive forms, malignant transformation and associated syndromes. The correlation of the demographic findings, the location and the clinical presentations with the imaging features are important for the diagnosis of BRDJ. The proposed clinico-radiological diagnostic algorithm with CT and MRI helps a specific diagnosis to be reached in some cases.

Method for interpreting iskinetic test data and MRI studies during patients ‘Rehabilitation after reconstructive shoulder joint surgery shoulder joint surgery

2021 ◽  
Vol 2 ◽  
pp. 22-33
Author(s):  
Elena Titskaya ◽  
◽  
Konstantin Simonov ◽  
Evgeny Kabaev ◽  
Alexander Matsulev ◽  
...  
Keyword(s):  
Spectral Decomposition ◽  
Shoulder Joint ◽  
Decomposition Methods ◽  
Resonance Imaging ◽  
Color Coding ◽  
Joint Surgery ◽  
Computer Visualization ◽  
Arthroscopic Shoulder Surgery ◽  
Magnetic Resonance Imaging Mri ◽  
The Relationship

The results of computer visualization of the biomechanics of the shoulder joint are presented. Possibilities of using biomechanical robotic mechanotherapy, implemented using the CON-TREX complex, in the rehabilitation of patients after arthroscopic shoulder surgery. The possibilities of clarifying visualization using magnetic resonance imaging (MRI) using spectral decomposition methods (shearlet transform and contrasting with color coding) have been studied. The relationship between MRI data and CON-TREX protocols in planning and carrying out rehabilitation procedures has been shown. The relationship between MRI data and CON-TREX protocols in planning and carrying out rehabilitation procedures has been shown. A method is described that makes it possible to improve the quality and availability of MRI data when studying the biomechanics of the shoulder joint during rehabilitation.

Enhanced magnetic resonance imaging in multiple sclerosis

2000 ◽  
Vol 6 (5) ◽  
pp. 320-326 ◽  
Author(s):  
M Filippi
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Tissue Loss ◽  
Resonance Imaging ◽  
The Past ◽  
Magnetic Resonance Imaging Mri ◽  
The One ◽  
The Relationship

Gadolinium-enhanced magnetic resonance imaging (MRI) is very sensitive in the detection of active lesions of multiple sclerosis (MS) and has become a valuable tool to monitor the evolution of the disease either natural or modified by treatment. In the past few years, several studies, on the one hand, have assessed several ways to increase the sensitivity of enhanced MRI to disease activity and, on the other, have investigated in vivo the nature and evolution of enhancing lesions using different non-conventional MR techniques to better define the relationship between enhancement and tissue loss in MS. The present review is a summary of these studies whose results are discussed in the context of MS clinical trial planning and monitoring.

scholarly journals Hybrid PET–MRI Imaging in Paediatric and TYA Brain Tumours: Clinical Applications and Challenges

2020 ◽  
Vol 10 (4) ◽  
pp. 218
Author(s):  
Ananth Shankar ◽  
Jamshed Bomanji ◽  
Harpreet Hyare
Keyword(s):  
Brain Tumours ◽  
Therapeutic Assessment ◽  
Mri Imaging ◽  
Resonance Imaging ◽  
Single Centre ◽  
Positron Emission ◽  
Early Treatment Response ◽  
Single Centre Experience ◽  
Magnetic Resonance Imaging Mri ◽  
Standard Magnetic Resonance Imaging

(1) Background: Standard magnetic resonance imaging (MRI) remains the gold standard for brain tumour imaging in paediatric and teenage and young adult (TYA) patients. Combining positron emission tomography (PET) with MRI offers an opportunity to improve diagnostic accuracy. (2) Method: Our single-centre experience of 18F-fluorocholine (FCho) and 18fluoro-L-phenylalanine (FDOPA) PET–MRI in paediatric/TYA neuro-oncology patients is presented. (3) Results: Hybrid PET–MRI shows promise in the evaluation of gliomas and germ cell tumours in (i) assessing early treatment response and (ii) discriminating tumour from treatment-related changes. (4) Conclusions: Combined PET–MRI shows promise for improved diagnostic and therapeutic assessment in paediatric and TYA brain tumours.

scholarly journals Modeling Tumor Cellularity in Newly Diagnosed GBMs using MR Imaging and Spectroscopy

2010 ◽  
Author(s):  
Alexandra Constantin ◽  
Sarah Nelson ◽  
Ruzena Bajcsy
Keyword(s):  
Expectation Maximization ◽  
Ex Vivo ◽  
Resonance Imaging ◽  
Tissue Samples ◽  
Imaging And Spectroscopy ◽  
Magnetic Resonance Imaging Mri ◽  
Definition Of ◽  
Quantitative Definition ◽  
The Relationship

In this paper, we analyze the relationship between parameters of brain tumors obtained through in vivo magnetic resonance imaging (MRI), in vivo magneticnresonance spectroscopy (MRS), and ex vivo immunohistochemistry (IHC). The goal of our project is to provide a quantitative definition of tumor cellularity based on the in vivo parameters. Biopsy samples obtained from previously untreated patients with a diagnosis of GBM are used to find the link between imaging parameters at the specific biopsy locations and IHC parameters from the corresponding tissue samples. A functional tree (FT) model of tumor cellularity is learned from the in vivo parameters and the remaining histological parameters. The tumor cellularity model is then tested on examples which contain only in vivo parameters, by first estimating the remaining IHC parameters by applying the Expectation Maximization (EM) algorithm, and then using the complete parameter vector for classification.

Bicaudate Index on Magnetic Resonance Imaging: Effects of Normal Aging

1994 ◽  
Vol 7 (1) ◽  
pp. 13-17 ◽  
Author(s):  
P. Murali Doraiswamy ◽  
Linda Patterson ◽  
Chul Na ◽  
Mustafa M. Husain ◽  
Orest Boyko ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Cerebral Atrophy ◽  
Normal Aging ◽  
Resonance Imaging ◽  
Huntington's Chorea ◽  
Caudate Nuclei ◽  
Computed Tomographic ◽  
Magnetic Resonance Imaging Mri ◽  
The Relationship

The bicaudate and bifrontal indices have been used in prior computed tomographic studies to investigate atrophy of the caudate nuclei in patients with Huntington's chorea and cerebral atrophy. However, the relationship between these indices and caudate volume has not been documented previously. In this study, we used high-field magnetic resonance imaging (MRI) to determine the effects of normal aging on the bicaudate and bifrontal indices and to study the relationship between these indices and caudate volume. The subjects were 49 normal volunteers, aged 22 to 82 years, who were without any significant neurologic or psychiatric disorders. Age was positively correlated with bicaudate index ( r = .59; P < .0001) and bifrontal index ( r = .40; P < .0047). Age was negatively correlated with caudate nuclei volume ( r = -.47; P < .0005). Caudate volume was negatively correlated with bicaudate ( r = -.27; P < .06) and bifrontal ( r = -.31; P < .03) indices. These findings are consistent with prior reports of caudate nuclei degeneration with increasing age. Linear and volumetric caudate measurements with MRI may prove useful in the investigation of caudate nuclei function in the neuromotor decline with normal aging and in disorders such as Huntington's chorea.

Fibroproliferative Neuromas May Occur After Iatrogenic Injury for Lipomatosis of Nerve

Neurosurgery ◽  
2013 ◽  
Vol 73 (2) ◽  
pp. 271-281 ◽  
Author(s):  
Mark A. Mahan ◽  
Kimberly K. Amrami ◽  
Robert J. Spinner
Keyword(s):  
Skin Incision ◽  
Iatrogenic Injury ◽  
Nerve Transection ◽  
Resonance Imaging ◽  
Unique Type ◽  
Postoperative Mri ◽  
Lipomatosis Of Nerve ◽  
High Incidence ◽  
Magnetic Resonance Imaging Mri ◽  
The Relationship

Abstract BACKGROUND: Lipomatosis of nerve (LN) is a condition associated with nerve-territory overgrowth. We have noted a unique type of neuroma at sites of LN injury; the neuroma extends beyond the epineurium, enhances, and appears to enlarge over time. OBJECTIVE: We sought to understand the relationship between fibroproliferative scarring and surgery performed on the nerve. METHODS: A review of the searchable records for LN at our institution found 52 cases, confirmed by pathology or pathognomonic appearance on magnetic resonance imaging (MRI). Clinical histories were reviewed to categorize the surgeries performed by the degree of iatrogenic injury to the nerve. Postoperative MRI was performed in 22 of the 46 patients who had surgery, which was then retrospectively reviewed for fibroproliferative neuromas. RESULTS: Complex and masslike neuromas were found on MRI, correlating with the degree of iatrogenic injury to the nerve. These fibrous neuromas proliferated beyond the epineurium, disrupted fascicular architecture, were contrast enhancing when contrast was administered, indicative they were unique and unlike stump or traction neuromas. Of the 8 patients who underwent surgery involving nerve decompression alone, none developed fibroproliferative neuromas. Of the 7 patients who underwent surgery involving nerve debulking, fibroproliferative neuromas developed in 4. Of the 11 patients who underwent surgery involving nerve transection, all developed fibroproliferative neuromas (P &lt; .001). There was also a high incidence of hypertrophic scarring of the skin incision (21.3%). CONCLUSION: Surgical injury of LN appears to be strongly associated with the development of fibroproliferative neuromas. It is possible that the pathological overgrowth stimulus associated with LN promotes exuberant scar formation.

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