Assessment of Diagnostic Accuracy of MRI in Diagnosing and Characterizing Intra-axial Brain Gliomas
Background: Magnetic Resonance Imaging (MRI) has emerged as most prevailing noninvasive radiological modality for the diagnosis of brain tumor, its prognosis, therapeutic assessment, observation of progression or regression of disease and planning of neurosurgical approaches. Objective: To assess th...
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Veröffentlicht in: | Pakistan journal of medical research 2021-12, Vol.60 (4), p.189 |
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description | Background: Magnetic Resonance Imaging (MRI) has emerged as most prevailing noninvasive radiological modality for the diagnosis of brain tumor, its prognosis, therapeutic assessment, observation of progression or regression of disease and planning of neurosurgical approaches. Objective: To assess the diagnostic accuracy of MRI in diagnosing and characterizing intra-axial brain gliomas taking histopathology as a gold standard. Study type, settings and duration: This prospective research was conducted in the Department of Radiology at Jinnah Hospital, Lahore from March 2016 to August 2016. Methodology: Two hundred patients with space occupying lesions diagnosed on CT scan of age 3 months to 65 years of either gender were included. Pregnant women and contraindication to MRI were omitted. The MRI of all other patients using 1.5 Tesla MR System with a gradient strength of 33 mT/m was performed. MRI study was interpreted by assessing the features favouring malignancy or benignity of gliomas. MRI findings were compared with the histopathology reports. Results: Mean age was 44.41±7.52 years. Among these 200 patients, 113 (56.50%) were male patients and 87 (43.50%) were female patients making male to female ratio of 1.2:1. In MRI positive patients, 89 were found to be true positive patients while 23 were found to be false positive patients. Among 88 MRI negative patients, 74 were true negative (p =0.367) whereas 14 came out to be False Negative. Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of MRI in diagnosing malignant cerebral glioma were 86.41%, 76.29%, 79.46%, 84.09% and 81.50% respectively. Conclusion: This study demonstrated that MRI is the non-invasive imaging modality of choice with high diagnostic accuracy in diagnosing malignant cerebral gliomas, and has not only radically improved our ability of distinguishing benign and malignant brain tumor pre-operatively but also aids the surgeons for appropriate decision-making. |
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Objective: To assess the diagnostic accuracy of MRI in diagnosing and characterizing intra-axial brain gliomas taking histopathology as a gold standard. Study type, settings and duration: This prospective research was conducted in the Department of Radiology at Jinnah Hospital, Lahore from March 2016 to August 2016. Methodology: Two hundred patients with space occupying lesions diagnosed on CT scan of age 3 months to 65 years of either gender were included. Pregnant women and contraindication to MRI were omitted. The MRI of all other patients using 1.5 Tesla MR System with a gradient strength of 33 mT/m was performed. MRI study was interpreted by assessing the features favouring malignancy or benignity of gliomas. MRI findings were compared with the histopathology reports. Results: Mean age was 44.41±7.52 years. Among these 200 patients, 113 (56.50%) were male patients and 87 (43.50%) were female patients making male to female ratio of 1.2:1. In MRI positive patients, 89 were found to be true positive patients while 23 were found to be false positive patients. Among 88 MRI negative patients, 74 were true negative (p =0.367) whereas 14 came out to be False Negative. Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of MRI in diagnosing malignant cerebral glioma were 86.41%, 76.29%, 79.46%, 84.09% and 81.50% respectively. Conclusion: This study demonstrated that MRI is the non-invasive imaging modality of choice with high diagnostic accuracy in diagnosing malignant cerebral gliomas, and has not only radically improved our ability of distinguishing benign and malignant brain tumor pre-operatively but also aids the surgeons for appropriate decision-making.</description><identifier>ISSN: 0030-9842</identifier><language>eng</language><publisher>Islamabad: Knowledge Bylanes</publisher><subject>Accuracy ; Age ; Brain cancer ; Brain research ; Brain tumors ; Chemotherapy ; Diagnosis ; Glioma ; Gliomas ; Histopathology ; Laws, regulations and rules ; Magnetic resonance imaging ; Patients ; Spectrum analysis ; Statistical analysis ; Tumors ; Variables</subject><ispartof>Pakistan journal of medical research, 2021-12, Vol.60 (4), p.189</ispartof><rights>COPYRIGHT 2021 Knowledge Bylanes</rights><rights>(c)2021 Pakistan Journal of Medical Research</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids></links><search><creatorcontrib>Mushtaq, Memoona</creatorcontrib><creatorcontrib>Arooj, Sadaf</creatorcontrib><creatorcontrib>Khaliq, Maria</creatorcontrib><creatorcontrib>Riffat Raja</creatorcontrib><creatorcontrib>Iqbal, Seerat</creatorcontrib><title>Assessment of Diagnostic Accuracy of MRI in Diagnosing and Characterizing Intra-axial Brain Gliomas</title><title>Pakistan journal of medical research</title><description>Background: Magnetic Resonance Imaging (MRI) has emerged as most prevailing noninvasive radiological modality for the diagnosis of brain tumor, its prognosis, therapeutic assessment, observation of progression or regression of disease and planning of neurosurgical approaches. Objective: To assess the diagnostic accuracy of MRI in diagnosing and characterizing intra-axial brain gliomas taking histopathology as a gold standard. Study type, settings and duration: This prospective research was conducted in the Department of Radiology at Jinnah Hospital, Lahore from March 2016 to August 2016. Methodology: Two hundred patients with space occupying lesions diagnosed on CT scan of age 3 months to 65 years of either gender were included. Pregnant women and contraindication to MRI were omitted. The MRI of all other patients using 1.5 Tesla MR System with a gradient strength of 33 mT/m was performed. MRI study was interpreted by assessing the features favouring malignancy or benignity of gliomas. MRI findings were compared with the histopathology reports. Results: Mean age was 44.41±7.52 years. Among these 200 patients, 113 (56.50%) were male patients and 87 (43.50%) were female patients making male to female ratio of 1.2:1. In MRI positive patients, 89 were found to be true positive patients while 23 were found to be false positive patients. Among 88 MRI negative patients, 74 were true negative (p =0.367) whereas 14 came out to be False Negative. Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of MRI in diagnosing malignant cerebral glioma were 86.41%, 76.29%, 79.46%, 84.09% and 81.50% respectively. Conclusion: This study demonstrated that MRI is the non-invasive imaging modality of choice with high diagnostic accuracy in diagnosing malignant cerebral gliomas, and has not only radically improved our ability of distinguishing benign and malignant brain tumor pre-operatively but also aids the surgeons for appropriate decision-making.</description><subject>Accuracy</subject><subject>Age</subject><subject>Brain cancer</subject><subject>Brain research</subject><subject>Brain tumors</subject><subject>Chemotherapy</subject><subject>Diagnosis</subject><subject>Glioma</subject><subject>Gliomas</subject><subject>Histopathology</subject><subject>Laws, regulations and rules</subject><subject>Magnetic resonance imaging</subject><subject>Patients</subject><subject>Spectrum analysis</subject><subject>Statistical analysis</subject><subject>Tumors</subject><subject>Variables</subject><issn>0030-9842</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkE1LxDAQhntQcF39DwHPlXx1Mz3WquvCiiB7L9l81Cxtok0L6q83ZRU9yBwG3nnmfYc5yRYYM5yXwOlZdh7jAeNCEMoXmapiNDH2xo8oWHTrZOtDHJ1ClVLTINXHLD8-b5DzP1PnWyS9RvWLTMBoBvc5Sxs_DjKX70526GaQiV93LvQyXmSnVnbRXH73Zba7v9vVD_n2ab2pq23elgXktBRWM1pyzTlQSwBTxsBYBZRSooHwku9tQRgpNQehyV4JrECAWBkLArNldnW0fR3C22Ti2BzCNPiU2FBBgRPOCfxSrexM47wN6WrVu6iaKr2EEbyis9f1P1QqbXqngjfWJf3PwhdT6Gn5</recordid><startdate>20211231</startdate><enddate>20211231</enddate><creator>Mushtaq, Memoona</creator><creator>Arooj, Sadaf</creator><creator>Khaliq, Maria</creator><creator>Riffat Raja</creator><creator>Iqbal, Seerat</creator><general>Knowledge Bylanes</general><general>AsiaNet Pakistan (Pvt) Ltd</general><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>M0S</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PADUT</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20211231</creationdate><title>Assessment of Diagnostic Accuracy of MRI in Diagnosing and Characterizing Intra-axial Brain Gliomas</title><author>Mushtaq, Memoona ; Arooj, Sadaf ; Khaliq, Maria ; Riffat Raja ; Iqbal, Seerat</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-g958-297fd3294d4482f1802338efc82221d81494bf51319d487d1bc70c87876ef8703</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Age</topic><topic>Brain cancer</topic><topic>Brain research</topic><topic>Brain tumors</topic><topic>Chemotherapy</topic><topic>Diagnosis</topic><topic>Glioma</topic><topic>Gliomas</topic><topic>Histopathology</topic><topic>Laws, regulations and rules</topic><topic>Magnetic resonance imaging</topic><topic>Patients</topic><topic>Spectrum analysis</topic><topic>Statistical analysis</topic><topic>Tumors</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mushtaq, Memoona</creatorcontrib><creatorcontrib>Arooj, Sadaf</creatorcontrib><creatorcontrib>Khaliq, Maria</creatorcontrib><creatorcontrib>Riffat Raja</creatorcontrib><creatorcontrib>Iqbal, Seerat</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Research Library China</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Pakistan journal of medical research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mushtaq, Memoona</au><au>Arooj, Sadaf</au><au>Khaliq, Maria</au><au>Riffat Raja</au><au>Iqbal, Seerat</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessment of Diagnostic Accuracy of MRI in Diagnosing and Characterizing Intra-axial Brain Gliomas</atitle><jtitle>Pakistan journal of medical research</jtitle><date>2021-12-31</date><risdate>2021</risdate><volume>60</volume><issue>4</issue><spage>189</spage><pages>189-</pages><issn>0030-9842</issn><abstract>Background: Magnetic Resonance Imaging (MRI) has emerged as most prevailing noninvasive radiological modality for the diagnosis of brain tumor, its prognosis, therapeutic assessment, observation of progression or regression of disease and planning of neurosurgical approaches. Objective: To assess the diagnostic accuracy of MRI in diagnosing and characterizing intra-axial brain gliomas taking histopathology as a gold standard. Study type, settings and duration: This prospective research was conducted in the Department of Radiology at Jinnah Hospital, Lahore from March 2016 to August 2016. Methodology: Two hundred patients with space occupying lesions diagnosed on CT scan of age 3 months to 65 years of either gender were included. Pregnant women and contraindication to MRI were omitted. The MRI of all other patients using 1.5 Tesla MR System with a gradient strength of 33 mT/m was performed. MRI study was interpreted by assessing the features favouring malignancy or benignity of gliomas. MRI findings were compared with the histopathology reports. Results: Mean age was 44.41±7.52 years. Among these 200 patients, 113 (56.50%) were male patients and 87 (43.50%) were female patients making male to female ratio of 1.2:1. In MRI positive patients, 89 were found to be true positive patients while 23 were found to be false positive patients. Among 88 MRI negative patients, 74 were true negative (p =0.367) whereas 14 came out to be False Negative. Overall sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of MRI in diagnosing malignant cerebral glioma were 86.41%, 76.29%, 79.46%, 84.09% and 81.50% respectively. Conclusion: This study demonstrated that MRI is the non-invasive imaging modality of choice with high diagnostic accuracy in diagnosing malignant cerebral gliomas, and has not only radically improved our ability of distinguishing benign and malignant brain tumor pre-operatively but also aids the surgeons for appropriate decision-making.</abstract><cop>Islamabad</cop><pub>Knowledge Bylanes</pub></addata></record> |
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subjects | Accuracy Age Brain cancer Brain research Brain tumors Chemotherapy Diagnosis Glioma Gliomas Histopathology Laws, regulations and rules Magnetic resonance imaging Patients Spectrum analysis Statistical analysis Tumors Variables |
title | Assessment of Diagnostic Accuracy of MRI in Diagnosing and Characterizing Intra-axial Brain Gliomas |
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