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10.1016/j.acra.2020.01.025 http://scihub22266oqcxt.onion/10.1016/j.acra.2020.01.025 32102748!ä!32102748 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Acad+Radiol 2021 ; 28 (2): e27-e34 Nephropedia Template TP {{tp|p=32102748|t=2021. Whole-Lesion DCE-MRI Intensity Histogram Analysis for Diagnosis in Patients with Suspected Lung Cancer |pdf=|usr=}}{{32102748}} gab.com Text Whole-Lesion DCE-MRI Intensity Histogram Analysis for Diagnosis in Patients with Suspected Lung Cancer JO: Acad Radiol http://www.kidney.de/pget.php?&tw=1&pmid=32102748 #FOAvip RATIONALE AND OBJECTIVES: To explore the diagnostic value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) intensity histogram metrics, relative to time intensity curve (TIC)-derived metrics, in patients with suspected lung cancer. MATERIALS AND METHODS: This retrospective study enrolled 49 patients with suspected lung cancer on routine CT imaging who underwent DCE-MRI scans and had final histopathologic diagnosis. Three TIC-derived metrics (maximum enhancement ratio, peak time [T(max)] and slope) and eight intensity histogram metrics (volume, integral, maximum, minimum, median, coefficient of variation [CoV], skewness, and kurtosis) were extracted from DCE-MRI images. TIC-derived and intensity histogram metrics were compared between benignity versus malignancy using the Wilcoxon rank-sum test. Associations between imaging metrics and malignancy risk were assessed by univariate and multivariate logistic regression odds ratios (ORs). RESULTS: There were 33 malignant lesions and 16 benign lesions based on histopathology. Lower CoV (OR?=?0.2 per 1-SD increase, p?=?0.0006), lower T(max) (OR?=?0.4 per 1-SD increase, p?=?0.005), and steeper slope (OR?=?2.4 per 1-SD increase, p?=?0.010) were significantly associated with increased risk of malignancy. Under multivariate analysis, CoV was significantly independently associated with malignancy likelihood after accounting for either T(max) (OR?=?0.3 per 1-SD increase, p?=?0.007) or slope (OR?=?0.3 per 1-SD increase, p?=?0.011). CONCLUSION: This initial study found that DCE-MRI CoV was independently associated with malignancy in patients with suspected lung cancer. CoV has the potential to help diagnose indeterminate pulmonary lesions and may complement TIC-derived DCE-MRI metrics. Further studies are warranted to validate the diagnostic value of DCE-MRI intensity histogram analysis. Twit Text FOAVip Whole-Lesion DCE-MRI Intensity Histogram Analysis for Diagnosis in Patients with Suspected Lung Cancer ????Acad Radiol http://www.kidney.de/pget.php?&tw=1&pmid=32102748 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32102748 #FOAvip English Wikipedia <ref>{{Cite pmid|32102748}}</ref> Whole-Lesion DCE-MRI Intensity Histogram Analysis for Diagnosis in Patients with Suspected Lung Cancer #MMPMID32102748 Wu W; Zhou S; Hippe DS; Liu H; Wang Y; Mayr NA; Yuh WTC; Xia L; Bowen SR Acad Radiol 2021[Feb]; 28 (2): e27-e34 PMID32102748show ga RATIONALE AND OBJECTIVES: To explore the diagnostic value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) intensity histogram metrics, relative to time intensity curve (TIC)-derived metrics, in patients with suspected lung cancer. MATERIALS AND METHODS: This retrospective study enrolled 49 patients with suspected lung cancer on routine CT imaging who underwent DCE-MRI scans and had final histopathologic diagnosis. Three TIC-derived metrics (maximum enhancement ratio, peak time [T(max)] and slope) and eight intensity histogram metrics (volume, integral, maximum, minimum, median, coefficient of variation [CoV], skewness, and kurtosis) were extracted from DCE-MRI images. TIC-derived and intensity histogram metrics were compared between benignity versus malignancy using the Wilcoxon rank-sum test. Associations between imaging metrics and malignancy risk were assessed by univariate and multivariate logistic regression odds ratios (ORs). RESULTS: There were 33 malignant lesions and 16 benign lesions based on histopathology. Lower CoV (OR?=?0.2 per 1-SD increase, p?=?0.0006), lower T(max) (OR?=?0.4 per 1-SD increase, p?=?0.005), and steeper slope (OR?=?2.4 per 1-SD increase, p?=?0.010) were significantly associated with increased risk of malignancy. Under multivariate analysis, CoV was significantly independently associated with malignancy likelihood after accounting for either T(max) (OR?=?0.3 per 1-SD increase, p?=?0.007) or slope (OR?=?0.3 per 1-SD increase, p?=?0.011). CONCLUSION: This initial study found that DCE-MRI CoV was independently associated with malignancy in patients with suspected lung cancer. CoV has the potential to help diagnose indeterminate pulmonary lesions and may complement TIC-derived DCE-MRI metrics. Further studies are warranted to validate the diagnostic value of DCE-MRI intensity histogram analysis. |*Lung Neoplasms[MESH] |*Magnetic Resonance Imaging[MESH] |Contrast Media[MESH] |Diagnosis, Differential[MESH] |Humans[MESH] |Retrospective Studies[MESH]Whole-Lesion DCE-MRI Intensity Histogram Analysis for Diagnosis in Pat(epmc).pdf DeepDyve Pubget Overpricing