ADC map parameters at mpMRI predict unfavorable cribriform pattern in PCa patients

63-year-old female potential kidney donor with an indeterminate liver mass Axial fat-suppressed FSE T2-weighted (Figure 1.9.1) and SSFP (Figure 1.9.2) images demonstrate a focal lesion with high signal intensity in the right hepatic lobe. Diffusion-weighted image (b=600 s/mm2) and corresponding ADC map (...

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Radiomics Analysis of Multiparametric PET/MRI for N- and M-Staging in Patients with Primary Cervical Cancer

RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren ◽

10.1055/a-1100-0127 ◽

2020 ◽

Vol 192 (08) ◽

pp. 754-763 ◽

Cited By ~ 1

Author(s):

Lale Umutlu ◽

Felix Nensa ◽

Aydin Demircioglu ◽

Gerald Antoch ◽

Ken Herrmann ◽

...

Keyword(s):

Image Processing ◽

Cervical Cancer ◽

Fdg Pet ◽

Maschinelles Lernen ◽

Sich Eine ◽

Statistische Analyse ◽

Adc Map ◽

18F Fdg

Zielsetzung Ziel dieser Studie war die Evaluierung des prädiktiven Potenzials der Radiomics-Analyse zur Bestimmung des N- und M-Stadiums des primären Zervixkarzinoms anhand multiparametrischer 18F-FDG-PET/MRT-Bildgebung. Material und Methoden 30 Patientinnen mit einem histologisch gesicherten, primären und therapienaiven Zervixkarzinom unterzogen sich einer multiparametrischen 18F-FDG-PET/MRT-Untersuchung unter Verwendung eines dedizierten Untersuchungsprotokolls des weiblichen Beckens. Nach Segmentierung der Primärtumoren wurden quantitative Bildparameter mittels der Radiomic-Image-Processing-Toolbox bestimmt. Insgesamt wurden 45 verschiedene quantitative Bildmerkmale jeweils anhand der T2-gewichteten TSE-Sequenzen, der nativen und kontrastmittelgestützten T1-gewichteten TSE-Sequenzen, der ADC-Map, verschiedenen Perfusionsparametern (Ktrans, Kep, Ve and iAUC) und den 18F-FDG-PET-Datensätzen für jeden Tumor extrahiert. Die statistische Analyse zur Bestimmung des N- und M-Stadiums erfolgte unter der Verwendung der Python 3.5 und Scikit-learn-Software-Bibliothek für maschinelles Lernen. Ergebnisse Insgesamt zeigte sich eine höhere Genauigkeit zur Prädiktion des korrekten M-Stadiums im Vergleich zum N-Stadium. Zur Prädiktion des korrekten M-Stadiums zeigten sich unter der Verwendung von SVM und SVM-RFE zur Feature-Auswahl die besten Ergebnisse mit einer Sensitivität von 91 %, einer Spezifität von 92 % und einer Fläche unter der Kurve (AUC) von 0,97. Die höchste Genauigkeit für die Bestimmung des N-Stadiums erfolgte unter der Verwendung von RBF-SVM und MIFS zur Feature-Auswahl mit einer Sensitivität von 83 %, einer Spezifität von 67 % und einer Fläche unter der Kurve (AUC) von 0,82. Schlussfolgerung Die Radiomics-Analyse von multiparametrischen PET/MR-Datensätzen ermöglicht eine präzise Prädiktion des M- und N-Stadiums von Patientinnen mit primärem Zervixkarzinom und könnte damit supportiv zur nichtinvasiven Tumor-Phänotypisierung und Patientenstratifizierung eingesetzt werden. Kernaussagen: Citation Format

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The Application of Diffusion- and Perfusion-Weighted Magnetic Resonance Imaging in the Diagnosis and Therapy of Acute Cerebral Infarction

International Journal of Biomedical Imaging ◽

10.1155/ijbi/2006/20164 ◽

2006 ◽

Vol 2006 ◽

pp. 1-11 ◽

Cited By ~ 3

Author(s):

Ying Han ◽

Enzhong Li ◽

Jie Tian ◽

Jian Chen ◽

Huifang Wang ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Diffusion Coefficient ◽

Magnetic Resonance ◽

Cerebral Blood Volume ◽

Mean Transit Time ◽

Resonance Imaging ◽

Stroke Patients ◽

Apparent Diffusion ◽

Weighted Magnetic Resonance Imaging ◽

Adc Map

Diffusion- and perfusion-weighted magnetic resonance imaging (DWI and PWI) was applied for stroke diagnose in 120 acute (<48h) ischemic stroke patients. At hyperacute (<6h) stage, it is difficult to find out the infarction zone in conventional T1 or T2 image, but it is easy in DWI, apparent diffusion coefficient (ADC) map; when at 3–6-hour stage it is also easy in PWI, cerebral blood flow (CBF) map, cerebral blood volume (CBV) map, and mean transit time (MTT) map; at acute (6–48 h) stage, DWI or PWI is more sensitive than conventional T1 or T2 image too. Combining DWI with ADC, acute and chronic infarction can be distinguished. Besides, penumbra which should be developed in meaning was used as an indication or to evaluate the therapeutic efficacy. There were two cases (<1.5h) that broke the model of penumbra because abnormity was found in DWI but not that in PWI, finally they recovered without any sequela.

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Automated Hierarchical Prostate Cancer Detection based on Whole Mount Pathology in ADC map, DWI, T2wMR, and T1wMR

KIISE Transactions on Computing Practices ◽

10.5626/ktcp.2018.24.9.470 ◽

2018 ◽

Vol 24 (9) ◽

pp. 470-475

Author(s):

Young Gi Kim ◽

Julip Jung ◽

Helen Hong ◽

Sung Il Hwang ◽

Hak Jong Lee

Keyword(s):

Prostate Cancer ◽

Cancer Detection ◽

Prostate Cancer Detection ◽

Whole Mount ◽

Adc Map

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Solitary fibrous tumor of the pleura: Apparent diffusion coefficient (ADC) value and ADC map to predict malignant transformation

Journal of Magnetic Resonance Imaging ◽

10.1002/jmri.20942 ◽

2007 ◽

Vol 26 (1) ◽

pp. 155-158 ◽

Cited By ~ 14

Author(s):

Tsutomu Inaoka ◽

Koji Takahashi ◽

Naoyuki Miyokawa ◽

Yoshinobu Ohsaki ◽

Tamio Aburano

Keyword(s):

Diffusion Coefficient ◽

Apparent Diffusion Coefficient ◽

Malignant Transformation ◽

Solitary Fibrous Tumor ◽

Adc Value ◽

Apparent Diffusion ◽

Adc Map ◽

Fibrous Tumor

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Potential use of Oxygen as a Metabolic Biosensor in Combination with T2*-Weighted MRI to Define the Ischemic Penumbra

Journal of Cerebral Blood Flow & Metabolism ◽

10.1038/jcbfm.2008.56 ◽

2008 ◽

Vol 28 (10) ◽

pp. 1742-1753 ◽

Cited By ~ 62

Author(s):

Celestine Santosh ◽

David Brennan ◽

Christopher McCabe ◽

I Mhairi Macrae ◽

William M Holmes ◽

...

Keyword(s):

Artery Occlusion ◽

Neuronal Morphology ◽

Border Zone ◽

Signal Change ◽

Apparent Diffusion ◽

In Series ◽

Adc Map ◽

Ischemic Core ◽

Echo Planar ◽

Cerebral Artery Occlusion

We describe a novel magnetic resonance imaging technique for detecting metabolism indirectly through changes in oxyhemoglobin:deoxyhemoglobin ratios and T2* signal change during ‘oxygen challenge’ (OC, 5 mins 100% O2). During OC, T2* increase reflects O2 binding to deoxyhemoglobin, which is formed when metabolizing tissues take up oxygen. Here OC has been applied to identify tissue metabolism within the ischemic brain. Permanent middle cerebral artery occlusion was induced in rats. In series 1 scanning ( n = 5), diffusion-weighted imaging (DWI) was performed, followed by echo-planar T2* acquired during OC and perfusion-weighted imaging (PWI, arterial spin labeling). Oxygen challenge induced a T2* signal increase of 1.8%, 3.7%, and 0.24% in the contralateral cortex, ipsilateral cortex within the PWI/DWI mismatch zone, and ischemic core, respectively. T2* and apparent diffusion coefficient (ADC) map coregistration revealed that the T2* signal increase extended into the ADC lesion (3.4%). In series 2 ( n = 5), FLASH T2* and ADC maps coregistered with histology revealed a T2* signal increase of 4.9% in the histologically defined border zone (55% normal neuronal morphology, located within the ADC lesion boundary) compared with a 0.7% increase in the cortical ischemic core (92% neuronal ischemic cell change, core ADC lesion). Oxygen challenge has potential clinical utility and, by distinguishing metabolically active and inactive tissues within hypoperfused regions, could provide a more precise assessment of penumbra.

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