Validity of US in Predicting CLNs Metastasis in Patients with OSCC - Softcover

Al-Ani, Rand ; Ibrahim, Usama ; Najim, Qais

9783330329089: Validity of US in Predicting CLNs Metastasis in Patients with OSCC

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ISBN 10: 3330329084 ISBN 13: 9783330329089

Verlag: LAP LAMBERT Academic Publishing, 2017

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Oral Squamous Cell Carcinoma (OSCC) is the most common malignant tumor in the world despite the advances in diagnosis and radiological imaging. Ultrasonography can improve the diagnostic accuracy, but good results are dependent on the operator expertise. In this book we presented two ways that can help in predicting metastatic cervical lymph node (CLN) images in patients with OSCC, independent on ultrasound (US) diagnostic criteria and operator expertise: 1. A Discriminant model that depends on the strongest predictive US criteria for metastasis. The model equation provides the physician a reliable probability guidance for managing cervical LN metastasis. It helps in managing controversial CLNs in patients with low-risk metastasis to be under observation rather than performing subsequent biopsies and neck dissections. 2. A Programming Code that works independently on US diagnostic criteria and operator expertise. The technique of the Code is based on the center of graph (C.O.G) in the Y axis of the histogram calculation for the node area. To our knowledge, this might be the first study that has used the C.O.G of image histogram to diagnose metastatic CLNs.

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�ber die Autorin bzw. den Autor

Rand Sh. Al-Ani, B.D.S., M.Sc., Ph.D., ist Dozentin in der Abteilung f�r Mund-, Kiefer- und Gesichtschirurgie an der Hochschule f�r Zahnmedizin der Universit�t Mosul / IRAQ. Ihr Forschungsschwerpunkt ist die orale und dentale Radiologie. F�r diese Forschung hat sie 2017 den IADR Unilever Hatton Divisional Award f�r die beste postgraduale (M.Sc.&Ph.D.) Forschung im Irak gewonnen.

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Verlag: LAP LAMBERT Academic Publishing
Erscheinungsdatum: 2017
Sprache: Englisch
ISBN 10: 3330329084
ISBN 13: 9783330329089
Einband: Taschenbuch
Anzahl der Seiten: 152
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Validity of US in Predicting CLNs Metastasis in Patients with OSCC

Rand Al-Ani

Verlag: LAP LAMBERT Academic Publishing Jun 2017, 2017

ISBN 10: 3330329084 ISBN 13: 9783330329089

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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Oral Squamous Cell Carcinoma (OSCC) is the most common malignant tumor in the world despite the advances in diagnosis and radiological imaging. Ultrasonography can improve the diagnostic accuracy, but good results are dependent on the operator expertise. In this book we presented two ways that can help in predicting metastatic cervical lymph node (CLN) images in patients with OSCC, independent on ultrasound (US) diagnostic criteria and operator expertise: 1. A Discriminant model that depends on the strongest predictive US criteria for metastasis. The model equation provides the physician a reliable probability guidance for managing cervical LN metastasis. It helps in managing controversial CLNs in patients with low-risk metastasis to be under observation rather than performing subsequent biopsies and neck dissections. 2. A Programming Code that works independently on US diagnostic criteria and operator expertise. The technique of the Code is based on the center of graph (C.O.G) in the Y axis of the histogram calculation for the node area. To our knowledge, this might be the first study that has used the C.O.G of image histogram to diagnose metastatic CLNs. 152 pp. Englisch. Bestandsnummer des Verk�ufers 9783330329089

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Validity of US in Predicting CLNs Metastasis in Patients with OSCC

Rand Al-Ani|Usama Ibrahim|Qais Najim

Verlag: LAP LAMBERT Academic Publishing, 2017

ISBN 10: 3330329084 ISBN 13: 9783330329089

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Al-Ani RandRand Sh. Al-Ani, B.D.S., M.Sc., Ph.D., is a lecturer in the Department of Oral and Maxillofacial Surgery in College of Dentistry/ University of Mosul / IRAQ. Her researches focus on Oral and Dental Radiology. For this re. Bestandsnummer des Verk�ufers 154744456

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Validity of US in Predicting CLNs Metastasis in Patients with OSCC

Rand Al-Ani

Verlag: LAP LAMBERT Academic Publishing Jun 2017, 2017

ISBN 10: 3330329084 ISBN 13: 9783330329089

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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Oral Squamous Cell Carcinoma (OSCC) is the most common malignant tumor in the world despite the advances in diagnosis and radiological imaging. Ultrasonography can improve the diagnostic accuracy, but good results are dependent on the operator expertise. In this book we presented two ways that can help in predicting metastatic cervical lymph node (CLN) images in patients with OSCC, independent on ultrasound (US) diagnostic criteria and operator expertise: 1. A Discriminant model that depends on the strongest predictive US criteria for metastasis. The model equation provides the physician a reliable probability guidance for managing cervical LN metastasis. It helps in managing controversial CLNs in patients with low-risk metastasis to be under observation rather than performing subsequent biopsies and neck dissections. 2. A Programming Code that works independently on US diagnostic criteria and operator expertise. The technique of the Code is based on the center of graph (C.O.G) in the Y axis of the histogram calculation for the node area. To our knowledge, this might be the first study that has used the C.O.G of image histogram to diagnose metastatic CLNs.VDM Verlag, Dudweiler Landstra�e 99, 66123 Saarbr�cken 152 pp. Englisch. Bestandsnummer des Verk�ufers 9783330329089

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Validity of US in Predicting CLNs Metastasis in Patients with OSCC

Rand Al-Ani

Verlag: LAP LAMBERT Academic Publishing, 2017

ISBN 10: 3330329084 ISBN 13: 9783330329089

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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Oral Squamous Cell Carcinoma (OSCC) is the most common malignant tumor in the world despite the advances in diagnosis and radiological imaging. Ultrasonography can improve the diagnostic accuracy, but good results are dependent on the operator expertise. In this book we presented two ways that can help in predicting metastatic cervical lymph node (CLN) images in patients with OSCC, independent on ultrasound (US) diagnostic criteria and operator expertise: 1. A Discriminant model that depends on the strongest predictive US criteria for metastasis. The model equation provides the physician a reliable probability guidance for managing cervical LN metastasis. It helps in managing controversial CLNs in patients with low-risk metastasis to be under observation rather than performing subsequent biopsies and neck dissections. 2. A Programming Code that works independently on US diagnostic criteria and operator expertise. The technique of the Code is based on the center of graph (C.O.G) in the Y axis of the histogram calculation for the node area. To our knowledge, this might be the first study that has used the C.O.G of image histogram to diagnose metastatic CLNs. Bestandsnummer des Verk�ufers 9783330329089

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