Variabilities of Magnetic Resonance Imaging–, Computed Tomography–, and Positron Emission Tomography–Computed Tomography–Based Tumor and Lymph Node Delineations for Lung Cancer Radiation Therapy Planning

Kishor Karki, Siddharth Saraiya, Geoffrey D. Hugo, Nitai Mukhopadhyay, Nuzhat Jan, Jessica Schuster, Matthew Schutzer, Lester Fahrner, Robert Groves, Kathryn M. Olsen, John Ford, Elisabeth Weiss

Research output: Contribution to journalArticle

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Abstract

Purpose To investigate interobserver delineation variability for gross tumor volumes of primary lung tumors and associated pathologic lymph nodes using magnetic resonance imaging (MRI), and to compare the results with computed tomography (CT) alone– and positron emission tomography (PET)-CT–based delineations. Methods and Materials Seven physicians delineated the tumor volumes of 10 patients for the following scenarios: (1) CT only, (2) PET-CT fusion images registered to CT (“clinical standard”), and (3) postcontrast T1-weighted MRI registered with diffusion-weighted MRI. To compute interobserver variability, the median surface was generated from all observers' contours and used as the reference surface. A physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest wall) on the median surface. Contoured volumes and bidirectional local distances between individual observers' contours and the reference contour were analyzed. Results Computed tomography– and MRI-based tumor volumes normalized relative to PET-CT–based volumes were 1.62 ± 0.76 (mean ± standard deviation) and 1.38 ± 0.44, respectively. Volume differences between the imaging modalities were not significant. Between observers, the mean normalized volumes per patient averaged over all patients varied significantly by a factor of 1.6 (MRI) and 2.0 (CT and PET-CT) (P=4.10 × 10−5 to 3.82 × 10−9). The tumor-atelectasis interface had a significantly higher variability than other interfaces for all modalities combined (P=.0006). The interfaces with the smallest uncertainties were tumor-lung (on CT) and tumor-mediastinum (on PET-CT and MRI). Conclusions Although MRI-based contouring showed overall larger variability than PET-CT, contouring variability depended on the interface type and was not significantly different between modalities, despite the limited observer experience with MRI. Multimodality imaging and combining different imaging characteristics might be the best approach to define the tumor volume most accurately.

Original languageEnglish (US)
Pages (from-to)80-89
Number of pages10
JournalInternational Journal of Radiation Oncology Biology Physics
Volume99
Issue number1
DOIs
StatePublished - Sep 1 2017

Fingerprint

Emission-Computed Tomography
delineation
lymphatic system
Positron-Emission Tomography
lungs
magnetic resonance
planning
radiation therapy
positrons
Lung Neoplasms
Radiotherapy
tumors
tomography
Lymph Nodes
cancer
Magnetic Resonance Imaging
Tumor Burden
Tomography
Neoplasms
Lung

ASJC Scopus subject areas

  • Radiation
  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

Cite this

Variabilities of Magnetic Resonance Imaging–, Computed Tomography–, and Positron Emission Tomography–Computed Tomography–Based Tumor and Lymph Node Delineations for Lung Cancer Radiation Therapy Planning. / Karki, Kishor; Saraiya, Siddharth; Hugo, Geoffrey D.; Mukhopadhyay, Nitai; Jan, Nuzhat; Schuster, Jessica; Schutzer, Matthew; Fahrner, Lester; Groves, Robert; Olsen, Kathryn M.; Ford, John; Weiss, Elisabeth.

In: International Journal of Radiation Oncology Biology Physics, Vol. 99, No. 1, 01.09.2017, p. 80-89.

Research output: Contribution to journalArticle

Karki, Kishor ; Saraiya, Siddharth ; Hugo, Geoffrey D. ; Mukhopadhyay, Nitai ; Jan, Nuzhat ; Schuster, Jessica ; Schutzer, Matthew ; Fahrner, Lester ; Groves, Robert ; Olsen, Kathryn M. ; Ford, John ; Weiss, Elisabeth. / Variabilities of Magnetic Resonance Imaging–, Computed Tomography–, and Positron Emission Tomography–Computed Tomography–Based Tumor and Lymph Node Delineations for Lung Cancer Radiation Therapy Planning. In: International Journal of Radiation Oncology Biology Physics. 2017 ; Vol. 99, No. 1. pp. 80-89.
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abstract = "Purpose To investigate interobserver delineation variability for gross tumor volumes of primary lung tumors and associated pathologic lymph nodes using magnetic resonance imaging (MRI), and to compare the results with computed tomography (CT) alone– and positron emission tomography (PET)-CT–based delineations. Methods and Materials Seven physicians delineated the tumor volumes of 10 patients for the following scenarios: (1) CT only, (2) PET-CT fusion images registered to CT (“clinical standard”), and (3) postcontrast T1-weighted MRI registered with diffusion-weighted MRI. To compute interobserver variability, the median surface was generated from all observers' contours and used as the reference surface. A physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest wall) on the median surface. Contoured volumes and bidirectional local distances between individual observers' contours and the reference contour were analyzed. Results Computed tomography– and MRI-based tumor volumes normalized relative to PET-CT–based volumes were 1.62 ± 0.76 (mean ± standard deviation) and 1.38 ± 0.44, respectively. Volume differences between the imaging modalities were not significant. Between observers, the mean normalized volumes per patient averaged over all patients varied significantly by a factor of 1.6 (MRI) and 2.0 (CT and PET-CT) (P=4.10 × 10−5 to 3.82 × 10−9). The tumor-atelectasis interface had a significantly higher variability than other interfaces for all modalities combined (P=.0006). The interfaces with the smallest uncertainties were tumor-lung (on CT) and tumor-mediastinum (on PET-CT and MRI). Conclusions Although MRI-based contouring showed overall larger variability than PET-CT, contouring variability depended on the interface type and was not significantly different between modalities, despite the limited observer experience with MRI. Multimodality imaging and combining different imaging characteristics might be the best approach to define the tumor volume most accurately.",
author = "Kishor Karki and Siddharth Saraiya and Hugo, {Geoffrey D.} and Nitai Mukhopadhyay and Nuzhat Jan and Jessica Schuster and Matthew Schutzer and Lester Fahrner and Robert Groves and Olsen, {Kathryn M.} and John Ford and Elisabeth Weiss",
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T1 - Variabilities of Magnetic Resonance Imaging–, Computed Tomography–, and Positron Emission Tomography–Computed Tomography–Based Tumor and Lymph Node Delineations for Lung Cancer Radiation Therapy Planning

AU - Karki, Kishor

AU - Saraiya, Siddharth

AU - Hugo, Geoffrey D.

AU - Mukhopadhyay, Nitai

AU - Jan, Nuzhat

AU - Schuster, Jessica

AU - Schutzer, Matthew

AU - Fahrner, Lester

AU - Groves, Robert

AU - Olsen, Kathryn M.

AU - Ford, John

AU - Weiss, Elisabeth

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N2 - Purpose To investigate interobserver delineation variability for gross tumor volumes of primary lung tumors and associated pathologic lymph nodes using magnetic resonance imaging (MRI), and to compare the results with computed tomography (CT) alone– and positron emission tomography (PET)-CT–based delineations. Methods and Materials Seven physicians delineated the tumor volumes of 10 patients for the following scenarios: (1) CT only, (2) PET-CT fusion images registered to CT (“clinical standard”), and (3) postcontrast T1-weighted MRI registered with diffusion-weighted MRI. To compute interobserver variability, the median surface was generated from all observers' contours and used as the reference surface. A physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest wall) on the median surface. Contoured volumes and bidirectional local distances between individual observers' contours and the reference contour were analyzed. Results Computed tomography– and MRI-based tumor volumes normalized relative to PET-CT–based volumes were 1.62 ± 0.76 (mean ± standard deviation) and 1.38 ± 0.44, respectively. Volume differences between the imaging modalities were not significant. Between observers, the mean normalized volumes per patient averaged over all patients varied significantly by a factor of 1.6 (MRI) and 2.0 (CT and PET-CT) (P=4.10 × 10−5 to 3.82 × 10−9). The tumor-atelectasis interface had a significantly higher variability than other interfaces for all modalities combined (P=.0006). The interfaces with the smallest uncertainties were tumor-lung (on CT) and tumor-mediastinum (on PET-CT and MRI). Conclusions Although MRI-based contouring showed overall larger variability than PET-CT, contouring variability depended on the interface type and was not significantly different between modalities, despite the limited observer experience with MRI. Multimodality imaging and combining different imaging characteristics might be the best approach to define the tumor volume most accurately.

AB - Purpose To investigate interobserver delineation variability for gross tumor volumes of primary lung tumors and associated pathologic lymph nodes using magnetic resonance imaging (MRI), and to compare the results with computed tomography (CT) alone– and positron emission tomography (PET)-CT–based delineations. Methods and Materials Seven physicians delineated the tumor volumes of 10 patients for the following scenarios: (1) CT only, (2) PET-CT fusion images registered to CT (“clinical standard”), and (3) postcontrast T1-weighted MRI registered with diffusion-weighted MRI. To compute interobserver variability, the median surface was generated from all observers' contours and used as the reference surface. A physician labeled the interface types (tumor to lung, atelectasis (collapsed lung), hilum, mediastinum, or chest wall) on the median surface. Contoured volumes and bidirectional local distances between individual observers' contours and the reference contour were analyzed. Results Computed tomography– and MRI-based tumor volumes normalized relative to PET-CT–based volumes were 1.62 ± 0.76 (mean ± standard deviation) and 1.38 ± 0.44, respectively. Volume differences between the imaging modalities were not significant. Between observers, the mean normalized volumes per patient averaged over all patients varied significantly by a factor of 1.6 (MRI) and 2.0 (CT and PET-CT) (P=4.10 × 10−5 to 3.82 × 10−9). The tumor-atelectasis interface had a significantly higher variability than other interfaces for all modalities combined (P=.0006). The interfaces with the smallest uncertainties were tumor-lung (on CT) and tumor-mediastinum (on PET-CT and MRI). Conclusions Although MRI-based contouring showed overall larger variability than PET-CT, contouring variability depended on the interface type and was not significantly different between modalities, despite the limited observer experience with MRI. Multimodality imaging and combining different imaging characteristics might be the best approach to define the tumor volume most accurately.

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