SlideShare a Scribd company logo
1 of 1
Individually optimized contrast-enhanced 4D-CT for radiotherapy
simulation in pancreatic adenocarcinoma
Wookjin Choi, Ming Xue, Barton Lane, Min Kyu Kang, Kruti Patel, William Regine, Paul Klahr,
Jiahui Wang, Shifeng Chen, Warren D'Souza, Wei Lu
Medical Physics, Memorial Sloan Kettering Cancer Center
Radiation Oncology and Radiology, University of Maryland School of Medicine
Purpose
Results
Method
To develop an individually optimized contrast-enhanced
(CE) 4D-CT for radiotherapy simulation in pancreatic
ductal adenocarcinoma (PDA).
• Ten PDA patients were enrolled and underwent three
CT scans
– Clinical standard: A 4D-CT immediately following a CE
3D-CT
– Proposed protocol: A single individually optimized CE 4D-
CT using a test injection to estimate the peak contrast
enhancement time and to optimize the delay time.
• Three physicians contoured the tumor and pancreatic
tissues.
• Image quality scores, tumor volume, motion, image
noise, tumor-to-pancreas contrast, and contrast-to-
noise ratio (CNR) were compared in the three CTs.
• Inter-observer variations in contouring the tumor were
as well as evaluated using simultaneous truth and
performance level estimation (STAPLE).
• The CE 4D-CT was largely comparable to CE 3D-CT
– Image quality, enhancement, and contrast
• High potential for simultaneously delineating the
tumor and quantifying tumor motion with a single scan.
• Contrast enhancement in PDA is still poor, large inter-
observer variations in contouring tumors.
• Image qualities of CE 3D-CT and CE 4D-CT were
comparable, and both were significantly better than
4D-CT.
• Tumor-to-pancreas contrast in CE 3D-CT and CE 4D-
CT were comparable, and the later was higher than
4D-CT.
• Noise in CE 3D-CT was much lower than 4D-CT and
CE 4D-CT.
• CNR was not significantly different between CE 3D-
CT and CE 4D-CT.
• Both GTV50% in CE 4D-CT and GTV in CE 3D-CT
were significantly smaller than GTV50% in 4D-CT.
• Tumor motion were comparable.
• Large inter-observer variations in all three CTs
CE 3D-CT CE 4D-CT4D-CT
Fig. 2. Three physicians visually scored image quality, and contoured the
tumor (red, T) and pancreatic tissue (blue, P).
𝐶𝑁𝑅 =
𝐶
𝜎𝑓
,T
P
Conclusion
CE 3D-CT 4D-CT CE 4D-CT
Pancreas (HU) 49.2 ± 12.3 44.6 ± 15.9* 75.5 ± 21.2*
Tumor(HU) 53.0 ± 9.2* 58.9 ± 14.3* 76.3 ±15.0*
Tumor-to-
pancreas
contrast (HU)
15.5 ± 20.7 9.2 ± 9.2* 16.7 ± 12.3
Noise (HU) 12.5 ± 3.9* 19.4 ± 5.8 22.1 ± 5.7*
CNR 1.4 ± 1.9* 0.6 ± 0.7* 0.8 ± 0.6
CE 3D-CT 4D-CT CE 4D-CT
General
ImageQuality
Anatomical details 4.1 ± 0.8 2.5 ± 0.6 3.6 ± 0.8
Motion artifacts 3.9 ± 1.0 3.4 ± 0.9 3.7 ± 0.8
Beam hardening 4.2 ± 0.8 3.3 ± 0.9 3.5 ± 0.8
Enhancement 3.2 ± 1.0 1.7 ± 0.9 3.3 ± 1.0
Regional Vessel
Definition
4.2 ± 1.1 2.7 ± 1.5 4.1 ± 1.3
Overall Average 4.0 ± 0.5 2.6 ± 0.5 3.8 ± 0.4
Signed rank test (P) <0.001*,
vs. 4D-CT
<0.001*,
vs. CE 4D-CT
0.082,
vs. CE 3D-CT
4D-CT CE 4D-CT P
Volume
(cm3)
GTV50% 42.0 ± 35.1 22.8 ± 18.9 0.005*
IGTV4 56.0 ± 38.1 32.8 ± 26.4 0.005*
GTV
Motion
(mm)
LR 2.3 ± 1.7 1.1 ± 0.5 0.14
AP 2.8 ± 1.6 2.6 ± 1.6 0.80
SI 6.0 ± 1.7 5.4 ± 1.6 0.39
3D 7.2 ± 2.0 6.2 ± 1.9 0.17
Table 1. Image Quality Scores
Table 2. Quantitative Analysis
Table 3. Tumor Volume and Motion
Fig. 5. Inter-observer variation in contouring tumors
Supported in part by Philips Healthcare, Inc.
and NIH Grant No. R01CA172638
*Contact: Wei Lu, Ph.D., luw@mskcc.org
We can determine optimal delay time Tdelay
4D-CT Acquisition Contrast Injection
LO
4D-CTScanLength
Organ
Tpeak
Tdelay = LO/V- Tpeak
ContrastEnhancementCurve
Time(s)
Enhancement (HU)
a
c
b
d
e
Time when the organ is
scanned over (Lo/V)
Time when organ reaches
peak enhancement Tpeak
Synchronize
Using a test injection enhancement curve {Xue et al., 2012. Med. Phy. 39: 3903-3903}.
ROI in aorta
{Bae 2010. Radiology 256: 32-61}
Enhancement (HU)
Time (Sec)
0 5 10 15 20 25 30 35 45
105
100
95
90
85
80
75
70
65
60
55
Typical transit time
Injection duration Typical arrival time
𝑇𝑝𝑒𝑎𝑘 = TID + 15 s + Tarr − 20 s
Tarr = 24.2 s
Tpeak
Pancreas
Scores ranged from 1 to 5, with 1 being “very poor” and 5 being “excellent.”, and
*Significant at 0.05.
*Significant at 0.05.
*Significant at 0.05.
Fig.1. Regions adjacent to the tumor–pancreas boundary were
selected to measure contrast.
Fig. 4. Determine the delay time.
Fig. 3. Estimate time to peak enhancement
78.0%
73.7%
66.0%66.5%
72.7%
55.6%
72.2% 72.5%
61.9%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
90.0%
Sensitivity Specificity Jaccard
CE 3D-CT 4D-CT CE 4D-CT

More Related Content

What's hot

Radiomics Analysis of Pulmonary Nodules in Low Dose CT for Early Detection of...
Radiomics Analysis of Pulmonary Nodules in Low Dose CT for Early Detection of...Radiomics Analysis of Pulmonary Nodules in Low Dose CT for Early Detection of...
Radiomics Analysis of Pulmonary Nodules in Low Dose CT for Early Detection of...
Wookjin Choi
 
Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induce...
Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induce...Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induce...
Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induce...
Wookjin Choi
 
Use of pre treatment protocols
Use of pre treatment protocols   Use of pre treatment protocols
Use of pre treatment protocols
Bartosz Bąk
 
automatic detection of pulmonary nodules in lung ct images
automatic detection of pulmonary nodules in lung ct imagesautomatic detection of pulmonary nodules in lung ct images
automatic detection of pulmonary nodules in lung ct images
Wookjin Choi
 

What's hot (20)

Radiomics Analysis of Pulmonary Nodules in Low Dose CT for Early Detection of...
Radiomics Analysis of Pulmonary Nodules in Low Dose CT for Early Detection of...Radiomics Analysis of Pulmonary Nodules in Low Dose CT for Early Detection of...
Radiomics Analysis of Pulmonary Nodules in Low Dose CT for Early Detection of...
 
Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induce...
Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induce...Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induce...
Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induce...
 
Computer-aided Detection of Pulmonary Nodules using Genetic Programming
Computer-aided Detection of Pulmonary Nodules using Genetic ProgrammingComputer-aided Detection of Pulmonary Nodules using Genetic Programming
Computer-aided Detection of Pulmonary Nodules using Genetic Programming
 
Image quality assessment of contrast-enhanced 4D-CT for pancreatic adenocarci...
Image quality assessment of contrast-enhanced 4D-CT for pancreatic adenocarci...Image quality assessment of contrast-enhanced 4D-CT for pancreatic adenocarci...
Image quality assessment of contrast-enhanced 4D-CT for pancreatic adenocarci...
 
computer aided detection of pulmonary nodules in ct scans
computer aided detection of pulmonary nodules in ct scanscomputer aided detection of pulmonary nodules in ct scans
computer aided detection of pulmonary nodules in ct scans
 
Image processing in lung cancer screening and treatment
Image processing in lung cancer screening and treatmentImage processing in lung cancer screening and treatment
Image processing in lung cancer screening and treatment
 
Computer aided detection of pulmonary nodules using genetic programming
Computer aided detection of pulmonary nodules using genetic programmingComputer aided detection of pulmonary nodules using genetic programming
Computer aided detection of pulmonary nodules using genetic programming
 
4 D CT simulation with synchronized intravenous contrast injection
4 D CT simulation with synchronized intravenous contrast injection4 D CT simulation with synchronized intravenous contrast injection
4 D CT simulation with synchronized intravenous contrast injection
 
Innovations conference 2014 dr shalini vinod dedicated magnetic resonance i...
Innovations conference 2014   dr shalini vinod dedicated magnetic resonance i...Innovations conference 2014   dr shalini vinod dedicated magnetic resonance i...
Innovations conference 2014 dr shalini vinod dedicated magnetic resonance i...
 
Technical Advances in radiotherapy for Lung (and liver) Cancer
Technical Advances in radiotherapy for Lung (and liver) CancerTechnical Advances in radiotherapy for Lung (and liver) Cancer
Technical Advances in radiotherapy for Lung (and liver) Cancer
 
IGRT in lung cancer
IGRT in lung cancerIGRT in lung cancer
IGRT in lung cancer
 
Use of pre treatment protocols
Use of pre treatment protocols   Use of pre treatment protocols
Use of pre treatment protocols
 
Innovations conference 2014 prof peter metcalfe moving towards mri along ra...
Innovations conference 2014   prof peter metcalfe moving towards mri along ra...Innovations conference 2014   prof peter metcalfe moving towards mri along ra...
Innovations conference 2014 prof peter metcalfe moving towards mri along ra...
 
Image guided adaptive radiotherapy
Image guided adaptive radiotherapyImage guided adaptive radiotherapy
Image guided adaptive radiotherapy
 
automatic detection of pulmonary nodules in lung ct images
automatic detection of pulmonary nodules in lung ct imagesautomatic detection of pulmonary nodules in lung ct images
automatic detection of pulmonary nodules in lung ct images
 
importance of ct-simulator in radiotherapy
importance of ct-simulator in radiotherapyimportance of ct-simulator in radiotherapy
importance of ct-simulator in radiotherapy
 
Rt
RtRt
Rt
 
Research into the effectiveness of daily image guided radiotherapy on the pro...
Research into the effectiveness of daily image guided radiotherapy on the pro...Research into the effectiveness of daily image guided radiotherapy on the pro...
Research into the effectiveness of daily image guided radiotherapy on the pro...
 
PERFORMANCE EVALUATION OF TUMOR DETECTION TECHNIQUES
PERFORMANCE EVALUATION OF TUMOR DETECTION TECHNIQUES PERFORMANCE EVALUATION OF TUMOR DETECTION TECHNIQUES
PERFORMANCE EVALUATION OF TUMOR DETECTION TECHNIQUES
 
Modern Radiation Treatment
Modern Radiation TreatmentModern Radiation Treatment
Modern Radiation Treatment
 

Similar to Individually Optimized Contrast-Enhanced 4D-CT for Radiotherapy Simulation in Pancreatic Adenocarcinoma

Imrt Where Next Image Guided Radiotherapy
Imrt Where Next Image Guided RadiotherapyImrt Where Next Image Guided Radiotherapy
Imrt Where Next Image Guided Radiotherapy
fondas vakalis
 
Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...
 Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons... Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...
Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...
breastcancerupdatecongress
 
Basem AL Al Zahrany .docx
Basem AL Al Zahrany                                               .docxBasem AL Al Zahrany                                               .docx
Basem AL Al Zahrany .docx
ikirkton
 
Clinical pet and pet ct
Clinical pet and pet ctClinical pet and pet ct
Clinical pet and pet ct
Springer
 

Similar to Individually Optimized Contrast-Enhanced 4D-CT for Radiotherapy Simulation in Pancreatic Adenocarcinoma (20)

Imrt Where Next Image Guided Radiotherapy
Imrt Where Next Image Guided RadiotherapyImrt Where Next Image Guided Radiotherapy
Imrt Where Next Image Guided Radiotherapy
 
A CT-Based Nomogram for Preoperative Prediction of Synchronous Peritoneal Met...
A CT-Based Nomogram for Preoperative Prediction of Synchronous Peritoneal Met...A CT-Based Nomogram for Preoperative Prediction of Synchronous Peritoneal Met...
A CT-Based Nomogram for Preoperative Prediction of Synchronous Peritoneal Met...
 
PERFORMANCE EVALUATION OF TUMOR DETECTION TECHNIQUES
PERFORMANCE EVALUATION OF TUMOR DETECTION TECHNIQUES PERFORMANCE EVALUATION OF TUMOR DETECTION TECHNIQUES
PERFORMANCE EVALUATION OF TUMOR DETECTION TECHNIQUES
 
Jean Michel Correas, prostate cancer use of multiparametric ultrasound imagin...
Jean Michel Correas, prostate cancer use of multiparametric ultrasound imagin...Jean Michel Correas, prostate cancer use of multiparametric ultrasound imagin...
Jean Michel Correas, prostate cancer use of multiparametric ultrasound imagin...
 
Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...
 Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons... Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...
Sophie Taieb : Breast MRI in neoadjuvant chemotherapy : A predictive respons...
 
IMRT and 3D CRT in cervical Cancers
IMRT and 3D CRT in cervical CancersIMRT and 3D CRT in cervical Cancers
IMRT and 3D CRT in cervical Cancers
 
Image registration and data fusion techniques.pptx latest save
Image registration and data fusion techniques.pptx latest saveImage registration and data fusion techniques.pptx latest save
Image registration and data fusion techniques.pptx latest save
 
Co-relation of multidetector CT scan based preoperative staging with intra-op...
Co-relation of multidetector CT scan based preoperative staging with intra-op...Co-relation of multidetector CT scan based preoperative staging with intra-op...
Co-relation of multidetector CT scan based preoperative staging with intra-op...
 
Introduction to compressed sensing MRI
Introduction to compressed sensing MRIIntroduction to compressed sensing MRI
Introduction to compressed sensing MRI
 
Basem AL Al Zahrany .docx
Basem AL Al Zahrany                                               .docxBasem AL Al Zahrany                                               .docx
Basem AL Al Zahrany .docx
 
Cedric De Bazelaire new advance in multiparametric breast mri jfim ifupi mila...
Cedric De Bazelaire new advance in multiparametric breast mri jfim ifupi mila...Cedric De Bazelaire new advance in multiparametric breast mri jfim ifupi mila...
Cedric De Bazelaire new advance in multiparametric breast mri jfim ifupi mila...
 
Effective Dose of Computed Tomography (CT) Chest and Abdomen-Pelvis in Some S...
Effective Dose of Computed Tomography (CT) Chest and Abdomen-Pelvis in Some S...Effective Dose of Computed Tomography (CT) Chest and Abdomen-Pelvis in Some S...
Effective Dose of Computed Tomography (CT) Chest and Abdomen-Pelvis in Some S...
 
(March 14, 2024) Webinar: Validation of DEXA for Longitudinal Quantification ...
(March 14, 2024) Webinar: Validation of DEXA for Longitudinal Quantification ...(March 14, 2024) Webinar: Validation of DEXA for Longitudinal Quantification ...
(March 14, 2024) Webinar: Validation of DEXA for Longitudinal Quantification ...
 
Clinical pet and pet ct
Clinical pet and pet ctClinical pet and pet ct
Clinical pet and pet ct
 
Controversies in Colorectal Cancer
Controversies in Colorectal CancerControversies in Colorectal Cancer
Controversies in Colorectal Cancer
 
PET GUIDED TARGET CONTOURING GUIDELINES.pptx
PET GUIDED TARGET CONTOURING GUIDELINES.pptxPET GUIDED TARGET CONTOURING GUIDELINES.pptx
PET GUIDED TARGET CONTOURING GUIDELINES.pptx
 
Advances in oncological PET/CT Imaging
Advances in oncological PET/CT ImagingAdvances in oncological PET/CT Imaging
Advances in oncological PET/CT Imaging
 
Advanced imaging modalities of the liver
Advanced imaging modalities of the liverAdvanced imaging modalities of the liver
Advanced imaging modalities of the liver
 
SPECT/CT: HOW Much Radiation Dose CT Constitute
SPECT/CT: HOW Much Radiation Dose CT ConstituteSPECT/CT: HOW Much Radiation Dose CT Constitute
SPECT/CT: HOW Much Radiation Dose CT Constitute
 
Sarcoma brachytherapy updates
Sarcoma brachytherapy updatesSarcoma brachytherapy updates
Sarcoma brachytherapy updates
 

More from Wookjin Choi

Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Canc...
Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Canc...Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Canc...
Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Canc...
Wookjin Choi
 
Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation...
Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation...Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation...
Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation...
Wookjin Choi
 
Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Canc...
Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Canc...Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Canc...
Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Canc...
Wookjin Choi
 
CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Ra...
CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Ra...CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Ra...
CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Ra...
Wookjin Choi
 
Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability ...
Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability ...Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability ...
Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability ...
Wookjin Choi
 
Simulation of Realistic Organ-At-Risk Delineation Variability in Head and Nec...
Simulation of Realistic Organ-At-Risk Delineation Variability in Head and Nec...Simulation of Realistic Organ-At-Risk Delineation Variability in Head and Nec...
Simulation of Realistic Organ-At-Risk Delineation Variability in Head and Nec...
Wookjin Choi
 

More from Wookjin Choi (20)

Deep Learning-based Histological Segmentation Differentiates Cavitation Patte...
Deep Learning-based Histological SegmentationDifferentiates Cavitation Patte...Deep Learning-based Histological SegmentationDifferentiates Cavitation Patte...
Deep Learning-based Histological Segmentation Differentiates Cavitation Patte...
 
Artificial Intelligence To Reduce Radiation-induced Cardiotoxicity In Lung Ca...
Artificial Intelligence To Reduce Radiation-induced Cardiotoxicity In Lung Ca...Artificial Intelligence To Reduce Radiation-induced Cardiotoxicity In Lung Ca...
Artificial Intelligence To Reduce Radiation-induced Cardiotoxicity In Lung Ca...
 
Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Canc...
Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Canc...Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Canc...
Novel Functional Radiomics for Prediction of Cardiac PET Avidity in Lung Canc...
 
Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation...
Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation...Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation...
Novel Deep Learning Segmentation Models for Accurate GTV and OAR Segmentation...
 
Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Canc...
Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Canc...Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Canc...
Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Canc...
 
CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Ra...
CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Ra...CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Ra...
CIRDataset: A large-scale Dataset for Clinically-Interpretable lung nodule Ra...
 
Artificial Intelligence in Radiation Oncology.pptx
 Artificial Intelligence in Radiation Oncology.pptx Artificial Intelligence in Radiation Oncology.pptx
Artificial Intelligence in Radiation Oncology.pptx
 
Artificial Intelligence in Radiation Oncology
Artificial Intelligence in Radiation OncologyArtificial Intelligence in Radiation Oncology
Artificial Intelligence in Radiation Oncology
 
Artificial Intelligence in Radiation Oncology
Artificial Intelligence in Radiation OncologyArtificial Intelligence in Radiation Oncology
Artificial Intelligence in Radiation Oncology
 
Artificial Intelligence in Radiation Oncology
Artificial Intelligence in Radiation OncologyArtificial Intelligence in Radiation Oncology
Artificial Intelligence in Radiation Oncology
 
Automatic motion tracking system for analysis of insect behavior
Automatic motion tracking system for analysis of insect behaviorAutomatic motion tracking system for analysis of insect behavior
Automatic motion tracking system for analysis of insect behavior
 
Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability ...
Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability ...Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability ...
Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability ...
 
Quantitative Cancer Image Analysis
Quantitative Cancer Image AnalysisQuantitative Cancer Image Analysis
Quantitative Cancer Image Analysis
 
Simulation of Realistic Organ-At-Risk Delineation Variability in Head and Nec...
Simulation of Realistic Organ-At-Risk Delineation Variability in Head and Nec...Simulation of Realistic Organ-At-Risk Delineation Variability in Head and Nec...
Simulation of Realistic Organ-At-Risk Delineation Variability in Head and Nec...
 
Quantitative image analysis for cancer diagnosis and radiation therapy
Quantitative image analysis for cancer diagnosis and radiation therapyQuantitative image analysis for cancer diagnosis and radiation therapy
Quantitative image analysis for cancer diagnosis and radiation therapy
 
Interpretable Spiculation Quantification for Lung Cancer Screening
Interpretable Spiculation Quantification for Lung Cancer ScreeningInterpretable Spiculation Quantification for Lung Cancer Screening
Interpretable Spiculation Quantification for Lung Cancer Screening
 
Radiomics in Lung Cancer
Radiomics in Lung CancerRadiomics in Lung Cancer
Radiomics in Lung Cancer
 
Interpretable Spiculation Quantification for Lung Cancer Screening
Interpretable Spiculation Quantification for Lung Cancer ScreeningInterpretable Spiculation Quantification for Lung Cancer Screening
Interpretable Spiculation Quantification for Lung Cancer Screening
 
Quantitative Image Analysis for Cancer Diagnosis and Radiation Therapy
Quantitative Image Analysis for Cancer Diagnosis and Radiation TherapyQuantitative Image Analysis for Cancer Diagnosis and Radiation Therapy
Quantitative Image Analysis for Cancer Diagnosis and Radiation Therapy
 
Dual energy CT in radiotherapy: Current applications and future outlook
Dual energy CT in radiotherapy: Current applications and future outlookDual energy CT in radiotherapy: Current applications and future outlook
Dual energy CT in radiotherapy: Current applications and future outlook
 

Recently uploaded

CYTOGENETIC MAP................ ppt.pptx
CYTOGENETIC MAP................ ppt.pptxCYTOGENETIC MAP................ ppt.pptx
CYTOGENETIC MAP................ ppt.pptx
Cherry
 
Porella : features, morphology, anatomy, reproduction etc.
Porella : features, morphology, anatomy, reproduction etc.Porella : features, morphology, anatomy, reproduction etc.
Porella : features, morphology, anatomy, reproduction etc.
Cherry
 
Reboulia: features, anatomy, morphology etc.
Reboulia: features, anatomy, morphology etc.Reboulia: features, anatomy, morphology etc.
Reboulia: features, anatomy, morphology etc.
Cherry
 
Human genetics..........................pptx
Human genetics..........................pptxHuman genetics..........................pptx
Human genetics..........................pptx
Cherry
 
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 bAsymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Sérgio Sacani
 
(May 9, 2024) Enhanced Ultrafast Vector Flow Imaging (VFI) Using Multi-Angle ...
(May 9, 2024) Enhanced Ultrafast Vector Flow Imaging (VFI) Using Multi-Angle ...(May 9, 2024) Enhanced Ultrafast Vector Flow Imaging (VFI) Using Multi-Angle ...
(May 9, 2024) Enhanced Ultrafast Vector Flow Imaging (VFI) Using Multi-Angle ...
Scintica Instrumentation
 
Phenolics: types, biosynthesis and functions.
Phenolics: types, biosynthesis and functions.Phenolics: types, biosynthesis and functions.
Phenolics: types, biosynthesis and functions.
Cherry
 
LUNULARIA -features, morphology, anatomy ,reproduction etc.
LUNULARIA -features, morphology, anatomy ,reproduction etc.LUNULARIA -features, morphology, anatomy ,reproduction etc.
LUNULARIA -features, morphology, anatomy ,reproduction etc.
Cherry
 

Recently uploaded (20)

CYTOGENETIC MAP................ ppt.pptx
CYTOGENETIC MAP................ ppt.pptxCYTOGENETIC MAP................ ppt.pptx
CYTOGENETIC MAP................ ppt.pptx
 
Dr. E. Muralinath_ Blood indices_clinical aspects
Dr. E. Muralinath_ Blood indices_clinical  aspectsDr. E. Muralinath_ Blood indices_clinical  aspects
Dr. E. Muralinath_ Blood indices_clinical aspects
 
Porella : features, morphology, anatomy, reproduction etc.
Porella : features, morphology, anatomy, reproduction etc.Porella : features, morphology, anatomy, reproduction etc.
Porella : features, morphology, anatomy, reproduction etc.
 
Cyanide resistant respiration pathway.pptx
Cyanide resistant respiration pathway.pptxCyanide resistant respiration pathway.pptx
Cyanide resistant respiration pathway.pptx
 
Genetics and epigenetics of ADHD and comorbid conditions
Genetics and epigenetics of ADHD and comorbid conditionsGenetics and epigenetics of ADHD and comorbid conditions
Genetics and epigenetics of ADHD and comorbid conditions
 
Early Development of Mammals (Mouse and Human).pdf
Early Development of Mammals (Mouse and Human).pdfEarly Development of Mammals (Mouse and Human).pdf
Early Development of Mammals (Mouse and Human).pdf
 
Reboulia: features, anatomy, morphology etc.
Reboulia: features, anatomy, morphology etc.Reboulia: features, anatomy, morphology etc.
Reboulia: features, anatomy, morphology etc.
 
Thyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate ProfessorThyroid Physiology_Dr.E. Muralinath_ Associate Professor
Thyroid Physiology_Dr.E. Muralinath_ Associate Professor
 
Human genetics..........................pptx
Human genetics..........................pptxHuman genetics..........................pptx
Human genetics..........................pptx
 
Clean In Place(CIP).pptx .
Clean In Place(CIP).pptx                 .Clean In Place(CIP).pptx                 .
Clean In Place(CIP).pptx .
 
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and SpectrometryFAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
FAIRSpectra - Enabling the FAIRification of Spectroscopy and Spectrometry
 
Cot curve, melting temperature, unique and repetitive DNA
Cot curve, melting temperature, unique and repetitive DNACot curve, melting temperature, unique and repetitive DNA
Cot curve, melting temperature, unique and repetitive DNA
 
Use of mutants in understanding seedling development.pptx
Use of mutants in understanding seedling development.pptxUse of mutants in understanding seedling development.pptx
Use of mutants in understanding seedling development.pptx
 
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 bAsymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
Asymmetry in the atmosphere of the ultra-hot Jupiter WASP-76 b
 
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
Human & Veterinary Respiratory Physilogy_DR.E.Muralinath_Associate Professor....
 
CURRENT SCENARIO OF POULTRY PRODUCTION IN INDIA
CURRENT SCENARIO OF POULTRY PRODUCTION IN INDIACURRENT SCENARIO OF POULTRY PRODUCTION IN INDIA
CURRENT SCENARIO OF POULTRY PRODUCTION IN INDIA
 
(May 9, 2024) Enhanced Ultrafast Vector Flow Imaging (VFI) Using Multi-Angle ...
(May 9, 2024) Enhanced Ultrafast Vector Flow Imaging (VFI) Using Multi-Angle ...(May 9, 2024) Enhanced Ultrafast Vector Flow Imaging (VFI) Using Multi-Angle ...
(May 9, 2024) Enhanced Ultrafast Vector Flow Imaging (VFI) Using Multi-Angle ...
 
Climate Change Impacts on Terrestrial and Aquatic Ecosystems.pptx
Climate Change Impacts on Terrestrial and Aquatic Ecosystems.pptxClimate Change Impacts on Terrestrial and Aquatic Ecosystems.pptx
Climate Change Impacts on Terrestrial and Aquatic Ecosystems.pptx
 
Phenolics: types, biosynthesis and functions.
Phenolics: types, biosynthesis and functions.Phenolics: types, biosynthesis and functions.
Phenolics: types, biosynthesis and functions.
 
LUNULARIA -features, morphology, anatomy ,reproduction etc.
LUNULARIA -features, morphology, anatomy ,reproduction etc.LUNULARIA -features, morphology, anatomy ,reproduction etc.
LUNULARIA -features, morphology, anatomy ,reproduction etc.
 

Individually Optimized Contrast-Enhanced 4D-CT for Radiotherapy Simulation in Pancreatic Adenocarcinoma

  • 1. Individually optimized contrast-enhanced 4D-CT for radiotherapy simulation in pancreatic adenocarcinoma Wookjin Choi, Ming Xue, Barton Lane, Min Kyu Kang, Kruti Patel, William Regine, Paul Klahr, Jiahui Wang, Shifeng Chen, Warren D'Souza, Wei Lu Medical Physics, Memorial Sloan Kettering Cancer Center Radiation Oncology and Radiology, University of Maryland School of Medicine Purpose Results Method To develop an individually optimized contrast-enhanced (CE) 4D-CT for radiotherapy simulation in pancreatic ductal adenocarcinoma (PDA). • Ten PDA patients were enrolled and underwent three CT scans – Clinical standard: A 4D-CT immediately following a CE 3D-CT – Proposed protocol: A single individually optimized CE 4D- CT using a test injection to estimate the peak contrast enhancement time and to optimize the delay time. • Three physicians contoured the tumor and pancreatic tissues. • Image quality scores, tumor volume, motion, image noise, tumor-to-pancreas contrast, and contrast-to- noise ratio (CNR) were compared in the three CTs. • Inter-observer variations in contouring the tumor were as well as evaluated using simultaneous truth and performance level estimation (STAPLE). • The CE 4D-CT was largely comparable to CE 3D-CT – Image quality, enhancement, and contrast • High potential for simultaneously delineating the tumor and quantifying tumor motion with a single scan. • Contrast enhancement in PDA is still poor, large inter- observer variations in contouring tumors. • Image qualities of CE 3D-CT and CE 4D-CT were comparable, and both were significantly better than 4D-CT. • Tumor-to-pancreas contrast in CE 3D-CT and CE 4D- CT were comparable, and the later was higher than 4D-CT. • Noise in CE 3D-CT was much lower than 4D-CT and CE 4D-CT. • CNR was not significantly different between CE 3D- CT and CE 4D-CT. • Both GTV50% in CE 4D-CT and GTV in CE 3D-CT were significantly smaller than GTV50% in 4D-CT. • Tumor motion were comparable. • Large inter-observer variations in all three CTs CE 3D-CT CE 4D-CT4D-CT Fig. 2. Three physicians visually scored image quality, and contoured the tumor (red, T) and pancreatic tissue (blue, P). 𝐶𝑁𝑅 = 𝐶 𝜎𝑓 ,T P Conclusion CE 3D-CT 4D-CT CE 4D-CT Pancreas (HU) 49.2 ± 12.3 44.6 ± 15.9* 75.5 ± 21.2* Tumor(HU) 53.0 ± 9.2* 58.9 ± 14.3* 76.3 ±15.0* Tumor-to- pancreas contrast (HU) 15.5 ± 20.7 9.2 ± 9.2* 16.7 ± 12.3 Noise (HU) 12.5 ± 3.9* 19.4 ± 5.8 22.1 ± 5.7* CNR 1.4 ± 1.9* 0.6 ± 0.7* 0.8 ± 0.6 CE 3D-CT 4D-CT CE 4D-CT General ImageQuality Anatomical details 4.1 ± 0.8 2.5 ± 0.6 3.6 ± 0.8 Motion artifacts 3.9 ± 1.0 3.4 ± 0.9 3.7 ± 0.8 Beam hardening 4.2 ± 0.8 3.3 ± 0.9 3.5 ± 0.8 Enhancement 3.2 ± 1.0 1.7 ± 0.9 3.3 ± 1.0 Regional Vessel Definition 4.2 ± 1.1 2.7 ± 1.5 4.1 ± 1.3 Overall Average 4.0 ± 0.5 2.6 ± 0.5 3.8 ± 0.4 Signed rank test (P) <0.001*, vs. 4D-CT <0.001*, vs. CE 4D-CT 0.082, vs. CE 3D-CT 4D-CT CE 4D-CT P Volume (cm3) GTV50% 42.0 ± 35.1 22.8 ± 18.9 0.005* IGTV4 56.0 ± 38.1 32.8 ± 26.4 0.005* GTV Motion (mm) LR 2.3 ± 1.7 1.1 ± 0.5 0.14 AP 2.8 ± 1.6 2.6 ± 1.6 0.80 SI 6.0 ± 1.7 5.4 ± 1.6 0.39 3D 7.2 ± 2.0 6.2 ± 1.9 0.17 Table 1. Image Quality Scores Table 2. Quantitative Analysis Table 3. Tumor Volume and Motion Fig. 5. Inter-observer variation in contouring tumors Supported in part by Philips Healthcare, Inc. and NIH Grant No. R01CA172638 *Contact: Wei Lu, Ph.D., luw@mskcc.org We can determine optimal delay time Tdelay 4D-CT Acquisition Contrast Injection LO 4D-CTScanLength Organ Tpeak Tdelay = LO/V- Tpeak ContrastEnhancementCurve Time(s) Enhancement (HU) a c b d e Time when the organ is scanned over (Lo/V) Time when organ reaches peak enhancement Tpeak Synchronize Using a test injection enhancement curve {Xue et al., 2012. Med. Phy. 39: 3903-3903}. ROI in aorta {Bae 2010. Radiology 256: 32-61} Enhancement (HU) Time (Sec) 0 5 10 15 20 25 30 35 45 105 100 95 90 85 80 75 70 65 60 55 Typical transit time Injection duration Typical arrival time 𝑇𝑝𝑒𝑎𝑘 = TID + 15 s + Tarr − 20 s Tarr = 24.2 s Tpeak Pancreas Scores ranged from 1 to 5, with 1 being “very poor” and 5 being “excellent.”, and *Significant at 0.05. *Significant at 0.05. *Significant at 0.05. Fig.1. Regions adjacent to the tumor–pancreas boundary were selected to measure contrast. Fig. 4. Determine the delay time. Fig. 3. Estimate time to peak enhancement 78.0% 73.7% 66.0%66.5% 72.7% 55.6% 72.2% 72.5% 61.9% 0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% Sensitivity Specificity Jaccard CE 3D-CT 4D-CT CE 4D-CT