Download “RECIST” criteria

Tumor Measurement Criteria
milestones - 1981 & 2000
TUMOR RESPONSE CRITERIA
WORLD HEALTH ORGANIZATION
(WHO)
RESPONSE EVALUATION
CRITERIA IN SOLID TUMORS
(RECIST)
WHO Handbook for Reporting
Results of Cancer Treatment
New Guidelines to Evaluate the
Response to Treatment in Solid Tumors
World Health Organization Offset Publication No. 48
Geneva, Switzerland, 1979
P Therasse, SG Arbuck, EA Eisenhauer,
J Wanders, RS Kaplan, L Rubinstein,
J Verweij, M Van Glabbeke, AT van Oosterom,
MC Christian, SG Gwyther
————————————————————————————
Reporting Results of Cancer Treatment
AB Miller, B Hogestraeten, M Staquet, A Winkler
Cancer 47:207–14, 1981
Journal of the National Cancer Institute
92: 205-216, 2000
WHO bi-linear measurement
Baseline
8 Weeks
RECIST Criteria
Response Evaluation Criteria In Solid Tumors
• Simplification of former methods
• 4 response categories (CR, PR, PD, SD)
• Based on linear 1-D being as good as 2-D
• Least effort, conservative, for widest acceptance
RECIST Criteria
• CR = disappearance of all target lesions
• PR = 30% decrease in the sum of the longest
diameter of target lesions
• PD = 20% increase in the sum of the longest
diameter of target lesions
• SD = small changes that don’t meet above
criteria
CR = complete response
PR = partial response
PD = progressive disease
SD = stable disease
RECIST criteria
‘Target’ lesions
• All measurable lesions up to a
maximum of five lesions per organ,
and 10 lesions in total
• Sum of the longest diameter of all of
the target lesions
RECIST
• RECIST criteria may be employed by NCIfunded cooperative groups which are
encouraged, but not required, to use
• RECIST criteria are a voluntary,
international standard, and not an NCI
standard
• That doesn’t mean Clinical Trial groups
are satisfied with it
baseline
24 weeks (PR confirmed - 52%)
20 weeks (PR at - 39%)
52 weeks (- 74%)
metastatic renal cell
baseline
13 wks (– 7 %)
27 wks (PR – 43 %)
metastatic renal cell
FDA reform plans
The Value of Image Data
Validated image data could lead to:
• Smaller clinical trials with fewer patients
• Earlier go/no decisions on compounds
• Faster regulatory approval
• Shorter time to market
Biomarker
• a measurable characteristic that predicts a clinical
endpoint
• “surrogate marker” is a biomarker that substitutes for a
clinical endpoint
– “surrogate marker” is a special case biomarker, i.e,
not just a predictor of a clinical endpoint, but a reliable
substitute for a clinical endpoint
• the distinction has regulatory implications
• Outcome data is needed to establish validity of a
surrogate marker
First steps
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•
•
•
Appropriate, disease-sensitive imaging
Uniformly acquired with objective QA
Quantitatively assessed
Centrally accessible with metadata
Image Processing ‘validation’
Lung nodule volume growth
Time Difference = 130 days
linear dimension increased 8 mm -> 11 mm in 4 months
A.P.Reeves, Cornell University, 1999
Why not calculate volumes?
• No fully automatic, objective methods
• Semi-automatic methods are timeconsuming, labor-intensive, and/or not
user-friendly.
Inhomogeneity problem
“Non-cytoreductive”(i.e. functional)
measures
•
•
•
•
•
FDG-PET
DCE-MRI
MR spectroscopy
CT density and contrast dynamics
Future:
– Other PET ligands
– Macromolecular MR agents
– Optical methods
PET, CT, hybrid PET/CT for
GIST response to imatinib (Gleevec)
baseline
7 wks post rx
G. W. Goerres et al, Univ Hosp Zurich
Concerns about assessing 18FDG uptake in
malignant tissue:
Visual: subjective
Standardized Uptake Value (SUV): semiquantitative
Kinetic analysis: quantitative
DCE MRI VEGF Inhibition time after contrast bolus (PTK/ZK
TK inhibitor oral dose results on colon mets)
Morgan B et al, JCO 2003
Chemotherapy Response by MRI & MRS
1 wk
pre-Tx
76 cc
Day 1
AC x1
79 cc
593
486
Day 42
AC x3
26 cc
Day 70
AC x4
25 cc
Day 112
taxol x2
11 cc
267
79
481
partial response to AC, regrowth on taxol
final pathology - viable IDC and extensive DCIS
Day 178
taxol x4
6 cc
595
Univ. of Minnesota
NCI-FDA Interagency Oncology
Task Force
• Imaging Science Development for Oncologic
Applications – Work in Progress
– Develop volumetric anatomical imaging for oncology
e.g. revise (RECIST)
– Develop standard dynamic (contrast) imaging
techniques for oncologic drug development and as
surrogate endpoint for drug approvals
– Validate FDG-PET for oncologic drug development
and as a surrogate endpoint for drug approvals
– Develop a pathway for accelerating molecular
imaging including ‘first in human’ studies in diagnosed
cancer patients
Foci on imaging
• NCI: Development and optimization of cancer
specific CAD methods
• NIBIB: Development of advanced algorithms and
generic image processing methods, code
documentation, open source software.
• NLM: Open source software and related data
processing platforms.
• NSF: Advanced algorithm development, specialized
hardware, GRID computing resources.
• FDA: Development of standards for database
development and
• NIST: Measurement of performance of application
specific software.
Imaging methods validated as cancer biomarkers.
Objectives:
1. Increase imaging studies, using standardized
acquisition protocols, in NCI-funded therapy trials
2. Collate imaging data from all NCI-funded trials, e.g.,
in Cancer Centers, Cooperative Groups, CCR, etc.
3. Engage FDA through Inter Organization Task Force
4. Develop cadre of oncology imaging specialists in
Cancer Centers
5. Develop functional imaging committees in all
Cooperative Groups
6. Develop volumetric and functional “RECIST”
criteria
CIP Near Term Goals: Data
Collection
Develop validated data collections:
• Lung nodules (FNIH Demonstration Project)
– for Detection, Classification, rx. Response
• Liver mets - rx response
• Colon polyps - screening detection,
classification
• Breast digital mammo - detection,
classification
Clinical Imaging Concerns
• Only 2% of all cancer patients are in formal
clinical trials
• Unless genetics is found to be deterministic, (all)
cancer therapy will continue to be experimental
• Conventional diagnostic imaging provides
(barely quantitative) information when following
a course of therapy