1. Tumor Measurement Criteria milestones - 1981 & 2000
TUMOR RESPONSE CRITERIA WORLD HEALTH ORGANIZATION (WHO)
WHO Handbook for Reporting Results of Cancer Treatment
World Health Organization Offset Publication No. 48 Geneva, Switzerland, 1979
————————————————————————————
Reporting Results of Cancer Treatment
AB Miller, B Hogestraeten, M Staquet, A Winkler
Cancer 47:207–14, 1981
RESPONSE EVALUATION CRITERIA IN SOLID TUMORS (RECIST)
New Guidelines to Evaluate the Response to Treatment in Solid Tumors
P Therasse, SG Arbuck, EA Eisenhauer, J Wanders, RS Kaplan, L Rubinstein, J Verweij, M Van Glabbeke, AT van Oosterom, MC Christian, SG Gwyther
Journal of the National Cancer Institute 92: , 2000
Initially WHO and now RECIST guidelines for tumor measurement assessment have standardized time to progression determinations. 

2. WHO bi-linear measurement
Baseline
8 Weeks

3. 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

4. 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

5. 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

9. RECIST
RECIST criteria may be employed by NCI-funded 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

10. 24 weeks (PR confirmed - 52%) 52 weeks (- 74%)
baseline
20 weeks (PR at - 39%)
24 weeks (PR confirmed - 52%)
52 weeks (- 74%)
Rx epothilone
metastatic renal cell

11. baseline 13 wks (– 7 %) 27 wks (PR – 43 %) metastatic renal cell
Rx with epothilone a microtubular apparatus stabilizer
metastatic renal cell

12. FDA reform plans

13. 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

14. 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

15. First steps Appropriate, disease-sensitive imaging
Uniformly acquired with objective QA
Quantitatively assessed
Centrally accessible with metadata

16. Image Processing ‘validation’
‘live wire’ algorithm boundary tracing vs region-growing ‘validation’ is just ‘accuracy’

18. Lung nodule volume growth
Time Difference = 130 days
linear dimension increased 8 mm -> 11 mm in 4 months
A.P.Reeves, Cornell University, 1999

19. Why not calculate volumes?
No fully automatic, objective methods
Semi-automatic methods are time-consuming, labor-intensive, and/or not user-friendly.

20. Inhomogeneity problem

21. “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

22. PET, CT, hybrid PET/CT for GIST response to imatinib (Gleevec)
baseline
7 wks post rx
The value of PET, CT and in-line PET/CT in patients with gastrointestinal stromal tumours: long-term outcome of treatment with imatinib mesylate
G. W. Goerres1  ,
Univ Hosp Zurich
Fig. 2 a Coronal MIP image and transverse PET (top), CT (middle) and co-registered PET/CT images (bottom) of a 72-year-old female patient (patient 3) before the introduction of treatment with imatinib mesylate. A large FDG-avid and hypodense lesion is present in the liver, involving both lobes (white open arrows). FDG uptake in this large lesion is not homogeneous. On the MIP image a large lesion adjacent to the heart, which did not take up FDG, is visible (long black arrow). Smaller foci of increased tracer uptake are present in the middle and lower abdomen (small black arrows). b The lesion at the distal oesophagus shows intense FDG uptake (patient after total gastrectomy and splenectomy). c In the mid-abdomen and pelvis, several lesions were found corresponding to mesenteric lymph node involvement (white arrows) and uptake in the wall of non-enlarged bowel loops (white and black open arrows). The discrimination of such uptake from non-specific muscular FDG uptake is difficult. d Seven weeks after the beginning of treatment a control scan was obtained, showing complete remission on the PET image and partial remission on the ceCT scan (not shown). On the CT image of the PET/CT scan, the liver lesion was less dense than on the first scan, but had not shrunk
G. W. Goerres et al, Univ Hosp Zurich

23. Concerns about assessing 18FDG uptake in malignant tissue:
Visual: subjective Standardized Uptake Value (SUV): semi-quantitative Kinetic analysis: quantitative

24. DCE MRI VEGF Inhibition time after contrast bolus (PTK/ZK TK inhibitor oral dose results on colon mets)
Morgan B et al, JCO 2003

25. Chemotherapy Response by MRI & MRS
1 wk
pre-Tx
76 cc
Day 1
AC x1
79 cc
Day 42
AC x3
26 cc
Day 70
AC x4
25 cc
Day 112
taxol x2
11 cc
Day 178
taxol x4
6 cc
593
486
267 79
481
595
partial response to AC, regrowth on taxol
final pathology - viable IDC and extensive DCIS
Univ. of Minnesota

26. 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

27. 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.

28. Imaging methods validated as cancer biomarkers.
Objectives:
Increase imaging studies, using standardized acquisition protocols, in NCI-funded therapy trials
Collate imaging data from all NCI-funded trials, e.g., in Cancer Centers, Cooperative Groups, CCR, etc.
Engage FDA through Inter Organization Task Force
Develop cadre of oncology imaging specialists in Cancer Centers
Develop functional imaging committees in all Cooperative Groups
Develop volumetric and functional “RECIST” criteria

29. 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

30. 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
? Concept of living with cancer the way we live with atherosclerosis
CMS may now