Tumor measurement criteria milestones 1981 2000
This presentation is the property of its rightful owner.
Sponsored Links
1 / 30

Tumor Measurement Criteria milestones - 1981 & 2000 PowerPoint PPT Presentation


  • 103 Views
  • Uploaded on
  • Presentation posted in: General

Tumor Measurement Criteria milestones - 1981 & 2000. RESPONSE EVALUATION CRITERIA IN SOLID TUMORS (RECIST) New Guidelines to Evaluate the Response to Treatment in Solid Tumors

Download Presentation

Tumor Measurement Criteria milestones - 1981 & 2000

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Tumor Measurement Criteriamilestones -1981 & 2000

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: 205-216, 2000

TUMOR RESPONSE CRITERIA WORLD HEALTH ORGANIZATION(WHO)

WHO Handbook for Reporting Results of Cancer Treatment

World Health Organization Offset Publication No. 48Geneva, Switzerland, 1979

————————————————————————————

Reporting Results of Cancer Treatment

AB Miller, B Hogestraeten, M Staquet, A Winkler

Cancer 47:207–14, 1981


WHO bi-linear measurement

Baseline

8 Weeks


RECIST CriteriaResponse 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 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


baseline

20 weeks (PR at - 39%)

24 weeks (PR confirmed - 52%)

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

  • 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 time-consuming, 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 forGIST response to imatinib (Gleevec)

baseline

7 wks post rx

G. W. Goerres et al, Univ Hosp Zurich


Visual: subjectiveStandardized Uptake Value (SUV): semi-quantitativeKinetic analysis: quantitative

Concerns about assessing 18FDG uptake in malignant tissue:


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

Day 42

AC x3

26 cc

Day 70

AC x4

25 cc

Day 112

taxol x2

11 cc

Day 178

taxol x4

6 cc

486

593

267

79

481

595

partial response to AC, regrowth on taxol

final pathology - viable IDC and extensive DCIS

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 specificCAD 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:

  • 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


CIP Near Term Goals: Data CollectionDevelop 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


  • Login