Difference between revisions of "Profile: CT Lung Nodule Volume Measurement for Primary/Regional Nodes and Metastatic Sites"

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: V-Cursor: None; proven DICOM
 
: V-Cursor: None; proven DICOM
  
Claim:  Can measure lung nodule volume with accuracy of X and repeatability of Y
+
Claim:  Can create, store, and retrieve mark ups of lung masses, i.e., region of interest (ROI) boundaries
 +
: D-Cursor: No compelling evidence that ROIs can be stored in DICOM in a way that is accessible to non-DICOM experts despite V-Claim of theoretical capacity. No evidence that third party image analysis software developers can move their ROI output into DICOM headers.
 +
 
 +
Claim:  Can measure lung nodule volume with repeatability of one half of one half of the RECIST threshold for making a diagnosis of Progressive Disease. For uniformly expanding cubes and solid spheres, an increase in the uni-dimensional Longest Diameter corresponds to an increase in volume of about 72%. In order to diagnose PD at a change of about one half that volume, 36%, the noise needs to be less than about 18%. The claim is thus somewhat hopefully set to a test-retest variability of less than 15%-to-20%.
 
: V-Cursor: Demonstrate this accuracy and repeatability is easily achievable
 
: V-Cursor: Demonstrate this accuracy and repeatability is easily achievable
:: ''<Insert link to relevant Groundwork>''
+
:: Relevant Groundwork Link 1: Test-Retest measurements of FDA phantoms, i.e., very-best-case-scenario, with variability one order of magnitude less than variability in "real life", i.e., algorithm returns variability of less than 1.5%
:: ''<Should we be further qualifying it as applicable to a certain stage or type of lung nodule?>''
+
:: Relevant Groundwork Link 2: Test-Retest measurements of small sample of NIST cases, i.e., nearly-best-case-clinical-scenario, with variability for measurement of isolated, simple lung nodules of less than 3% (up to 4 times the noise in phantoms and less than one fifth the noise expected in real life scenarios).
 +
:: Relevant Groundwork Link 3: Test-Retest measurements of a few well behaved masses in the MSKCC coffee break study of less than 10% between Image Set 1 and Image Set 2 of each patient studied twice in succession. This 10% threshold is somewhat capriciously based on the assumption that the precision of measurement in selected MSKCC coffee break nodules will be twice as good as that which can be achieved in most clinical trial scenarios.
  
 
==Profile Details (what equipment and users must do to achieve it)==
 
==Profile Details (what equipment and users must do to achieve it)==

Revision as of 16:08, 19 January 2009

Please review and consider:

  • are the claims appropriate, useful, sufficient
  • would it make sense to move any claims to a different profile

Note:

  • V-Cursor = Precursor Question about validating a Profile Claim; D-Cursor = Precursor Question about determining a Profile Detail
  • this is a skeleton to get an idea of what it might look like; details are still missing


Profile Claims (what users will be able to achieve)

Claim: Can create, store, retrieve images of lung nodules

V-Cursor: None; proven DICOM

Claim: Can create, store, retrieve linear, area and volume measurements made on lung nodule images

V-Cursor: None; proven DICOM

Claim: Can create, store, and retrieve mark ups of lung masses, i.e., region of interest (ROI) boundaries

D-Cursor: No compelling evidence that ROIs can be stored in DICOM in a way that is accessible to non-DICOM experts despite V-Claim of theoretical capacity. No evidence that third party image analysis software developers can move their ROI output into DICOM headers.

Claim: Can measure lung nodule volume with repeatability of one half of one half of the RECIST threshold for making a diagnosis of Progressive Disease. For uniformly expanding cubes and solid spheres, an increase in the uni-dimensional Longest Diameter corresponds to an increase in volume of about 72%. In order to diagnose PD at a change of about one half that volume, 36%, the noise needs to be less than about 18%. The claim is thus somewhat hopefully set to a test-retest variability of less than 15%-to-20%.

V-Cursor: Demonstrate this accuracy and repeatability is easily achievable
Relevant Groundwork Link 1: Test-Retest measurements of FDA phantoms, i.e., very-best-case-scenario, with variability one order of magnitude less than variability in "real life", i.e., algorithm returns variability of less than 1.5%
Relevant Groundwork Link 2: Test-Retest measurements of small sample of NIST cases, i.e., nearly-best-case-clinical-scenario, with variability for measurement of isolated, simple lung nodules of less than 3% (up to 4 times the noise in phantoms and less than one fifth the noise expected in real life scenarios).
Relevant Groundwork Link 3: Test-Retest measurements of a few well behaved masses in the MSKCC coffee break study of less than 10% between Image Set 1 and Image Set 2 of each patient studied twice in succession. This 10% threshold is somewhat capriciously based on the assumption that the precision of measurement in selected MSKCC coffee break nodules will be twice as good as that which can be achieved in most clinical trial scenarios.

Profile Details (what equipment and users must do to achieve it)

The profile defines the following roles and several transactions and activities they participate in:

  • Acquisition System
  • Measurement System
  • Measurer
  • ...

Activity: Acquisition System Calibration

... <If determined to be necessary>

Activity: Patient Preparation

Activity: Image Acquisition

Detail: The acquisition system shall support saving and using saved acquisition protocols

Detail: The acquisition system shall support configuration of the following acquisition parameters

D-Cursor: What acquisition parameters matter? (kVp, mA, …)
<Insert link to relevant Groundwork>
D-Cursor: What value ranges constitute an acceptable “baseline”?
<Perhaps tie ranges to performance levels, e.g. Level 2 parameters might be sufficient for 1cm+ nodules, but Level 3 parameters are required for less than 1cm nodules>\
D-Cursor: What uniform language should be used for documenting image acquisition protocols in the profile
CT Acquisition Protocol Groundwork

Detail: The acquisition system shall produce images with the following characteristics

D-Cursor: What image characteristics matter? (resolution, noise level?)
<Insert link to relevant Groundwork>

Activity: Image Reconstruction

Transaction: Transfer Images

Detail: The acquisition system shall support DICOM CT Storage as SCU.

Detail: The measurement system shall support DICOM CT Storage as SCP and DICOM Q/R as SCU

Activity: Measurement

Detail: The measurement system shall support the following measurements:

D-Cursor: What measurements are useful for evaluating lung nodules
  • Bitvol <because it is the typical “detailed” volume measurement>
  • RECIST <because it is the current gold standard and we need it to compare>
  • Modified RECIST (J. Natl. Cancer Inst. 2008;100:698-711) <to support wider cancer etiology than HCC>
<consider just adding a bunch of tools if they are easy to implement>
D-Cursor: What accuracy is initially sufficient to be useful?
D-Cursor: What repeatability is initially sufficient to be useful?
D-Cursor: What accuracy/repeatability can be easily achieved?
<Insert link to relevant Groundwork>
D-Cursor: What is the theoretical limit for accuracy/repeatability with typical equipment
<Insert link to relevant Groundwork>

Detail: The measurer shall …

D-Cursor: What do we need to specify about the measurer?
D-Cursor: What is the limit on accuracy/repeatability due to the measurer (reader)?
See 1A Reader Variability Study

<Should we add an Activity: Measurer Training to train/confirm the skill of each measurer>

Transaction: Transfer Measurements

QIBA Profile: CT Lung Nodule Volume Change

This profile presumes the CT Lung Nodule Volume Quantification Profile is already supported by the participating systems.

Profile Claims (what users will be able to achieve)

Claim: Can determine tumor volume change based on comparison of measurements from multiple studies

V-Cursor:

Claim: Can achieve change accuracy of X and repeatability of Y

V-Cursor: Demonstrate this accuracy and repeatability is easily achievable
<Insert link to relevant Groundwork>

Profile Details (what equipment and users must do to achieve it)

Activity: Patient Preparation

QIBA Profile: CT Lung Nodule Response

This profile presumes the CT Lung Nodule Volume Change Profile is already supported by the participating systems.

Profile Claims (what users will be able to achieve)

Claim: Can determine tumor "response" based largely on a change in measured volume

V-Cursor: Demonstrate that tumor response is adequately correlated with volume change
<Insert link to relevant Groundwork>

Claim: Can achieve a certain degree of confidence.

V-Cursor:
<Insert link to relevant Groundwork>

Profile Details (what equipment and users must do to achieve it)

D-Cursor: What other details must also be recorded


To Do

  • Split other profiles to separate pages once the structure/content stabilizes a bit
  • Review standard requirements traceability structures to see if they can help/be used
  • Consider regrouping the Details under the Roles rather than Activities if that makes it clearer what each system or person must do to comply.