Profile: CT Lung Nodule Volume Measurement for Primary/Regional Nodes and Metastatic Sites

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 (CT Storage)

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

V-Cursor: None; proven DICOM (SR Storage w Templates, e.g. Chest CAD)

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

V-Cursor: Need Sample Implementation

Chest CAD polylines or New DICOM Segmentation objects (by pixel) are likely sufficient, but should try out a sample implementation to confirm (and identify key Details to require in the Profile).

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%. 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

Groundwork: 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: Image Acquisition

Detail: The acquisition system shall support saving and easily calling up saved acquisition protocols by UPICT or ACRIN proper name.

Detail: The acquisition system shall support configuration of the following acquisition parameters that lend themselves to single breath hold images with eventual display of isotropic voxels at reconstruction intervals of 5 mm or less without gaps or interleaving.

D-Cursor: What acquisition parameters matter? (kVp, mA, …)

<Insert link to UPICT protocol specifications by Professor McNitt-Gray and colleagues>

D-Cursor: What value ranges constitute an acceptable “baseline”?

• Late Stage (IIIb and IV) Lung Cancer in World Wide Clinical Trials (pharma base case): Outer ring of quality must be RI = 5 mm; next ring RI = 3 mm. Inner ring specified by Professor Mulshine and colleagues for top-shelf clinical trials of neoadjuvant therapy in earlier stage disease at RI < 1.5 mm

D-Cursor: What uniform language should be used for documenting image acquisition protocols in the profile.

<Insert link to table supplied for ACRIN 6678>

<Insert link to table supplied for NLST>

<Manufacturers should provide CDs with acquisition parameters as they did for the MRI study of brain volumes to the Alzheimer's Disease Neuroimaging Trial sponsored by the Foundation for NIH>

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>

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? Precision of measurement is the primary objective. Accuracy is less important to the base case for pharma. Accuracy becomes increasingly important to the inner rings of quality, reaching its maximum in screening studies of asymptomatic people with risk factors for lung cancer.

D-Cursor: What repeatability is initially sufficient to be useful?

D-Cursor: What accuracy/repeatability can be easily achieved?

<Insert link to relevant Groundwork>

<Insert link to very preliminary image analysis in very-best-case-scenario of extremely well demarcated, simple lung nodules which suggest test-retest variability is less than 1% when RI is 5 mm>

D-Cursor: What is the theoretical limit for accuracy/repeatability with typical equipment

<Insert link to relevant Groundwork>

<Insert links to image analysis of well demarcated tumors in the MSKCC coffee break images as the most optimistic boundary, and analysis of complex masses invading solid tissues as the most realistic boundary. First link will be to image analysis by RadPharm, Inc. Other links will be provided by software developers as the data become available.

Detail: The measurer shall be able to diagnose Progressive Disease at one half the change in volume associated with RECIST line-lengths.

D-Cursor: What do we need to specify about the measurer? Human oversight will be required. In the first stage, a trained technologist or image analysis specialist will select tumors for automatic boundary demarcation. In the next stage, the image analysis specialist will be able to manually correct portions of the boundary where either the algorithm failed or the mass becomes too complex to reliably follow over the course of treatment. In the final stage, a trained radiologist will accept or revise the mark ups.

D-Cursor: What is the limit on accuracy/repeatability due to the measurer (reader)? The limit of inter-rater reliability will be such that thresholds for diagnosing Progressive Disease will be within one time-point assessment in a series of time-points for patients enrolled in longitudinal trials. The need for adjudication between discrepant time-point assessments will be less for volumetric image analysis than for ordinary RECIST 1.1 assessments.

See 1A Reader Variability Study

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

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>

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

RECIST: References to the Response Evaluation Criteria In Solid Tumors are based on the article “New Guidelines to Evaluate the Response to Treatment in Solid Tumors”, by Patrick Therasse et.al., Journal of the National Cancer Institute, Vol. 92, No. 3, February 2, 2000, pp. 205-216. See also http://www.eortc.be/recist/ .

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.