VolCT - Group 1A

Current Goals & Status:

• Goal: Benchmark intra/inter-reader variability for lung nodule volume measurements
  • Status: Most of Dataset acquired; finalizing reader software
  • Related Profile:

Work Documents

• Vol-CT - 1A Group Call Summaries
• Proposed 1A Protocol Outline (2008-11-13-v05)- For Comment from QIBA Members

Projects

May want to split these out to separate pages later

VolCT Lung Anthropomorphic Phantom Study

Objective:

Measure intra- & inter-reader bias and variability phantom lesions for:

• Uni-dimensional size measurement
• Semi-automatic 3D volumetric measure

May compare with fully automated algorithm(s)

Dataset:

Ground truth has been established by physical measurement "ex vivo“ on FDA phantom inserts.

Nodules (10 attached nodules)

• -10 & +100HU
• 10, 20 mm spheres
• 10 mm ovoid, lobulated, spiculated

Image Dataset

• 100 mAs exposures
• 0.75 & 5.0 mm slices
• 1 recon kernel
• Status:
  • mostly acquired by FDA/CDRH/OSEL.
  • Missing: 10 mm ovoid, spic, lob (Est: 12/01/08)

Acquisition Protocol:

• Scanner: Philips 16 slice
• Exposure (120 kVp): 100 mAs
• Slice thickness (50% overlap): 0.75 & 5.0 mm slices
• Recon kernel: Standard/medium (Still on table: Detail/Lung kernel)
• Pitch: 1.2
• 2 repeat scans
• 40 segmentations in set

The study is being conducted as a pilot. The size (data, readers) has not been selected for any specific level of significance.

Study Protocol:

Expert readers will measure/estimate nodule size from CT images.

Readers: 6 RadPharm radiologists

Software:

• Wendy will visit RadPharm and provide more info next week
• In-house review software (Siemens?)
  • Semi-automated 3D volume software
  • Uni-dimensional measure (RESIST)
• Which fully automated software?

Reading Session:

• Readers read all cases in 2 different reading sessions
  • Random ordering
    • One-dimensional measure
    • Semi-automated segmentation
  • Sessions separated by 3 week(?)
  • Include duplicate cases within each read session (1/3-1/2 of cases for intra-reader estimates)
• Time restrictions: Probably not (?)
• Specific instructions: Probably not (?)

Analysis:

Estimate intra- and inter-reader variability in the different volume estimate

• Estimate bias from known truth
• Estimate variability

Compare the bias and variability with the different methods