Detecting Lung Nodules: Challenges and Solutions Geoffrey D. Rubin, MD, MBA, FACR, FSCBTMR
Learning Objectives Awareness of lung nodule detection performance Apply best practice for detection of lung nodules To review the status of computer assisted detection for lung cancer detection
Fun Facts 35% of lung cancers detected in NLST were < 10 mm 1-mm thick CT scan contains 9,000,000 lung voxels 10-mm lung cancer occupies 1200 voxels (0.013%) 4-mm lung cancer occupies 77 voxels (0.00085%)
Decide What to Detect Is it clinically relevant? Size 4 mm on incidence screen (Lu-RADS) 6 mm on a prevalence screen (Lu-RADS) 5 mm as incidental finding (Fleischner criterea) Character Composition: Solid, part solid, ground glass, calcified Shape: Spheroid or flat
What is important to detect?
Radiologist Performance Detecting Nodules Highly variable performance, particularly < 1 cm diameter Detecting Cancer Consistently excellent (~95%) sensitivity on incidence screens Missed cancers are small and detected on follow-up scan
12-mm Lung Cancers Different Patients
The Challenge of Thin Sections and Small (4-6 mm) Nodules
Methods 157 synthesized 5 mm nodules embedded in nodule-free lung CT scans to yield 40 CT volumes with between 3 5 nodules per scan 13 radiologists searched all scans using cinepaging 1.25-mm thick sections Radiol. 2015;274:276-286
Digitally Imbedded 5-mm Nodules N = 157 nodules Nodules Detected out of 157 100% 80% 60% 40% 20% 95% 90% 79% 68% 59% 53% 46% 41% 32% 26% 19% 14% 8% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 Readers Detecting out of 13 Radiology 2015 274:276-286
Detecting 5-mm Nodules Detected Missed 100% 75% 49% Detected Overall 50% 25% 0% 1 2 3 4 5 6 7 8 Radiologists 9 10 11 12 13
Reading the Scan Stacked cine review of thin (< 2 mm) sections on a PACS viewing station is standard Search patterns are variable and result in varying degrees of lung coverage Developing a systematic approach and assuring undisturbed search should be productive strategies
Driller Scanner
Thin-slab Maximum Intensity Projection (TS-MIP) Benefit established for detection of small solid nodules Greatest benefit for less experienced readers Transverse plane has been shown to be more effective than coronal plane Eur Radiol. 2006;16:325 332
TS-MIP
TS-MIP 1-30 mm thick
1-mm vs. 7-mm Thickness
Computer-Aided Detection (CADe) Advantages When used as a second reader, more nodules are detected Reduces interobserver variability Inexhaustible Longitudinal tracking
Computer-Aided Detection Disadvantages When used as a second reader, it lengthens the interpretative process False positive detections must be rejected Blind Spots (location, composition) One size to fit all
Computer-Aided Detection Key Questions What are we willing to pay for enhanced sensitivity? What is the most effective design and workflow for CAD? Validation and quantitation of clinical CAD solutions
Godoy MCB, Kim TJ, White CS, et al. Benefit of computer-aided detection analysis for the detection of subsolid and solid lung nodules on thin- and thick-section CT. AJR. 2013 Jan;200(1):74 83. 155 nodules: 74 solid, 22 part solid, 59 GGO 4.0 27.5 mm, (5.5 mm average) Thick = 5 mm & Thin = 1 mm 4 readers, performance averaged
Godoy MCB, Kim TJ, White CS, et al. AJR. 2013 Jan;200(1):74 83. FP Solid Subsolid GGO 1 2.25 0.5 1.5 0.25 0.75 R C -thi AD ck -th + in R C -th AD ic -th k + ic k Al AD C R C -th AD in -th + in on e in th R- th ic k 0 R- Sensitivity 0.75 0 False Positives 3
European Journal of Radiology 82 (2013) 1332 1337 6 radiologists, 207 nodules in 50 CT scans Concurrent Reader Second Reader Reading Time 132 s 210 s Sensitivity 70% 72%
Computer-Aided Detection (CAD) Variable performance with different CAD implementation Know your system Consider what CAD is tuned to detect Solid, ground-glass, atypical locations (endobronchial, juxtamediastinal) How will you use CAD? Screening tool (primary reader) Inexhaustible assistant (secondary reader)
Summary Detecting all nodules through unassisted reading of transverse sections is impossible A clear understanding of what is clinically important and use of TS-MIP will improve performance CAD should become a critical element for effective interpretation as standards for its use are developed and radiologist-friendly workflows are developed This should happen soon.