Randy D Ernst 1 , Russell C Hardie 2 , Metin N Gurcan 3 , Aytekin Oto 1 , - PowerPoint PPT Presentation

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  1. Randy D Ernst1, Russell C Hardie2, Metin N Gurcan3, Aytekin Oto1, Steve K Rogers3, Jeffrey W Hoffmeister3 1. Department of Radiology, The University of Texas Medical Branch, Galveston TX 2. iCAD Inc. and University of Dayton, Dayton OH 3. iCAD Inc., Beavercreek OH CAD Performance Analysis for Pulmonary Nodule Detection: Comparison of Thick- and Thin-Slice Helical CT Scans

  2. Introduction • This study compares the performance of a CAD (QuickCue™, iCAD, Inc.) system in detecting lung nodules from thick- and thin-slice multi-detector row CT scans, and to evaluate the potential benefit of CAD on radiologist sensitivity.

  3. Methods and Materials • 57 reports reviewed retrospectively • Case selection: • Obtained during a 5-month period • Referred from multiple departments • Contain at least 1 pulmonary nodule but fewer than 10 nodules to localize • Have no significant breathing miss - registration, post surgical changes, pleural effusions & atelectasis

  4. Methods and Materials • 4-detector LightSpeed QX/I Scanner, GE systems • HQ setting with 5.0 collimation, helical pitch of 0.75/1.0 • Standard-dose (160 - 270 mA, 120 kVp) • Images were reconstructed at 5 mm (thick) and 2.5 mm (thin) slice thicknesses.

  5. Methods and Materials • 140 nodules (3 mm - 25 mm) were identified • pre-CAD by radiologists • From thick-slice cases only. • Cases with multiple nodules were excluded. • Truth marks were mapped to the thin-slice data • Mean nodule size 7.3 ± 4.2 mm (3 – 25 mm) • Gold standard for nodule truth comes for post-CAD Radiologist review • One gold standard for thick-slice and one for thin-slice

  6. CAD System(QuickCue™, iCAD Inc.) DICOM Images 3D Lung Segmentation 3D Candidate Segmentation Calculate Features Classifier Detection Mask

  7. Review of Thick-Slice CAD Results • CAD detected 72.1% (101/140) of the pre-CAD truth nodules • CAD detected 35 additional radiologist-confirmed nodules, an increase of 25% (35/140) in sensitivity • 5.6 (317/57) false-positives per case • 55 due to atelectasis • 18 due to scarring

  8. Venn Diagram for Thick Pre-CAD Review CAD 0 0 317 101 35 39 3 Post-CAD Review Gold Standard

  9. Review of Thin-Slice CAD Results • CAD detected 80.7% (113/140) of the pre-CAD truth nodules. • CAD detected 94 additional radiologist-confirmed nodules, an increase of 67.1% (94/140). • 4.6 (262/57) false-positives per case. • 70 due to atelectasis • 39 due to scarring

  10. Venn Diagram for Thin Pre-CAD Review using thick-slice with detections mapped to thin-slice CAD using thin-slice 0 0 262 113 94 26 0 Post-CAD Review of thin-slice Gold Standard

  11. Comparison

  12. FROC Curve for CAD

  13. CAD detections in Thick-Slice Additional Detections

  14. CAD detections in Thin-Slice Additional Detections

  15. Case Follow-up • 5 primary lung cancers • 24 cases of metastatic cancer including • 7 lymphomas, 4 breast, 4 head and neck, 2 colon, 2 pancreas, 1 carcinoid, 1 seminoma,  1 ovarian, 1 melanoma and 1 tracheal papillomatosis • 23 cases of infection, including • 19 granulomatous disease either calcified, stable on follow-up or biopsy proven. 4 were presumed infection that resolved with follow-up • 1 case proved to be a thrombosed AVM • 4 cases lost to follow up

  16. Example TPs • Examples of nodules that are detected by both radiologist and CAD

  17. Example TPs • Examples of nodules that are initially missed by radiologists then detected after reviewing CAD

  18. Review of CAD Results • Sources of false positives • Vessel intersections • Inaccurate lung segmentation • Partial volume effects • Other lung abnormalities (scarring, atelectasis)

  19. Example FPs

  20. Review of CAD Results • Sources of false negatives (missed nodules) • Low density, irregular • Strong connectivity with vessels • Imperfect candidate segmentation • Inaccurate lung segmentation

  21. Example FNs

  22. Conclusions • Preliminary results indicate that both sensitivity and specificity of the CAD system increases when used with thin-slice scans versus thick-slice scans. • The CAD system operating on both thick- and thin-slice scans improved radiologist sensitivity • Improvement was greater for CAD operating on thin-slice scans