nodules detected during CT lung-cancer screening, if sharper reconstruction filters are utilized. ... disease (five-year survival of 60%-80%).2-5 The superior lung-nodule detection .... Radiologic evaluation of the solitary pulmonary nodule.
Calcification classifications of small nodules identified during CT lung-cancer screening Philip F. Judya, Roberto Rivaa, Yoshiko Kadotaa,b, Francine L. Jacobsona Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis St., Boston MA 02115, b Department of Radiology, National Defense Medical College, Japan a
ABSTRACT The aim of this study was to determine whether radiologists are more likely to report as calcified the small nodules detected during CT lung-cancer screening, if sharper reconstruction filters are utilized. Images were reconstructed with the 2 filters used at our institution for the lung (B50f) and for the mediastinum (B30f). The 4 lung-cancer screening cases were reconstructed with 1.25-mm section thickness at 0.6-mm section increments. Using a lax criterion, 2 radiologists identified the locations of nodular features and rated the likelihood that the features were calcified. There were 302 nodules reports. More of these (57%) were reported on images reconstructed using the smooth filter. Sixty (60) reports were definitely or possibly calcified. Seventy-three percent (73%) calcification reports were from images reconstructed using B50f. There were 27 calcification reports of one of the radiologist that were classified as non-calcified by the other radiologist. Most of calcification reports (81%) of 27 reports on which radiologists disagree regarding the likelihood of calcification were from images reconstructed using B50f. Radiologists are more likely to report small nodules detected during lung-cancer screening as calcified using the sharper reconstruction filter. Whether these nodules are actually calcified or not remains a question. Keywords: computed tomography, lung cancer, screening, reconstruction filter, calcification
1.0 INTRODUCTION Lung cancer is the most common cause of cancer death in the industrialized world.1 More people die of lung cancer than of colorectal, breast, and prostate cancer combined. Lung cancer was diagnosed in 171,900 individuals in USA and 157,200 individuals died of it in 2003 (i.e., 15% five year survival). However, individuals detected with early stage lung cancer and who are treated will often outlive their disease (five-year survival of 60%-80%).2-5 The superior lung-nodule detection sensitivity of CT has lead to considerable interest in using CT to screen for lung cancer.6-8 The National Lung Screening Trial (NLST) is evaluating the potential of CT to detect early stage lung cancer and reduce mortality from lung cancer.9 The NLST protocol specifies that the images be reconstructed using a filter that is smoother than was used in our lung-cancer screening program before we joined NLST. The sharper reconstruction filter is felt to improve the definition of lung detail and has supporters.10,11 Hence, our interest in comparing reconstruction filters. The rational for using a smoother reconstruction filter is that sharper reconstruction filters have some degree of edge enhancing incorporated into the filter. The edge enhancement produces image artifacts resembling calcification in the image of the nodule.12 Since most small nodules identified by CT are benign; radiologists desire a scheme to eliminate benign nodules from further evaluations. The presence of calcification in a nodule indicates that the nodule is likely to be benign, because more than 90% of calcified nodules are benign. The fraction calcified nodules that a benign increases as nodule size decreases. Consequently, misclassification of a nodule as calcified could have serious consequences; a nodule with a likelihood of being malignant is misclassified as benign. While considerable research has demonstrated that quantitative CT methods can account for the consequences of reconstruction filter differences and
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accurately determine whether calcification is present in a nodule,13 in practice, radiologist decisions are based on whether calcifications are visible within nodules. Quantification is considered unnecessary. Why did radiologists at my institution use a sharper reconstruction filter? They preferred the sharper images. Our hypothesis was that the radiologists discounted the noise or enhancement image features that mimic calcifications because such features were visible in both nodules and vessels. Their strategy was to compare nodule “contents” with the “contents” of features identified as vessels. This is a discrimination task, not a task of detection of calcification within the nodule. The hypothesis implies that radiologists are equally likely to report a nodule as calcified whether a sharper reconstruction filter or smoother reconstruction filter is used
2.0 METHODS AND MATERIALS 2.1 Radiologist Procedures Two radiologists used a lax criterion to identify suspicious locations on 4 low-dose CT cases and rate the likelihood that the identified locations were calcified. The radiologists used a workstation dedicated to the evaluation of chest CT images (Siemens LungCARE). Radiologists could toggle between lung and mediastinal display windows and also used sliding MIPS slabs. They both had considerable experience using this workstation to evaluate CT studies performed for purpose of lung cancer detection. The radiologists used the annotation feature of the workstation to rate with a 4-category scale the likelihood that the feature was calcified and simultaneously identify the location of the feature. The location and ratings were transferred to a Microsoft Access database for evaluation. The radiologists knew the experiment’s hypothesis. These are the written instructions provided to the radiologists: Task: To identify all nodule features present, attempt to determine size of the nodule using LungCare and to annotate making 2 ratings. A.
Confidence that identified feature is actually a nodule NH No high confidence NM No medium confidence NL No low confidence YL Yes low confidence YM Yes medium confidence YH Yes high confidence
B.
Degree of calcification NCH Not Calcified-High Confidence NCL Not Calcified-Low Confidence CaL Calcified- Low Confidence CaH Calcified-High Confidence
During the first evaluation of the 4 cases each radiologist viewed half of B50f conditions and half the B30f conditions. The B50f-condition cases of one radiologist were B30f-condition cases of the other radiologist. During the second evaluation of the 4 cases the reconstruction-filter conditions were reversed. 2.2 Data Acquisition A single acquisition of projection data was obtained of the 4 lung-cancer screening cases using the Siemens Volume Zoom. A 4x1-mm detector collimation was used. A spiral acquisition was used. The CT gantry rotated at 0.5 second per rotation rate with a feed of 8 mm per rotation (pitch=2.0). X-ray tube current was 80 mA, that is, (40 mAs per rotation or 20 mAs effective). The x-ray tube potential was 120 kVp.
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2.3 Image Reconstruction Exams of the 4 patients used the B50f reconstruction filter (a sharp filter equivalent to BONE of GE scanners) and the B30f reconstruction filter (a smooth filter equivalent to STANDARD of GE Scanners). The section thickness was 1.25 mm and images were reconstructed at axial increments of 0.6 mm.
3.0 RESULTS Using the lax criterion, 302 nodules reports were available for analysis. All reports indicated that the identified features were nodules. A larger number of reports (57%) were from images reconstructed using the smooth filter (B30f) than from images reconstructed using the sharp filter (B50f). Of these 302 reports, 60 reports were definitely or possibly calcified and 73% of these calcification reports were from images reconstructed using the (B50f) sharper filter. The radiologists disagreed whether features were calcified on 27 occasions, that is 45% of calcification reports. Table 1. tabulates the reconstruction filters of the images with features rated as calcified when the other radiologist rated features as non-calcified. Images reconstructed with B50f contributed 82% of the calcification reports when there was a disagreement regarding the likelihood that a feature was calcified.
Radiologist
B50f
B30f
1
7
0
2
15
5
Table 1. Sources of features rated as calcified when other radiologist rated features as non-calcified
4.0 DISCUSSION Radiologists are more likely to report small nodules detected during lung-cancer screening as calcified using the sharper reconstruction filter, consequently more nodules may be classified as benign when sharper reconstruction filters are used. Whether the nodules are actually calcified or not remains a question. Some of the nodular features are very small and may represent “micro-calcification” that are only recognized as calcifications because a sharp reconstruction filter was used. Other nodule features may “contain” artifactual calcifications or noise that radiologist do not recognize as such. Among the reasons that non-calcified nodules might be classified as “containing” calcifications using sharper reconstruction filters are 1) edge enhancement and 2) higher pixel noise. These preliminary results suggest that radiologists do not discount the noise or the enhancement image features that mimic calcifications, when evaluating whether small nodular features are calcified. Of interest, the radiologists were apparently not inhibited reporting of nodules on images that were reconstructed using the smoother filter, because they reported more nodules using images reconstructed with the smoother filter. The lower perceived noise might have increased their confidence regarding the likelihood that a feature was a nodule. At our institution CT images use for lung-cancer screening are reconstructed with both smooth and sharp reconstruction filters.
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REFERENCES 1. Jemal A, Murray T, Samuels A, Ghafoor A, Ward E, Thum MJ. Cancer Statistics, 2003. CA Cancer J Clin 2003; 53:5-26. 2. Williams DE, Pairolero PC, Davis CS, et al. Survival of patients surgically treated for stage I lung cancer. J Thorac Cardiovasc Surg 1981; 82:70-6. 3. Martini N, McCaughan BC, McCormack P, et al. Lobectomy for stage I lung caner. In: Kittle CF, ed. Current controversies in thoracic surgery. Philadelphia: Saunders, 1986:171-4. 4. Mountain CF. Revisions in the international system for staging lung cancer. Chest 1997; 111:1710-17. 5. Naruke T, Tsuchiya R, Kondo H, Asamura H, Nakayama H. Implications of staging in lung cancer. Chest 1997; 112:242S-248S. 6. Kaneko M, Eguchi K, Ohmatsu H, et al. Peripheral lung cancer: screening and detection with low-dose spiral CT versus Radiography. Radiology 1996; 201:798-802. 7. Sone S, Takashima S, Li F, et al. Mass screening for lung cancer with mobile spiral computed tomography scanner. Lancet 1998; 351:1242-45. 8. Henschke CI, McCauley DI, Yankelevitz DF, et al. Early lung cancer action project: overall design and findings from baseline screening. Lancet 1999; 354:99-105. 9. Hillman BJ; ACRIN. Economic, legal, and ethical rationales for the ACRIN national lung screening trial of CT screening for lung cancer. Acad Radiol. 2003 Mar; 10(3): 349-50. 10. Webb WR. Radiologic evaluation of the solitary pulmonary nodule. AJR Am J Roentgenol. 1990 Apr; 154(4): 701-8. 11. Zwirewich CV, Terriff B. High-spatial-frequency (bone) algorithm improves quality of standard CT of the thorax. AJR Am J Roentgenol. 1989 Dec; 153(6): 1169-73. 12. Swensen SJ, Morin RL, Aughenbaugh GL, Leimer DW. CT reconstruction algorithm selection in the evaluation of solitary pulmonary nodules. J Comput Assist Tomogr. 1995 Nov-Dec; 19(6): 932-5. 13. Zerhouni EA, Spivey JF, Morgan RH, Leo FP, Stitik FP, Siegelman. Factors influencing quantitative CT measurements of solitary pulmonary nodules. J Comput Assist Tomogr. 1982 Dec; 6(6): 1075-87
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