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CT Histogram Analysis in Pathologically Proven Adrenal Masses

¹ Division of Radiology, Cleveland Clinic Foundation, 9500 Euclid Avenue, Desk A21, Cleveland, Ohio 44195.
² Department of Endocrinology and Metabolism, Cleveland Clinic Foundation, Cleveland, Ohio.

Received February 2, 2005; accepted after revision April 15, 2005.

 
Address correspondence to E. M. Remer (remere1{at}ccf.org).

Abstract

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OBJECTIVE. The purpose of this article is to evaluate a histogram analysis method for distinguishing adrenal adenomas from metastases, pheochromocytomas, and adrenocortical carcinomas on CT.

MATERIALS AND METHODS. A pathology database was searched, and 335 adrenalectomies from 1995 to 2002 were identified. CT images were available for retrospective review in 187 patients (93 males, 94 females; age range, 15-84 years; mean age, 55.2 years) with 208 adrenal masses. This included 112 adenomas in 104 patients, 48 metastases in 39 patients, 40 pheochromocytomas in 36 patients, and eight adrenocortical carcinomas in eight patients. Histogram analysis was performed using a circular region of interest for mean attenuation, number of pixels, number of negative pixels (< 0 H), and percentage of negative pixels by two interpreters. Areas of necrosis were excluded from measurements. Observer agreement was calculated.

RESULTS. In 72 of 76 (94.7%) and 63 of 72 (87.5%) adenomas, respectively, interpreters found attenuation values greater than 10 H contained negative pixels on unenhanced CT scans. None of the enhanced adenomas had mean attenuation less than or equal to 10 H, but 24 (38.7%) and 28 (45.2%), respectively, had negative pixels. Negative pixels were present in unenhanced and enhanced metastases, pheochromocytomas, and carcinomas. Using a 5% or 10% negative pixel threshold value to diagnose adenoma improved specificity but diminished sensitivity. Specificity for a 10% negative pixel threshold was approximately 88% for unenhanced CT scans and 99% for enhanced CT scans, with sensitivities of 71% and 12%, respectively.

CONCLUSION. Although specificity for the diagnosis of adenomas on enhanced CT scans with histogram analysis was high when a 10% negative pixel threshold was used, low sensitivity likely limits clinical usefulness.

Keywords: abdominal imaging • adrenal adenoma • adrenal carcinoma • adrenal gland • adrenal metastasis • CT imaging • pheochromocytoma

Introduction

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Commonly, an adrenal mass is discovered incidentally on a contrast-enhanced abdominal CT scan. In this situation, CT densitometry and enhanced attenuation washout methods cannot be used to assess if the mass is an adenoma because during routine CT examinations neither unenhanced nor delayed enhanced images are obtained. Bae et al. [1] reported a method to diagnose adrenal adenomas on routine enhanced abdominal CT examinations based on the distribution of tissue attenuation in the mass, termed "histogram analysis." With this technique, a region of interest (ROI) within an adrenal mass is measured—plotting the pixel attenuation versus pixel frequency on a standard CT workstation—and the number of pixels that measure fat attenuation (those < 0 H) are determined. Histogram analysis, like unenhanced CT densitometry, relies on the fact that adenomas contain large amounts of intracytoplasmic lipid [2]. Although promising, further confirmation of this technique in other patient populations is necessary before it can be widely accepted. This report applies the CT histogram analysis method in a group of masses that also include pheochromocytomas and primary adrenocortical carcinomas in addition to adenomas and metastases. Unlike the prior series, all diagnoses were confirmed by histopathology. Two different observers performed a histogram analysis of each mass in this series and their observer agreement was assessed.

Materials and Methods

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Our institutional review board approved this study, and informed consent was waived. A pathology database was searched and 335 adrenalectomies from 1995 to 2002 were identified. CT images were available for retrospective review in 187 patients (93 males, 94 females; age range, 15-84 years, mean age, 55.2 years) with 208 adrenal masses. CT scans were available for retrospective review. This included 112 adenomas in 104 patients, 48 metastases in 39 patients, 40 pheochromocytomas in 36 patients, and eight adrenocortical carcinomas in eight patients.

View larger version (140K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1A —48-year-old woman with left adrenal pheochromocytoma. Unenhanced CT scan shows region of interest (ROI) with mean attenuation of 38 H. Histogram superimposed on image shows distribution of pixels in ROI.

View larger version (141K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1B —48-year-old woman with left adrenal pheochromocytoma. Unenhanced histogram analysis shows 13 negative pixels.

View larger version (144K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1C —48-year-old woman with left adrenal pheochromocytoma. Enhanced image shows mean attenuation of 86 H.

View larger version (142K): [in this window] [in a new window] [as a PowerPoint slide]   Fig. 1D —48-year-old woman with left adrenal pheochromocytoma. Enhanced histogram analysis shows zero negative pixels.

CT Technique
CT scans were performed using single or MDCT units (Somatom Plus 4, Volume Zoom, or Sensation 16, Siemens Medical Solutions). Imaging protocols varied considerably over the review period because of changes in CT technology. Contrast-enhanced CT scans were obtained 60-70 seconds after IV administration of 150 mL of 300 mg I/mL nonionic contrast medium (most commonly iopromide; Ultravist 300, Berlex) injected at a rate of 2-4 mL/s using a power injector. Reconstruction thickness was 8 mm at 4-mm intervals from 1995-1999 and 5 mm at 2.5-mm intervals for 1999-2002. Detector collimation was 5 or 8 mm for single-row scanners and 2.5 or 5 mm for multirow scanners (120 kVp, 200-250 mAs). Images were reconstructed with a standard soft-tissue algorithm.

Data
All CT studies were retrieved from the institutional image archive to a clinical PACS workstation (MagicView 1000, Siemens Medical Solutions). Measurements were obtained as previously described [1]. For each examination, the image that contained the maximal cross-sectional diameter of the adrenal mass was chosen. Maximal diameter was measured. A circular ROI was placed on the adrenal mass, taking care to avoid the periphery of the mass to eliminate partial volume effects or any areas of necrosis (Figs. 1A, 1B, 1C, and 1D). Necrosis was defined as a focal area of hypoattenuation compared with the remainder of the adrenal mass. If possible, approximately two thirds of the mass was measured.

The ROI measures were displayed to include a histogram, mean attenuation, number of pixels, and range of pixel attenuation. The measurement tool was initially set to include a range of pixels from -1000 to 1000 H. The measurement was then repeated with the pixels' limits set at -1 to -1000 H, so that the number of pixels less than zero (negative pixels) could be counted. A subset of the mean attenuation values of unenhanced masses from 1995-2002 [3] and 1997-2002 [4] were published previously as parts of other series.

Data Analysis
The percentage of negative pixels was calculated by dividing the number of negative pixels by the total number of pixels for each adrenal mass. The percentage of adrenal masses with a mean attenuation of 10 H or less was calculated for unenhanced and enhanced studies of adenomas, metastases, pheochromocytomas, and adrenocortical carcinomas. The percentages of each type of adrenal mass that contained any, more than 5% negative pixels, and more than 10% negative pixels were calculated. Observer concordance was assessed by determining the percent agreement for each observation and then calculating kappa statistics [5].

Results

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Adrenal Adenomas on Unenhanced CT
The mean attenuation of the 105 unenhanced adenomas was 18.3 H ± 14.3 [SD] for interpreter 1 and 15.5 H ± 14.4 for interpreter 2 (Table 1). The range of attenuation values for interpreters 1 and 2 was -27 to 51 and -17 to 45.2, respectively. Only 29 of 105 (27.6%) and 33 of 105 (31.4%) unenhanced adenomas had attenuation of 10 H or less, but all contained negative pixels. Interpreter 1 found 72 of 76 (94.7%) and interpreter 2 found 63 of 72 (87.5%) adenomas with attenuation values greater than 10 H that contained negative pixels. The number of unenhanced adenomas with the percentage of negative pixels greater than 5% was 85 of 105 (81%) for interpreter 1 and 82 of 105 (78.1%) for interpreter 2. The number of adenomas with a percentage of negative pixels greater than 10% was 73 (69.5%) for interpreter 1 and 76 (72.4%) for interpreter 2. The overall range for percentage of negative pixels for both interpreters was 0-90 with a mean of 24 ± 0.2. The numbers of masses with negative pixels within various mean attenuation ranges are listed in Table 1. Sensitivities for interpreters 1 and 2 using 1 negative pixel, 5% negative pixels, and 10% negative pixel threshold values to diagnose an adenoma on unenhanced scans are found in Table 2.

Adrenal Adenomas on Enhanced CT
The mean attenuation of the 62 enhanced adenomas was 64.9 ± 26.1 for interpreter 1 and 63.1 ± 30.8 for interpreter 2. The range of attenuation values was 26 to 199 and 19 to 176, respectively. None had mean attenuation less than or equal to 10 H, but 24 (38.7%) and 28 (45.2%) had negative pixels. The number of adenomas with more than 5% negative pixels was 14 (22.6%) for interpreter 1 and 16 (25.8%) for interpreter 2. The number with more than 10% negative pixels was 7 (11.3%) for each interpreter. The range of the percentage of negative pixels was zero to 30 and zero to 29 with a mean of 4 ± 0.07 for each interpreter. Overall, 24 of 62 (38.7%) and 29 of 62 (46.8%) adenomas with attenuation measurements greater than 10 H had negative pixels. The sensitivities for interpreters 1 and 2 using one negative-pixel, 5% negative-pixel, and 10% negative-pixel threshold values to diagnose an adenoma on enhanced CT scans are found in Table 2.

Nonadenomas on Unenhanced CT
Negative pixels were present in 21 (interpreter 1) and 20 (interpreter 2) of 34 unenhanced metastases, three and 12 of 44 enhanced metastases, 21 and 28 of 35 unenhanced pheochromocytomas, four and 14 of 34 enhanced pheochromocytomas, five and six of seven unenhanced carcinomas and three and five of nine enhanced carcinomas, respectively. The mean attenuation values can be found in Tables 3, 4, 5. None of the unenhanced and enhanced metastases, pheochromocytomas, or carcinomas had attenuation values less than or equal to 10 H. The specificities for each interpreter associated with choosing a threshold for a positive study of one negative pixel, 5% negative pixels, or 10% negative pixels for unenhanced and enhanced studies are found in Table 2.

Observer Agreement
Interobserver agreement was evaluated by calculating the percentage of agreement between the two interpreters for each observation, that is, identifying adenomas (with and without IV contrast) and nonadenomas (with and without IV contrast) at thresholds of one negative pixel and 5% negative pixels. Kappa statistics and percentages of agreement are found in Table 6.

Discussion

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Although unenhanced CT densitometry and delayed contrast-enhanced CT are accurate methods to diagnose adenoma, most adrenal masses are identified incidentally after a standard contrast-enhanced abdominal CT has been performed. Without unenhanced or delayed-enhanced images available, a repeat study is necessary to attempt to diagnose an adenoma. Bae et al. [1] described a histogram analysis method with the goal of improving sensitivity in distinguishing between adenomas and metastases on standard contrast-enhanced CT studies. The histogram analysis method uses an ROI within the adrenal mass and determines if pixels measuring less than 0 H are present. Bae et al. [1] found that only 10.9% (20/184) of adenomas had a mean attenuation of 10 H or less on contrast-enhanced examinations but that 52.7% (97/184) of them could be diagnosed by the presence of negative pixels using the histogram method. In our series, none of the 62 enhanced adenomas had a mean attenuation of 10 H or less, but between 38.7% and 45.2% (24/28) had negative pixels.

Unlike Bae et al. [1], however, our series did have a number of nonadenomas that contained negative pixels. We found that there were metastases, pheochromocytomas, and adrenocortical carcinomas that contained negative pixels. In our series, this diminished the specificity of the histogram technique on enhanced scans to between 64.4% and 88.5%. This drop in specificity was even greater on unenhanced CT scans where using one negative pixel as a diagnostic threshold led to specificities between 28.9% and 38.2%. Comparing adenomas and metastases only improved specificity to 93.2-95.5% on enhanced scans and 38.2-41.2% on unenhanced scans.

Despite having no metastases with negative pixels in their series, Bae et al. [1] recommended using a threshold of 10% negative pixels to diagnose adenomas because the lowest percentage of negative pixels in their adenoma group that measured less than 10 H on enhanced examinations was 9.8%. None of our histopathologically diagnosed adenomas measured less than 10 H on enhanced studies. Adenomas had negative pixel values that ranged from 0-30%. In our series, using a 10% negative pixel threshold maintained high specificity of 98.9%, but sensitivity dropped to unacceptably low levels of between 11.3-12.9% on enhanced studies. These levels are similar to what the Bae et al. [1] series found when assessing CT densitometry on enhanced scans.

The mean attenuation value for unenhanced adenomas in this series is higher than many published previously. An analysis of prior studies reported a sensitivity of 71% for a 10-H threshold value [6]. The percentage of adenomas with attenuation of 10 H or less in this series was only approximately 30%. This is likely related to a high percentage of lipid-poor adenomas in our study population. An alternative explanation is that some unknown difference exists in our study population of pathologically proven adenomas from those in other series that were mainly proved by lack of interval growth or characteristic appearance. Many of the adenomas in this series were resected simultaneously with renal cell carcinomas.

Lesions with both unenhanced and enhanced CT images had an increase in mean attenuation and a decrease in the percentage of negative pixels on enhanced images compared with unenhanced. This was seen in the Bae et al. [1] series and was attributed to the pseudoenhancement effect that has been described for renal cysts [7-9].

Bae et al. [1] enumerated factors that may affect image quality and noise that were, similarly, not standardized in this study. These include patient body habitus, breathing motion artifact, size and location of ROI, kilovolt peak and milliampere second values, slice collimation, section thickness, reconstruction kernel, IV contrast media injection rate, and scan delay. Other factors that could impact image noise include differences in CT scanner technology—both single-detector and MDCT scanners were used in this series. For MDCT systems, more patient length is scanned per rotation; thus, for extended-length studies, the X-ray tube current can be higher than for single-section units. The higher current reduces image noise and improves image quality, which is critical for thin-section extended-length studies, especially of large patients [10]. This could reduce the number of spuriously negative pixels. However, thinner slice thickness may lead to nosier images. A recent phantom study (Tongdee R, et al., Comparison of CT histogram analysis and mean attenuation methods in characterization of adrenal masses: a phantom study, presented at the 2004 annual meeting of the Radiological Society of North America) by Bae's group evaluated the effects of changes in image thickness and the image reconstruction kernel on mean attenuation and the percentage of negative pixels. They found that the percentage of negative pixels was highly correlated to an increase in the SD of the mean attenuation values. However, the percentage of negative pixels and SDs increased together only as the reconstruction kernel changed from smooth to sharp and the slice thickness decreased. This suggests that thin slices or sharp kernels may be inappropriate for histogram analysis because of excessive image noise.

We chose to include adrenal abnormalities other than adenomas and metastases in our series. Although the clinical goal in patients with a primary malignancy and an adrenal mass is to distinguish between a metastasis and an incidentaloma, most typically an adenoma, other abnormalities such as pheochromocytomas [3] and adrenocortical carcinomas can also be discovered incidentally. A comprehensive analysis of histogram performance should include these other adrenal lesions. Although no myelolipomas were included in this series, they often have specific imaging features of macroscopic fat [2]. Because of the large amount of mature fat, most myelolipomas are easily recognized on CT and would either be excluded from this type of analysis or cause them to be mistaken for adenomas. Either situation is clinically acceptable. Similarly, the inclusion of adrenocortical carcinoma and pheochromocytomas in the series includes lesions that can be centrally necrotic. Although the presence of necrosis was not specifically recorded, areas of necrosis or cystic change were intentionally avoided in the ROI measurement in this series. Much like the performance of mean attenuation measurements to diagnose adenomas or adrenal enhancement washout [2], atypical imaging features should clinically supersede histogram analysis in arriving at a diagnosis. Findings such as large size, central necrosis, or calcification should raise suspicion for carcinoma [2] or large degenerated adenoma [11] based on mass morphology alone and obviate the need for histogram analysis.

One strength of our study is that we relied on histopathologic proof to determine the diagnosis of each of the adrenal masses. This diminishes uncertainty and potential misdiagnoses that can occur when criteria such as lack of interval change on imaging studies or another imaging test such as MRI are used as indicating the true diagnoses of the adrenal masses.

Two interpreters independently measured ROIs on all patients in each group. Interobserver agreement was measured at one negative pixel and 5% negative pixel thresholds (Table 6). Percent agreement ranged from 70-92%, with three values in the 70-79% range, three values in the 80-89% range, and one value greater than 90%. One might have predicted higher agreement than the interpreters achieved. Factors that may have influenced interpreter agreement include ROI placement, ROI size, and image choice for ROI measurement. The interpreters were instructed to choose approximately two thirds of the mass and to exclude borders with retroperitoneal fat and areas of heterogeneously low attenuation or calcifications from their measurements. However, they may have had different placement of the ROI despite the same instructions. Thus, retroperitoneal fat or areas of necrosis may have been unintentionally included. Although Bae et al. [1] excluded masses with areas of cystic change, calcification, or necrosis, other studies [12, 13] using ROI measurements to differentiate different adrenal masses excluded these areas from the ROI. Excluding these masses from the analysis could potentially have diminished interpreter errors, improving agreement, but would have diminished applicability of the test. Second, although instructions specified that the largest axial size of the mass should be selected from which to measure the ROI, the interpreters could have chosen different axial images, adding to variability. Lastly, interpreters may have chosen different sized ROIs that could have added variability, especially with larger masses.

In several circumstances in this study, the overall agreement was high (such as 89% for nonadenomas 5% negative pixels with contrast), but the kappa value was slight (0.15). The kappa value is a measure of agreement corrected for chance. This paradoxical result is caused by the high prevalence of negative cases. Prevalence effects can lead to situations in which the values of k do not correspond with intuition [14].

The issue then becomes the actual percent-agreement values themselves. Exactly what constitutes an acceptable level of agreement between interpreters for any test is subjective and may vary depending on the setting, technique, or clinical application. We could only find one study using ROIs to differentiate adrenal masses that evaluated interpreter concordance [15]. Three interpreters' ROI measurements were used to create receiver operating characteristic curves. Although these were determined to be "virtually identical," kappa values were not reported. Therefore, it is hard to judge what level of agreement one should expect for this technique. Should the level of agreement between our two interpreters call into question the reproducibility of the test? Further studies are needed.

There are several limitations of our study. There is the potential for verification bias in our study. This occurs when the study results are only reported for subjects with verified disease status. However, the most typical scenario in which the results of the diagnostic test under study affect whether the gold standard procedure is used to verify the test result is not the case. Second, the study was retrospectively performed and, therefore, imaging parameters were not controlled within the population.

In conclusion, our study shows that using a 10% negative pixel threshold to discriminate adenomas from nonadenomas on enhanced scans has a high specificity of 98.9% but suffers from poor sensitivity. Further modifications of this technique may be necessary before it is clinically useful.

References

Top Abstract Introduction Materials and Methods Results Discussion References

 

1. Bae KT, Fuangtharnthip P, Prasad SR. Joe BN, Heiken JP. Adrenal masses: CT characterization with histogram analysis method. Radiology 2003;228 : 735-742[Abstract/Free Full Text]
2. Dunnick NR, Korobkin M. Imaging of adrenal incidentalomas: current status. AJR 2002;179 : 559-568[Free Full Text]
3. Motta-Ramirez GA, Remer EM, Herts BR, Gill IS, Hamrahian AH. Comparison on CT findings in symptomatic and incidentally discovered pheochromocytomas. AJR 2005;185 : 684-688[Abstract/Free Full Text]
4. Hamrahian AH, Ioachimescu AG, Remer EM, et al. Clinical utility of noncontrast CT attenuation value (HU) to differentiate adrenal adenomas/hyperplasias from nonadenomas: Cleveland Clinic experience. J Clin Endocrinol Metab 2005;90 : 871-877[Abstract/Free Full Text]
5. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33 : 159-174[CrossRef][Medline]
6. Boland GW, Lee MJ, Gazelle GS, Halpern EF, McNicholas MM, Mueller PR. Characterization of adrenal masses using unenhanced CT: an analysis of the CT literature. AJR 1998;171 : 201-204[Abstract/Free Full Text]
7. Maki DD, Birnbaum BA, Chakraborty DP, Jacobs JE, Carvalho BM, Herman GT. Renal cyst pseudoenhancement: beam-hardening effects on CT numbers. Radiology 1999;213 : 468-472[Abstract/Free Full Text]
8. Coulam CH, Sheafor DH, Leder RA, Paulson EK, DeLong DM, Nelson RC. Evaluation of pseudoenhancement of renal cysts during contrast-enhanced CT. AJR 2000; 174:493 -498[Abstract/Free Full Text]
9. Bae KT, Heiken JP, Siegel CL, Bennett HF. Renal cysts: is attenuation artifactually increased on contrast-enhanced CT images? Radiology 2000;216 : 792-796[Abstract/Free Full Text]
10. Rydberg J, Buckwalter KA, Caldemeyer KS, et al. Multisection CT: scanning techniques and clinical applications. RadioGraphics 2000;20 : 1787-1806[Abstract/Free Full Text]
11. Newhouse JH, Heffess CS, Wagner BJ, Imray TJ, Adair CF, Davidson AJ. Large degenerated adrenal adenomas: radiologic-pathologic correlation. Radiology 1999;210 : 385-391[Abstract/Free Full Text]
12. Szolar DH, Kammerhuber FH. Adrenal adenomas and nonadenomas: assessment of washout at delayed contrast-enhanced CT. Radiology 1998;207 : 369-375[Abstract/Free Full Text]
13. Caoili EM, Korobkin M, Francis IR, et al. Adrenal masses: characterization with combined unenhanced and delayed enhanced CT. Radiology 2002;222 : 629-633[Abstract/Free Full Text]
14. Kundel HL, Polansky M. Measurement of observer agreement. Radiology 2003;228 : 303-308[Abstract/Free Full Text]
15. Lee MJ, Hahn PF, Papanicolau N, et al. Benign and malignant adrenal masses: CT distinction with attenuation coefficients, size, and observer analysis. Radiology 1991;179 : 415-418[Abstract/Free Full Text]

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