Combining Washout and Noncontrast Data From Adrenal Protocol CT

Rationale and Objectives

To determine if combination of washout and noncontrast data from delayed adrenal computed tomography (CT) improves diagnostic performance, and demonstration of an optimizing analytical framework.

Materials and Methods

This retrospective study consisted of 97 adrenal lesions, in 96 patients, with pathologically proven adrenal lesions (75 benign; 22 malignant), who had undergone noncontrast, portal- and approximate 15-minute delayed-phase CT. Lesion CT attenuations (Hounsfield units [HU]) during each phase, and “absolute” and “relative” percent enhancement washouts (APEW and RPEW) were assessed. The optimum combination of sequential parameters and thresholds was determined by recursive partitioning analysis; resultant diagnostic performance was compared to commonly applied single-parameter criteria for malignancy (noncontrast > 10 HU, APEW < 60%, RPEW < 40%).

Results

The above single-parameter criteria yielded sensitivities, specificities, and accuracies for malignancy of 100.0%, 41.3%, and 54.6%; 97.9%, 61.3%, and 69.1%; and 96.6%, 74.7%, and 78.4%, respectively. Recursive partitioning analysis identified noncontrast ≥24.75 HU, with subsequent APEW ≤63.49%, as the optimum sequential parameter-threshold combination, which yielded increased sensitivity, specificity, and accuracy of 100.0%, 85.3%, and 90.7%, respectively. Discrimination using the combined sequential classifier yielded statistically significant improvements in accuracy when compared to the above conventional single-parameter criteria (all P ≤ .039).

Conclusion

Sequential application of noncontrast and washout criteria from delayed contrast-enhanced adrenal CT can improve diagnostic performance beyond that of commonly applied single-parameter criteria. Validation of the sequential ordering and refinement of the specific threshold values warrant further study.

Introduction

Adrenal lesions are encountered in a variety of clinical settings, ranging from purely incidental, where the estimated incidence is as high as 9% of abdominal computed tomographies (CTs) , to cancer staging, where the incidence can be expected to be even higher. Whatever the clinical setting, their detection typically presents radiologists and clinicians with the challenge of differentiating whether they might be malignant and benign.

A variety of clinical and imaging-based algorithms have been developed to assist in the management of such lesions, for example, by Berland et al. . A fundamental component of this and many algorithms is the utilization of delayed (10–15 minutes post contrast) washout adrenal protocol CT, and the application of cutoff thresholds to categorize malignancy and benignity. Commonly applied thresholds are 60% for “absolute percent enhancement washout” (APEW), and 40% for “relative percent enhancement washout” (RPEW) . Many algorithms incorporate a preceding decision-node based on noncontrast (NC) CT attenuation of the lesion (typically with a threshold of 10 Hounsfield units [HU]). Application of such consecutive CT evaluations with associated cutoff criteria has been shown to yield very high diagnostic performances . Some work has suggested that application of combined sequential thresholds to the adrenal protocol itself may yield high sensitivities and specificities . However, as suggested by a recent careful meta-analysis, there is considerable room for more careful studies and improvements in diagnostic performance of imaging evaluations . To the best of our knowledge, application of optimization methodologies to improve diagnostic performance using the data available in the adrenal protocol CT itself has not been explored.

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Materials and Methods

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CT Scan

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CT Analysis

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Absolute PEW(APEW)=[(PV−DL)/(PV−NC)]∗100 Absolute PEW

(

APEW

)

[

(

−

)

(

−

)

]

∗

100

Relative PEW(RPEW)=[(PV−DL)/(PV)]∗100 Relative PEW

(

RPEW

)

[

(

−

)

(

)

]

∗

100

where NC, PV, and DL are the mean attenuations on NC, portal-venous, and delayed-phase contrast-enhanced CT, respectively .

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Statistical Analysis

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Results

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Diagnostic Performance Using Commonly applied Thresholds

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TABLE 1

Sensitivity, Specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV) and Accuracy for Malignancy, at “Commonly-applied” and “Optimum” Cutoff Thresholds

Method Parameter First Cutoff Threshold Second Cutoff Threshold Sens (%) Spec (%) PPV (%) NPV (%) Accuracy (%) Accuracy 95% CI “Commonly-applied” Single NC > 10 HU N/A 100.0 41.3 33.3 100.0 54.6 44.2–64.8 Single APEW < 60 % N/A 97.9 61.3 42.0 95.5 69.1 58.9–78.1 Single RPEW < 40 % N/A 96.6 74.7 51.3 90.9 78.4 68.8–86.1 Combined NC > 10 HU APEW ≤ 60 % 95.5 74.7 52.5 98.2 79.4 70.0–86.9 Combined NC > 10 HU RPEW ≤ 40 % 90.1 77.3 54.1 96.7 80.4 71.1–87.8 “Optimum” Single NC ≥ 24.75 HU N/A 100.0 72.0 51.2 100.0 78.4 68.8–86.1 Single APEW ≤ 59.25 % N/A 90.9 66.7 44.4 96.2 72.2 62.1–80.8 Single RPEW ≤ 43.38 % N/A 95.5 73.3 51.2 98.2 78.4 68.8–86.1 Combined \* NC ≥ 24.75 HU APEW ≤ 63.49 % 100.0 88.0 71.0 100.0 90.7 83.1–95.7 Combined NC ≥ 24.75 HU RPEW ≤ 46.63 % 100.0 85.3 66.7 100.0 88.7 80.6–94.2

95% CI, 95% confidence interval.

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Diagnostic Performance Using “Optimized” Thresholds

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Discussion

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Conclusions

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Funding

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References

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Combining Washout and Noncontrast Data From Adrenal Protocol CT

Rationale and Objectives

Materials and Methods

Results

Conclusion

Introduction

Materials and Methods

CT Scan

CT Analysis

Statistical Analysis

Results

Diagnostic Performance Using Commonly applied Thresholds

Diagnostic Performance Using “Optimized” Thresholds

Discussion

Conclusions

Funding

References

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