Evaluation of diagnostic accuracy: multidetector CT image noise correction improves specificity of a Gaussian model-based algorithm used for characterization of incidental adrenal nodules.

OBJECTIVES: To investigate whether the histogram analysis method of characterizing adrenal nodules as adenomas is affected by increased noise with modern CT technique, and if an extension that allows for noise correction will improve diagnostic performance. MATERIALS AND METHODS: This is a HIPAA-compliant, IRB-approved retrospective study performed on 58 total patients. The first group of 29 patients had 33 adrenal lesions that were pathology-proven non-adenomas. The second group had 29 patients with 33 pathology-proven or presumed adenomas based on established imaging criteria. The nodules were evaluated using the histogram method, mean attenuation method, and a Gaussian model-based algorithm without (uncorrected Gaussian algorithm) and with correction (corrected Gaussian algorithm) for image noise. Sensitivity, specificity, and accuracy for identifying adenoma were derived. RESULTS: There were no significant differences in identifying adenoma from non-adenoma when using the histogram analysis method and the uncorrected Gaussian algorithm, both of which had low specificities of 42.4% and 47.0%, respectively (p = 0.30). Adding noise correction to the Gaussian algorithm resulted in a statistically significant increase in specificity relative to the histogram method (86.4% vs. 42.4%, p < 0.001). The corrected Gaussian algorithm improved sensitivity compared to the mean attenuation method (71.2% vs. 54.5%, p < 0.001), but had lower specificity (86.4% vs. 100%, p < 0.001), and similar overall accuracy (78.8% vs. 77.3%, p = 0.74). CONCLUSION: With modern low-dose CT technique, the specificity scores of the histogram method for discrimination of adrenal adenomas and non-adenomas are lower than with previous higher dose scans. The specificity and accuracy of a histogram-equivalent method can be increased mathematically through image noise correction, and the corrected Gaussian algorithm has improved sensitivity to the mean attenuation with similar accuracy albeit with lower specificity. Although this suggests limited utility for histogram analysis in adrenal nodule characterization, our study demonstrates the potential mathematical application for other noise-dependent CT characterization methods.

CT Detectability of Small Low-Contrast Hypoattenuating Focal Lesions: Iterative Reconstructions versus Filtered Back Projection.

Purpose To investigate performance in detectability of small (≤1 cm) low-contrast hypoattenuating focal lesions by using filtered back projection (FBP) and iterative reconstruction (IR) algorithms from two major CT vendors across a range of 11 radiation exposures. Materials and Methods A low-contrast detectability phantom consisting of 21 low-contrast hypoattenuating focal objects (seven sizes between 2.4 and 10.0 mm, three contrast levels) embedded into a liver-equivalent background was scanned at 11 radiation exposures (volume CT dose index range, 0.5-18.0 mGy; size-specific dose estimate [SSDE] range, 0.8-30.6 mGy) with four high-end CT platforms. Data sets were reconstructed by using FBP and varied strengths of image-based, model-based, and hybrid IRs. Sixteen observers evaluated all data sets for lesion detectability by using a two-alternative-forced-choice (2AFC) paradigm. Diagnostic performances were evaluated by calculating area under the receiver operating characteristic curve (AUC) and by performing noninferiority analyses. Results At benchmark exposure, FBP yielded a mean AUC of 0.79 ± 0.09 (standard deviation) across all platforms which, on average, was approximately 2% lower than that observed with the different IR algorithms, which showed an average AUC of 0.81 ± 0.09 (P = .12). Radiation decreases of 30%, 50%, and 80% resulted in similar declines of observer detectability with FBP (mean AUC decrease, -0.02 ± 0.05, -0.03 ± 0.05, and -0.05 ± 0.05, respectively) and all IR methods investigated (mean AUC decrease, -0.00 ± 0.05, -0.04 ± 0.05, and -0.04 ± 0.05, respectively). For each radiation level and CT platform, variance in performance across observers was greater than that across reconstruction algorithms (P = .03). Conclusion Iterative reconstruction algorithms have limited radiation optimization potential in detectability of small low-contrast hypoattenuating focal lesions. This task may be further complicated by a high degree of variation in radiologists' performances, seemingly exceeding real performance differences among reconstruction algorithms. © RSNA, 2018 Online supplemental material is available for this article.

Use of Computed Tomography to Determine Perforation in Patients With Acute Appendicitis.

PURPOSE: Urgent appendectomy has long been the standard of care for acute appendicitis. Six randomized trials have demonstrated that antibiotics can safely treat appendicitis, but approximately 1 in 4 of these patients eventually requires appendectomy. Overall treatment success may be limited by complex disease including perforation. Patients׳ success on antibiotic therapy may depend on preoperative identification of complex disease on imaging. However, the effectiveness of computed tomography (CT) in differentiating complex disease including perforated from nonperforated appendicitis remains to be determined. The purpose of this study was to assess the preoperative diagnostic accuracy of CT in determining appendiceal perforation in patients operated for acute appendicitis. METHODS: We performed a retrospective review of pathology and radiology reports from consecutive patients who presented to the emergency department with suspicion for acute appendicitis between January 2012 and May 2015. CT scans were re-reviewed by abdominal imaging fellowship-trained radiologists using standardized criteria, and the radiologists were blinded to pathology and surgical findings. Radiologists specifically noted presence or absence of periappendiceal gas, abscess, appendicolith, fat stranding, and bowel wall thickening. The overall radiologic impression as well as these specific imaging findings was compared to results of pathology and operative reports. Pathology reports were considered the standard for diagnostic accuracy. RESULTS: Eighty-nine patients (65% male, average age of 34 years) presenting with right lower quadrant pain underwent CT imaging and prompt appendectomy. Final pathology reported perforation in 48% (n = 43) of cases. Radiologic diagnosis of perforation was reported in 9% (n = 8), correctly identifying perforation in 37.5% (n = 3), and incorrectly reporting perforation in 62.5% of nonperforated cases per pathology. Radiology missed 93% (n = 40) of perforations postoperatively diagnosed by pathology. There was no secondary finding (fat stranding, diameter >13mm, abscess, cecal wall thickening, periappendiceal gas, simple fluid collection, appendicolith, and phlegmon) with a clinically reliable sensitivity or specificity to predict perforated appendicitis. Surgeon׳s report of perforation was consistent with the pathology report of perforation in only 28% of cases. CONCLUSIONS: The usefulness of a CT for determining perforation in acute appendicitis is limited, and methods to improve precision in identifying patients with complicated appendicitis should be explored as this may help for improving risk prediction for failure of treatment with antibiotic therapy and help guide patients and providers in shared decision-making for treatment options.

Three-dimensional reconstruction volume: a novel method for volume measurement in kidney cancer.

BACKGROUND AND PURPOSE: The role of volumetric estimation is becoming increasingly important in the staging, management, and prognostication of benign and cancerous conditions of the kidney. We evaluated the use of three-dimensional reconstruction volume (3DV) in determining renal parenchymal volumes (RPV) and renal tumor volumes (RTV). We compared 3DV with the currently available methods of volume assessment and determined its interuser reliability. PATIENTS AND METHODS: RPV and RTV were assessed in 28 patients who underwent robot-assisted laparoscopic partial nephrectomy for kidney cancer. Patients with a preoperative creatinine level of <1.2 mg/dL with available scans were selected. RPV and RTV were then assessed using 3DV, as well as cylindrical approximation for RPV and spherical approximation for RTV as described previously in the literature. Measures of the same quantity from each method were then compared. In addition, interuser reliability was determined for 3DV. RESULTS: Calculated volumes differed widely in comparison with 3DV. For example, cylindrical volumes for the contralateral kidney pre- and postsurgery overestimated 3D reconstruction volumes by 15% to 102% and 12% to 101%, respectively. In addition, volumes obtained from 3DV displayed high interuser reliability regardless of experience. CONCLUSIONS: 3DV provides a highly reliable way of assessing kidney volumes. Given that 3DV takes into account visible anatomy, the differences observed using previously published methods can be attributed to the failure of geometry to accurately approximate kidney or tumor shape. 3DV provides a more accurate, reproducible, and clinically useful tool for urologists looking to improve patient care using analysis related to volume.