Technical and Interpretive Pitfalls in Adrenal                     Imaging

Nandra, Gurinder; Duxbury, Oliver; Patel, Pawan; Patel, Jaymin H.; Patel, Nirav; Vlahos, Ioannis

doi:10.1148/rg.2020190080

Cited by 32 publications

(17 citation statements)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[17][18][19][20] Contrast materials can improve the visibility of adrenal structures imaged by CT and MRI scans and might have a positive effect on diagnosis accuracy. 21 Thus, imaging methods and contrast materials were thought to be confounders for subgroup analyses. Moreover, a large sample size may represent experienced interventional radiologists and support the credibility of the included studies.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic accuracy of adrenal imaging for subtype diagnosis in primary aldosteronism: systematic review and meta-analysis

et al. 2020

View full text Add to dashboard Cite

ObjectivesAccurate subtype classification in primary aldosteronism (PA) is critical in assessing the optimal treatment options. This study aimed to evaluate the diagnostic accuracy of adrenal imaging for unilateral PA classification.MethodsSystematic searches of PubMed, EMBASE and the Cochrane databases were performed from 1 January 2000 to 1 February 2020, for all studies that used CT or MRI in determining unilateral PA and validated the results against invasive adrenal vein sampling (AVS). Summary diagnostic accuracies were assessed using a bivariate random-effects model. Subgroup analyses, meta-regression and sensitivity analysis were performed to explore the possible sources of heterogeneity.ResultA total of 25 studies, involving a total of 4669 subjects, were identified. The overall analysis revealed a pooled sensitivity of 68% (95% CI: 61% to 74%) and specificity of 57% (95% CI 50% to 65%) for CT/MRI in identifying unilateral PA. Sensitivity was higher in the contrast-enhanced (CT) group versus the traditional CT group (77% (95% CI 66% to 85%) vs 58% (95% CI 50% to 66%). Subgroup analysis stratified by screening test for PA showed that the sensitivity of the aldosterone-to-renin ratio (ARR) group was higher than that of the non-ARR group (78% (95% CI 69% to 84%) vs 66% (95% CI 58% to 72%)). The diagnostic accuracy of PA patients aged ≤40 years was reported in four studies, and the overall sensitivity was 71%, with 79% specificity. Meta-regression revealed a significant impact of sample size on sensitivity and of age and study quality on specificity.ConclusionCT/MRI is not a reliable alternative to invasive AVS without excellent sensitivity or specificity for correctly identifying unilateral PA. Even in young patients (≤40 years), 21% of patients would have undergone unnecessary adrenalectomy based on imaging results alone.

show abstract

Section: Discussionmentioning

confidence: 99%

Diagnostic accuracy of adrenal imaging for subtype diagnosis in primary aldosteronism: systematic review and meta-analysis

et al. 2020

View full text Add to dashboard Cite

show abstract

“…As DLR simulates the complete CT system, contrary to FBP and hybrid IR techniques, one might assume that CT reconstructions made by DLR may result in different CT values for certain tissues than with the use of FBP or hybrid IR. This can lead to serious complications when CT values reconstructed by DLR differ much from FBP or hybrid IR, that established cut-off-values in certain diagnostic methods will not hold anymore for DLR reconstructed CT images resulting in missing diagnoses [7]. Hence, in this systematic review and meta-analysis, we sought to evaluate differences between DLR reconstructed CT values and FBP or hybrid IR reconstructed CT values.…”

Section: Introductionmentioning

confidence: 99%

The effect of deep learning reconstruction on abdominal CT densitometry and image quality: a systematic review and meta-analysis

et al. 2021

View full text Add to dashboard Cite

Objective To determine the difference in CT values and image quality of abdominal CT images reconstructed by filtered back-projection (FBP), hybrid iterative reconstruction (IR), and deep learning reconstruction (DLR). Methods PubMed and Embase were systematically searched for articles regarding CT densitometry in the abdomen and the image reconstruction techniques FBP, hybrid IR, and DLR. Mean differences in CT values between reconstruction techniques were analyzed. A comparison between signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of FBP, hybrid IR, and DLR was made. A comparison of diagnostic confidence between hybrid IR and DLR was made. Results Sixteen articles were included, six being suitable for meta-analysis. In the liver, the mean difference between hybrid IR and DLR was − 0.633 HU (p = 0.483, SD ± 0.902 HU). In the spleen, the mean difference between hybrid IR and DLR was − 0.099 HU (p = 0.925, SD ± 1.061 HU). In the pancreas, the mean difference between hybrid IR and DLR was − 1.372 HU (p = 0.353, SD ± 1.476 HU). In 14 articles, CNR was described. In all cases, DLR showed a significantly higher CNR. In 9 articles, SNR was described. In all cases but one, DLR showed a significantly higher SNR. In all cases, DLR showed a significantly higher diagnostic confidence. Conclusions There were no significant differences in CT values reconstructed by FBP, hybrid IR, and DLR in abdominal organs. This shows that these reconstruction techniques are consistent in reconstructing CT values. DLR images showed a significantly higher SNR and CNR, compared to FBP and hybrid IR. Key Points CT values of abdominal CT images are similar between deep learning reconstruction (DLR), filtered back-projection (FBP), and hybrid iterative reconstruction (IR). DLR results in improved image quality in terms of SNR and CNR compared to FBP and hybrid IR images. DLR can thus be safely implemented in the clinical setting resulting in improved image quality without affecting CT values.

show abstract

“…However, on CT, despite a high degree of enhancement, 35% of pheochromocytomas had an APW and RPW similar to lipid-poor AA [29,31]. Pheochromocytomas demonstrating washout often have a peak enhancement greater than 110 HU [21]. Calcifications are present in 20% of pheochromocytomas [32].…”

Section: Metanephrine-secreting Adrenal Lesionsmentioning

confidence: 99%

“…Thirty percent of AAs do not display the typical intracellular microscopical fatty content (i.e., the so-called "lipid-poor AAs"), and thus require image acquisition at 60 s and 10 min or 15 min after the start of intravenous administration of iodinated contrast material to further allow calculation of the absolute percentage washout (APW) and relative percentage washout (RPW) [21]. The 10-min delayed acquisition yields a lower accuracy than 15 min and may require confirmation with a 15 min acquisition if negative [21]. A cutoff of 60% for APW yielded 88% sensitivity and 89% specificity of differentiating between lipid-poor AA and non-adenoma lesions, and a cut-off of 40% for RPW yielded 100% sensitivity and 100% specificity [22,23].…”

Section: Typical Incidental Adrenal Lesions On Imagingmentioning

confidence: 99%

Adrenal Mass Characterization in the Era of Quantitative Imaging: State of the Art

Barat

Gaujoux

Tenenbaum

et al. 2022

Cancers

View full text Add to dashboard Cite

Detection and characterization of adrenal lesions have evolved during the past two decades. Although the role of imaging in adrenal lesions associated with hormonal secretion is usually straightforward, characterization of non-functioning adrenal lesions may be challenging to confidently identify those that need to be resected. Although many adrenal lesions can be readily diagnosed when they display typical imaging features, the diagnosis may be challenging for atypical lesions. Computed tomography (CT) remains the cornerstone of adrenal imaging, but other morphological or functional modalities can be used in combination to reach a diagnosis and avoid useless biopsy or surgery. Early- and delayed-phase contrast-enhanced CT images are essential for diagnosing lipid-poor adenoma. Ongoing studies are evaluating the capabilities of dual-energy CT to provide valid virtual non-contrast attenuation and iodine density measurements from contrast-enhanced examinations. Adrenal lesions with attenuation values between 10 and 30 Hounsfield units (HU) on unenhanced CT can be characterized by MRI when iodinated contrast material injection cannot be performed. 18F-FDG PET/CT helps differentiate between atypical benign and malignant adrenal lesions, with the adrenal-to-liver maximum standardized uptake value ratio being the most discriminative variable. Recent studies evaluating the capabilities of radiomics and artificial intelligence have shown encouraging results.

show abstract

Technical and Interpretive Pitfalls in Adrenal Imaging

Abstract: Identify and avoid technical pitfalls encountered at adrenal imaging. Describe and avoid interpretive pitfalls, including mimics of adrenal pathologic conditions.Recognize imaging features that may suggest an endocrine disturbance or specific endocrine conditions.

Cited by 32 publications

References 81 publications

Diagnostic accuracy of adrenal imaging for subtype diagnosis in primary aldosteronism: systematic review and meta-analysis

Diagnostic accuracy of adrenal imaging for subtype diagnosis in primary aldosteronism: systematic review and meta-analysis

The effect of deep learning reconstruction on abdominal CT densitometry and image quality: a systematic review and meta-analysis

Adrenal Mass Characterization in the Era of Quantitative Imaging: State of the Art

Contact Info

Product

Resources

About