Can Patient Triaging with Clinical Scoring Systems Reduce CT Use in Adolescents and Young Adults Suspected of Having Appendicitis?

Background There are ongoing efforts to reduce CT radiation exposure for the diagnosis of appendicitis. Recent guidelines recommend using clinical scoring systems to triage patients who need imaging examinations. Purpose To determine whether patient triaging with scoring systems can reduce CT use without a loss of diagnostic accuracy in adolescents and young adults suspected of having appendicitis. Materials and Methods This retrospective study used data from a previous multicenter randomized controlled trial conducted between December 2013 and August 2016. Five scoring systems (adult appendicitis, appendicitis inflammatory response, modified Alvarado, Broek, and Christian scores) were used to categorize patients into low-, intermediate-, or high-probability groups. CT use was simulated for only the intermediate-probability group. The primary outcomes were CT reduction rate, sensitivity, and specificity. The CT reduction rate was defined as the proportion of patients in low- and high-probability groups who would not have to undergo CT among all patients. Sensitivity and specificity were calculated in the overall diagnostic pathway using each scoring system and subsequent CT. As a secondary analysis, to maintain the diagnostic accuracy to a level of when CT was used for all patients with suspected appendicitis, new cutoff values for probability group stratification targeting 97.6% sensitivity and 94.9% specificity were applied for each of the scoring systems. Results A total of 2888 patients (mean age ± standard deviation, 28 years ± 9; 1580 women and 1308 men) with suspected appendicitis were evaluated, of whom 1088 had and 1800 did not have appendicitis. The CT reduction rates of the five scoring systems ranged from 55.6% (1606 of 2888 patients) to 71.1% (2053 of 2888), but at the cost of sensitivity (range, 48.7% [530 of 1088] to 81.2% [883 of 1088]) and specificity (range, 79.0% [1422 of 1800] to 97.8% [1761 of 1800]). Targeting 97.6% sensitivity and 94.9% specificity, the CT reduction rates of all five scoring systems were 0% (0 of 2888). Conclusion Using clinical scoring systems in triaging patients for selective CT use led to a considerable loss of diagnostic accuracy. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Mellnick in this issue.

Differentiation between complicated and uncomplicated appendicitis: diagnostic model development and validation study.

PURPOSE: Differentiating complicated appendicitis has become important, as multiple trials showed that non-operative management of uncomplicated appendicitis is feasible. We developed and validated a diagnostic model to differentiate complicated from uncomplicated appendicitis. METHODS: This retrospective study included 1153 patients (mean age ± standard deviation, 30 ± 8 years) with appendicitis on CT (804 patients for development, and 349 for validation). Complicated appendicitis was confirmed in 300 and 121 patients in the development and validation datasets, respectively. The reference standard was surgical or pathological report except in 7 patients who underwent percutaneous abscess drainage. We developed a model using multivariable logistic regression and Bayesian information criterion. We assessed calibration and discriminatory performance of the model in the validation dataset via calibration plot and the area under the curve (AUC), respectively. We measured sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and proportion of false- and true-negatives of the model in the validation dataset, targeting 95% sensitivity. RESULTS: Five CT features (contrast-enhancement defect of the appendiceal wall, abscess, moderate or severe periappendiceal fat stranding, appendiceal diameter, and extraluminal air) and percentage of segmented neutrophil were included in our model. The calibration slope was 1.03, and AUC was 0.81 (95% CI 0.77-0.85) in the validation dataset. The sensitivity, specificity, PPV, NPV, and proportion of false- and true-negatives were 93.4% (91.8-99.1), 28.1% (13.6-24.1), 40.8% (35.0-46.8), 88.9% (79.3-95.1), 2.3%, and 18.3%, respectively. CONCLUSION: Our model may identify patients with unequivocally uncomplicated appendicitis, who may benefit from non-operative management with low risk of failure.

Diagnostic Yield and False-Referral Rate of Staging Chest CT in Patients with Colon Cancer.

Purpose To measure the diagnostic yield and false-referral rate (FRR) of staging contrast material-enhanced chest CT based on the clinical stage from contrast-enhanced abdominal CT in patients with colon cancer. Materials and Methods This retrospective study included 1743 patients (mean age, 63.4 years; range, 18-96 years) with a diagnosis of colon cancer. The primary outcomes were diagnostic yield and FRR of contrast-enhanced chest CT in the detection of thoracic metastasis. The proportions of patients with occult thoracic metastasis and those undergoing pulmonary metastasectomy for true-positive metastases were key secondary outcomes. The outcomes were stratified according to clinical stage at contrast-enhanced abdominal CT. Results The diagnostic yields in clinical stage 0/I, cII, cIII, and cIV were 0% (95% confidence interval [CI]: 0%, 0.8%), 1.3% (95% CI: 0.4%, 3.3%), 4.4% (95% CI: 3.0%, 6.1%), and 43.3% (95% CI: 36.8%, 49.9%), respectively. The corresponding FRRs were 5.7% (95% CI: 3.8%, 8.2%), 2.9% (95% CI: 1.3%, 5.5%), 6.7% (95% CI: 5.0%, 8.8%), and 6.1% (95% CI: 3.4%, 10.0%), respectively. The proportions of patients with occult metastasis were 0% (95% CI: 0%, 0.8%), 3.3% (95% CI: 1.6%, 5.9%), 1.5% (95% CI: 0.8%, 2.7%), and 6.1% (95% CI: 3.4%, 10.0%), respectively. The proportion of patients who underwent pulmonary metastasectomy was 0% (none of 474; 95% CI: 0%, 0.8%) for clinical stage 0/I tumors. Conclusion In clinical stages 0 and I, the diagnostic yield of staging contrast-enhanced chest CT in detecting thoracic metastasis was zero. For clinical stages II, III, and IV, contrast-enhanced chest CT as a baseline examination was helpful for the detection of thoracic metastasis and allowed for the possibility of a curative metastasectomy. There was no significant association between clinical stage and false-referral rate. © RSNA, 2018 Online supplemental material is available for this article.

Low-dose (2-mSv) computed tomography for suspected appendicitis: Applicability in an emergency department.

OBJECTIVES: To document the level of interobserver agreement and compare the diagnostic performances of emergency physicians and radiologists at interpreting low radiation CT images of acute appendicitis in adolescents and young adults. METHODS: One hundred and seven adolescents and young adult patients (aged 15 to 44years) that underwent 2-mSv low-dose CT for suspected acute appendicitis between June and December in 2013 were enrolled in this retrospective study. Three emergency physicians and three radiologists with different experiences of low-dose CT independently reviewed CT images. These six physicians rated the likelihood of acute appendicitis using a 5-point Likert scale. We calculated interobserver agreement and compared the diagnostic performances between emergency physicians and radiologists. And diagnostic confidence was also assessed using the likelihood of acute appendicitis. RESULTS: Acute appendicitis was pathologically confirmed in 42 patients (39%); the remaining 65 patients were considered not to have appendicitis. Fleiss' Kappa for reliability of agreement between emergency physicians and radiologists for the diagnosis of acute appendicitis was 0.720 (95% confidence intervals (CI), 0.685-0.726). Pooled areas under the receiver operating characteristics curve (AUC) for a diagnosis of appendicitis were 0.904 and 0.944 for emergency physicians and radiologists, respectively, and these AUC values were not significantly different (95% confidence interval, -0.087, 0.007; p=0.0855). CONCLUSION: The emergency physicians and radiologists showed good interobserver agreement and comparable diagnostic performances for appendicitis in adolescents and adults using low-dose CT images. Low-dose CT could be a useful tool for the diagnosis of appendicitis by emergency physicians.

Can We Perform CT of the Appendix with Less Than 1 mSv? A De-escalating Dose-simulation Study.

OBJECTIVES: To systematically explore the lowest reasonably achievable radiation dose for appendiceal CT using an iterative reconstruction (IR) in young adults. METHODS: We prospectively included 30 patients who underwent 2.0-mSv CT for suspected appendicitis. From the helical projection data, 1.5-, 1.0- and 0.5-mSv CTs were generated using a low-dose simulation tool and the knowledge-based IR. We performed step-wise non-inferiority tests sequentially comparing 2.0-mSv CT with each of 1.5-, 1.0- and 0.5-mSv CT, with a predetermined non-inferiority margin of 0.06. The primary end point was the pooled area under the receiver-operating-characteristic curve (AUC) for three abdominal and three non-abdominal radiologists. RESULTS: For the abdominal radiologists, the non-inferiorities of 1.5-, 1.0- and 0.5-mSv CT to 2.0-mSv CT were sequentially accepted [pooled AUC difference: 2.0 vs. 0.5 mSv, 0.017 (95% CI: -0.016, 0.050)]. For the non-abdominal radiologists, the non-inferiorities of 1.5- and 1.0-mSv CT were accepted; however, the non-inferiority of 0.5-mSv CT could not be proved [pooled AUC difference: 2.0 vs. 1.0 mSv, -0.017 (-0.070, 0.035) and 2.0 vs. 0.5 mSv, 0.045 (-0.071, 0.161)]. CONCLUSION: The 1.0-mSv appendiceal CT was non-inferior to 2.0-mSv CT in terms of diagnostic performance for both abdominal and non-abdominal radiologists; 0.5-mSv appendiceal CT was non-inferior only for abdominal radiologists. KEY POINTS: • For both abdominal and non-abdominal radiologists, 1.0-mSv appendiceal CT could be feasible. • The 0.5-mSv CT was non-inferior to 2.0-mSv CT only for expert abdominal radiologists. • Reader experience is an important factor affecting diagnostic impairment by low-dose CT.

Systematic Review and Meta-Analysis of CT Features for Differentiating Complicated and Uncomplicated Appendicitis.

Purpose To perform a systematic review and meta-analysis to identify computed tomographic (CT) features for differentiating complicated appendicitis in patients suspected of having appendicitis and to summarize their diagnostic accuracy. Materials and Methods Studies on diagnostic accuracy of CT features for differentiating complicated appendicitis (perforated or gangrenous appendicitis) in patients suspected of having appendicitis were searched in Ovid-MEDLINE, EMBASE, and the Cochrane Library. Overlapping descriptors used in different studies to denote the same image finding were subsumed under a single CT feature. Pooled diagnostic accuracy of the CT features was calculated by using a bivariate random effects model. CT features with pooled diagnostic odds ratios with 95% confidence intervals not including 1 were considered as informative. Results Twenty-three studies were included, and 184 overlapping descriptors for various CT findings were subsumed under 14 features. Of these, 10 features were informative for complicated appendicitis. There was a general tendency for these features to show relatively high specificity but low sensitivity. Extraluminal appendicolith, abscess, appendiceal wall enhancement defect, extraluminal air, ileus, periappendiceal fluid collection, ascites, intraluminal air, and intraluminal appendicolith showed pooled specificity greater than 70% (range, 74%-100%), but sensitivity was limited (range, 14%-59%). Periappendiceal fat stranding was the only feature that showed high sensitivity (94%; 95% confidence interval: 86%, 98%) but low specificity (40%; 95% confidence interval, 23%, 60%). Conclusion Ten informative CT features for differentiating complicated appendicitis were identified in this study, nine of which showed high specificity, but low sensitivity. © RSNA, 2017 Online supplemental material is available for this article.

Evaluation of tumor angiogenesis in a mouse PC-3 prostate cancer model using dynamic contrast-enhanced sonography.

OBJECTIVES: The purpose of this study was to evaluate tumor angiogenesis in a mouse xenograft model injected with human PC-3 prostate cancer cells using contrast-enhanced sonography. METHODS: Sixteen nude mice were injected with human prostate cancer cells on the back or the flank. Contrast-enhanced sonography was performed with a 5- to 12-MHz broadband linear transducer after a 500-µL bolus injection of a sonographic contrast agent composed of lipid shells and sulfur hexafluoride. Contrast-enhanced sonograms were obtained by the pulse inversion coded harmonic technique with a low mechanical index of 0.07. A region of interest was drawn to encompass the tumor, and time-intensity curves were acquired. After fitting the curve by a gamma variate function, the maximum intensity, area under the curve for up to 50 seconds, time to peak, shape parameter, and scale parameter were derived. The tumor volume, percentage of vascular endothelial growth factor expression, and CD31-positive vessel count (microvessel density) were correlated with the parameters derived from the time-intensity curve. RESULTS: The maximum intensity was positively correlated with the microvessel density with statistical significance (r = 0.552; P = .03). The percentage of vascular endothelial growth factor expression did not have any correlation with the parameters from the curve. CONCLUSIONS: Contrast-enhanced sonography can reflect tumor vascularity in a prostate cancer animal model. Sonography of tumor angiogenesis may permit functional assessment of the tumor vasculature and provide an imaging biomarker for tumor responses to antiangiogenic therapies.

Predicting the fidelity of JPEG2000 compressed CT images using DICOM header information.

PURPOSE: To propose multiple logistic regression (MLR) and artificial neural network (ANN) models constructed using digital imaging and communications in medicine (DICOM) header information in predicting the fidelity of Joint Photographic Experts Group (JPEG) 2000 compressed abdomen computed tomography (CT) images. METHODS: Our institutional review board approved this study and waived informed patient consent. Using a JPEG2000 algorithm, 360 abdomen CT images were compressed reversibly (n = 48, as negative control) or irreversibly (n = 312) to one of different compression ratios (CRs) ranging from 4:1 to 10:1. Five radiologists independently determined whether the original and compressed images were distinguishable or indistinguishable. The 312 irreversibly compressed images were divided randomly into training (n = 156) and testing (n = 156) sets. The MLR and ANN models were constructed regarding the DICOM header information as independent variables and the pooled radiologists' responses as dependent variable. As independent variables, we selected the CR (DICOM tag number: 0028, 2112), effective tube current-time product (0018, 9332), section thickness (0018, 0050), and field of view (0018, 0090) among the DICOM tags. Using the training set, an optimal subset of independent variables was determined by backward stepwise selection in a four-fold cross-validation scheme. The MLR and ANN models were constructed with the determined independent variables using the training set. The models were then evaluated on the testing set by using receiver-operating-characteristic (ROC) analysis regarding the radiologists' pooled responses as the reference standard and by measuring Spearman rank correlation between the model prediction and the number of radiologists who rated the two images as distinguishable. RESULTS: The CR and section thickness were determined as the optimal independent variables. The areas under the ROC curve for the MLR and ANN predictions were 0.91 (95% CI; 0.86, 0.95) and 0.92 (0.87, 0.96), respectively. The correlation coefficients of the MLR and ANN predictions with the number of radiologists who responded as distinguishable were 0.76 (0.69, 0.82, p < 0.001) and 0.78 (0.71, 0.83, p < 0.001), respectively. CONCLUSIONS: The MLR and ANN models constructed using the DICOM header information offer promise in predicting the fidelity of JPEG2000 compressed abdomen CT images.