CT Diagnostic Performance Research Articles

Orbital CT scan parameters in dysthyroid optic neuropathy: a systematic review and meta-analysis.

Addressing Dysthyroid Optic Neuropathy (DON) is crucial due to its debilitating impact in thyroid eye disease (TED). Prompt treatment can preserve vision. Despite lacking definitive diagnostic criteria, computed tomography's (CT) parameters are commonly used for diagnosis. However, these parameters exist without consensus on their diagnostic performance. Systematic review and meta-analysis. We conducted a meta-analysis of studies assessing orbital CT diagnostic performance for DON in adults with TED. We searched various databases including Medline, PubMed, Scopus, and EMBASE, and others electronic databases, until July 2023. Evaluated CT parameters includes Barrett index (BI), fat prolapse via superior-orbital-fissure (SOF), superior-ophthalmic-vein-dilatation (SOVD), and the Nugent score. Diagnostic Test Accuracy analysis (DTA) was performed using R. A total of 9 articles with documented target parameters, collectively analysed 212 orbits with DON. Nugent score exhibited highest diagnostic ability with a log diagnostic odd ratio (logDOR) of 2.64 (95% CI, 2.02, 3.25). Another significant DON indicator was a BI ≥ 50%, with a logDOR of 1.97 (95% CI, 1.17; 2.77). Conversely, fat prolapse via SOF and SOVD proved less sensitive, with a logDOR of 1.42 and 1.09 respectively. Regarding the SROC curve, Nugent score and the BI have the greatest AUC. Variations in study locale, participant demographics, and measurement methods accounted for heterogeneity in meta-analysis. Nugent score and a BI ≥ 50% prove to be significant diagnostic parameters for DON, distinguishing them from fat prolapse via SOF and SOVD. Prioritizing these parameters can lead to prompt treatment and thus enhanced visual outcomes. CRD42023446376.

Evaluation of CT Scan Diagnostic Value in the Novel Coronavirus Disease and Presenting a Corona CT Severity Index.

Several diagnostic methods were proposed and evaluated for the COVID-19 disease. However, published studies have reported different diagnostic values for these methods. The present study aimed to evaluate the diagnostic performance and accuracy of CT in the novel coronavirus disease (COVID-19) and developed and presented a Corona CT severity index. In this retrospective study, CT diagnostic performance was measured based on sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy, and RT-PCR was regarded as a standard. Patients' CT reports were evaluated by a radiologist, and scoring and calculating of the CT severity index were performed. Of 208 patients, 82 showed positive, and 126 showed negative RT-PCR results with a positive frequency of 39.4% (95% CI, 32.7-46.4). The chest CT scan related to 136 patients indicated COVID- 19, whereas the initial RT-PCR assays of 56 patients were negative. Considering RT-PCR results as the reference standard, the sensitivity, specificity, and accuracy of chest CT to indicate COVID-19 infection were 100%, 55.6% (95% CI 46.4-64.4%), and 72.8% (95% CI 66.2-78.8%), respectively. The severity of pulmonary involvement was assigned with different grades. For 60.7% of patients with severity grades of 2 to 6, who showed the involvement of at least one lung lobe in CT, PCR retrieved negative results. CT scan shows an acceptable sensitivity as well as a consistently better specificity to identify COVID-19 pneumonia than PCR. It may be considered a major method to identify COVID-19 in epidemic locations.

CT findings and diagnostic performance of upper urinary tract carcinoma in situ.

To evaluate the CT characteristics and detectability of carcinoma in situ (CIS) of the upper urinary tract. Between January 2007 and March 2020, 28 patients (mean age: 73years, 25 male and 3 female) with 29 pure CIS lesions of the upper urinary tract (i.e., without concomitant non-CIS lesion) who underwent nephroureterectomy were identified. The most recent CT scan performed before ureteroscopy, systemic neoadjuvant chemotherapy, or nephroureterectomy was selected for analysis. Twenty-eight patients without upper tract malignancy were selected as a control group. All images were evaluated for presence of upper urinary tract CIS using confidence levels ranging from 1 to 100 by two radiologists. The confidence level of 75 was used as a cutoff threshold for calculating sensitivity and specificity. The median interval between CT scan and nephroureterectomy was 96days. The number of true-positive lesions (per-lesion sensitivity) was 41% (12/29) and 52% (15/29) by readers 1 and 2. The true-positive lesion appeared as wall thickening in 83% (10/12) by reader 1 and 80% (12/15) by reader 2, and as a mass in 17% (2/12) by reader 1 and 20% (3/15) by reader 2. All mass-forming lesions were located in the renal collecting system. The per-patient sensitivity and specificity were 42% and 100% in reader 1, and 54% and 96% in reader 2. The common abnormal finding of pure CIS in the upper urinary tract was wall thickening. Pure CIS could also appear as a mass-forming lesion when it is located in the renal collecting system. • The common abnormal finding of pure CIS in the upper urinary tract is wall thickening. Gradually progressive urothelial wall thickening and/or worsening symptoms should raise the suspicion of CIS. • Pure CIS in the upper urinary tract also appears as a mass-forming lesion when it is located in the renal collecting system. • Hydronephrosis and fat stranding play an auxiliary role in detecting pure CIS in the upper urinary tract.

Systematic review and meta-analysis of diagnostic performance of CT imaging for assessing resectability of pancreatic ductal adenocarcinoma after neoadjuvant therapy: importance of CT criteria.

To assess the CT diagnostic performance for evaluating resectability of pancreatic ductal adenocarcinoma (PDAC) after neoadjuvant therapy and identify the factor(s) that affect(s) diagnostic performance. Databases were searched to identify studies published from January 1, 2000, to November 5, 2019 that evaluated the CT diagnostic performance for assessing resectability of post-neoadjuvant PDAC. Two reviewers independently extracted data and assessed the study quality. A meta-analysis was performed to obtain summary sensitivity and specificity values using a bivariate random-effects model, and heterogeneity across studies was assessed. Univariable meta-regression analysis was performed with eight variables, including the different CT criteria for resectability, conventional National Comprehensive Cancer Network (NCCN) criteria for upfront surgery, and modified criteria for post-neoadjuvant surgery. Ten studies were included and analyzed. The summary sensitivity and specificity for resectability were 78% (95% CI 68-86%) and 60% (95% CI 44-74%), respectively. No significant heterogeneity was identified (bivariate correlation coefficient ρ = - 1, p-value for hierarchical summary receiver operating characteristics model β = 0.667). The two different CT criteria showed different diagnostic performance (p < 0.01), with higher sensitivity (81% [95% CI 73-90%] vs. 28% [95% CI 15-42%], p < 0.01) and lower specificity (57% [95% CI 41-73%] vs. 90% [95% CI 80-100%], p < 0.01) for the modified criteria. No other variables affected the diagnostic performance. CT criteria were the factors that affected the diagnostic performance. Modification of the conventional criteria improved sensitivity but lowered specificity. Further modifications are required to improve specificity and uniformity.

Temporal variations in the diagnostic performance of chest CT for Covid-19 depending on disease prevalence: Experience from North-Eastern France

Rationale and ObjectiveThe purpose of this work was to analyze temporal variations in the diagnostic performance of chest CT for Covid-19 throughout the first wave, depending on disease prevalence variations between the ascending, peak and descending phases of the epidemic in North-Eastern France. Materials and MethodsFrom March 6th to April 22nd 2020, all consecutive adult patients referred to the “Covid-19 clinic” of our Emergency Department with the availability of chest CT and of at least one RT-PCR result were retrospectively included in the present study. Chest CT was considered positive when typical Covid-19 lesions were observed (bilateral and predominantly peripheral and sub-pleural ground glass opacities and/or alveolar consolidations). RT-PCR results were considered as the reference standard. Ascending, peak and descending phases were determined based on the number of CT scans performed daily. CT diagnostic performance were calculated and variations between phases were tested for equivalence or difference using Bayesian methods. Results2194 consecutive chest CT were analyzed. Overall CT diagnostic performance was Se = 84.2 [82.0 ; 86.3], Sp = 86.6 [84.5 ; 88.5], PPV = 86.1 [84.0 ; 88.1], NPV = 84.7 [82.6 ; 86.7] and accuracy = 85.4 [83.9 ; 86.8], with no significant differences between chest and non-chest radiologists. Variations between the ascending (11 days, 281 chest CT, disease prevalence 37.0 %), the peak (18 days, 1167 chest CT, disease prevalence 64 %) and the descending phases (19 days, 746 chest CT, disease prevalence 32.2 %) were highest for PPV and NPV with a probability of difference >99.9 %, and smallest for accuracy and specificity with a probability of equivalence >98.8 %. ConclusionIn a homogenous cohort of 2194 consecutive chest CT performed over a 7-week epidemic wave, we observed significant variations of CT predictive values whereas CT specificity appeared marginally affected.

CT evaluation of extranodal extension of cervical lymph node metastases in patients with oral squamous cell carcinoma using deep learning classification.

To clarify CT diagnostic performance in extranodal extension of cervical lymph node metastases using deep learning classification. Seven-hundred and three CT images (178 with and 525 without extranodal extension) in 51 patients with cervical lymph node metastases from oral squamous cell carcinoma were enrolled in this study. CT images were cropped to an arbitrary size to include lymph nodes and surrounding tissues. All images were automatically divided into two datasets, assigning 80% as the training dataset and 20% as the testing dataset. The automated selection was repeated five times. Each training dataset was imported to a deep learning training system "DIGITS". Five learning models were created after 300 epochs of the learning process using a neural network "AlexNet". Each testing dataset was applied to each created learning model and resulting five performances were averaged as estimated diagnostic performances. A radiologist measured the minor axis and three radiologists evaluated central necrosis and irregular borders of each lymph node, and the diagnostic performances were obtained. The deep learning accuracy of extranodal extension was 84.0%. The radiologists' accuracies based on minor axis ≥ 11mm, central necrosis, and irregular borders were 55.7%, 51.1% and 62.6%, respectively. The deep learning diagnostic performance in extranodal extension was significantly higher than that of radiologists. This method is expected to improve diagnostic accuracy by further study with increasing the number of patients.

Value of early repeated abdominal CT in selective non-operative management for blunt bowel and mesenteric injury.

To evaluate the performance of an early repeated computed tomography (rCT) in initially non-operated patients with blunt bowel and mesenteric injuries (BBMI). This was a monocentric retrospective observational study from 2009 to 2017 of patients with a BBMI on initial CT (iCT). Patients initially non-operated on were scheduled for a rCT within 48h. Initial CT and rCT diagnostic performance were compared based on a surgical injury prediction score previously described. For statistical analysis, we used the chi-square analyses for paired data (McNemar test). Eighty-four patients (1.9% of trauma) had suspected BBMI on iCT. Among these patients, 22 (26.2%) were initially operated on, 18 (21.4%) were later operated on, and 44 (52.4%) were not operated on. The therapeutic laparotomy rate was 85%. Thirty-four patients initially non-operated on had a rCT. The absolute value of the CT scan score increased for 15 patients (44.1%). The early rCT diagnostic performance, compared with iCT, showed an increase in sensitivity (from 63.6 to 91.7%), in negative predictive value (from 77.4 to 94.7%), and in AUC (from 0.77 to 0.94). In initially non-operated patients with BBMI lesions, the performance of an early rCT improved the sensitivity of lesion detection requiring surgical repair and the security of patient selection for non-operative treatment. • Selective non-operative treatment for hemodynamically stable patients with blunt bowel and/or mesenteric injuries on CT is developing but remains controversial. • An early repeated CT improved the sensitivity of lesion detection requiring surgical repair and the security of patient selection for conservative treatment.

CT angiography (CTA) and diagnostic performance of noninvasive fractional flow reserve: results from the Determination of Fractional Flow Reserve by Anatomic CTA (DeFACTO) study.

Fractional flow reserve (FFR) computed from standard coronary CT scans (FFRCT) is a novel noninvasive method for determining the functional significance of coronary artery lesions. Compared with CT alone, FFRCT significantly improves diagnostic accuracy and discrimination for patients with and without hemodynamically significant coronary artery stenoses. To date, the impact of CT image quality on diagnostic performance of FFRCT is unknown. We evaluated the impact of patient preparation, CT scan protocol, and factors related to image quality on the diagnostic accuracy of FFRCT. We studied stable patients with suspected coronary artery disease (CAD), enrolled from 17 centers, who underwent CT, invasive coronary angiography, FFR, and FFRCT. The accuracy of CT and FFRCT for diagnosis of ischemia was compared against an invasive FFR reference standard. Anatomically obstructive CAD was defined by a stenosis value of at least 50 by CT or invasive coronary angiography, whereas ischemia was defined by an FFR or FFRCT of up to 0.80. Ischemia was assessed at the per-patient and per-vessel levels. Diagnostic performance of FFRCT was then evaluated in relation to patient preparation, including administration before CT of a β-blocker or nitroglycerin, as well as in relation to imaging characteristics, including misalignment, noise, motion, and coronary artery calcium. Among 252 study participants, 137 (54.0%) had an abnormal FFR. Administration of a β-blocker increased FFRCT specificity (51.0% vs 66.0%; p = 0.03) with lower bias (-0.084 vs -0.048; p = 0.008), whereas nitroglycerin pretreatment within 30 minutes of CT was associated with improved specificity (54.0% vs 75.0%; p = 0.013). Misalignment artifacts resulted in impaired sensitivity (43.0% vs 86.0%; p = 0.001) with resultant reductions in overall accuracy (56.0% vs 71.0%; p = 0.03). No differences in diagnostic performance of FFRCT were noted in the presence of coronary motion or increasing coronary artery calcium score. Use of β-blockade and nitroglycerin administration before CT improve diagnostic performance of FFRCT. Diagnostic accuracy of FFRCT is significantly reduced in the setting of misalignment artifacts.

N staging of lung cancer patients with PET/MRI using a three-segment model attenuation correction algorithm: Initial experience

Evaluate the performance of PET/MRI at tissue interfaces with different attenuation values for detecting lymph node (LN) metastases and for accurately measuring maximum standardised uptake values (SUVmax) in lung cancer patients. Eleven patients underwent PET/CT and PET/MRI for staging, restaging or follow-up of suspected or known lung cancer. Four experienced readers determined the N stage of the patients for each imaging method in a randomised blinded way. Concerning metastases, SUVmax of FDG-avid LNs were measured in PET/CT and PET/MRI in all patients. A standard of reference was created with a fifth experienced independent reader in combination with a chart review. Results were analysed to determine interobserver agreement, SUVmax correlation between CT and MRI (three-segment model) attenuation correction and diagnostic performance of the two techniques. Overall interobserver agreement was high (κ = 0.86) for PET/CT and substantial (κ = 0.70) for PET/MRI. SUVmax showed strong positive correlation (Spearman's correlation coefficient = 0.93, P < 0.001) between the two techniques. Diagnostic performance of PET/MRI was slightly inferior to that of PET/CT, without statistical significance (P > 0.05). PET/MRI using three-segment model attenuation correction for LN staging in lung cancer shows a strong parallel to PET/CT in terms of SUVmax, interobserver agreement and diagnostic performance. •F18-FDG PET/MRI shows similar performance to F18-FDG PET/CT in lung cancer N staging. •PET/MRI has substantial interobserver agreement in N staging. •A three-segment model attenuation correction is reliable for assessing the mediastinum.