Purpose To compare the sensitivity and specificity of contrast-enhanced ultrasound (CEUS), computed tomography (CT) and magnetic resonance imaging (MRI) in the evaluation of unclear renal lesions to the histopathological outcome. Materials and methods A total of 255 patients with a single unclear renal mass with initial imaging studies between 2005 and 2015 were included. Patient ages ranged from 18 to 86 with (mean age 62 years; SD ± 13). CEUS (255 patients), CT (88 out of 255 patients; 34.5 %) and MRI (36 out of 255 patients; 14.1 %) were used for determining malignancy or benignancy and initial findings were correlated with the histopathological outcome. Results CEUS showed a sensitivity of 99.1 % (95 % confidence interval (CI): 96.7 %, 99.9 %), a specificity of 80.5 % (95 % CI: 65.1 %, 91.2 %), a positive predictive value (PPV) of 96.4 % (95 % CI: 93.0 %, 98.4 %) and a negative predictive value (NPV) of 94.3 % (95 % CI: 80.8 %, 99.3 %). CT showed a sensitivity of 97.1 % (95 % CI: 89.9 %, 99.6 %), a specificity of 47.4 % (95 % CI: 24.4 %, 71.1 %), a PPV of 87.0 % (95 % CI: 77.4 %, 93.6 %) and a NPV of 81.8 % (95 % CI: 48.2 %, 97.7 %). MRI showed a sensitivity of 96.4 % (95 % CI: 81.7 %, 99.9 %), a specificity of 75.0 % (95 % CI: 34.9 %, 96.8 %), a PPV of 93.1 % (95 % CI: 77.2 %, 99.2 %) and a NPV of 85.7 % (95 % CI: 42.1 %, 99.6 %). Out of the 212 malignant lesions a total of 130 clear cell renal carcinomas, 59 papillary renal cell carcinomas, 7 chromophobe renal cell carcinomas, 4 combined clear cell and papillary renal cell carcinomas and 12 other malignant lesions, e. g. metastases, were diagnosed. Out of the 43 benign lesions a total 10 angiomyolipomas, 3 oncocytomas, 8 benign renal cysts and 22 other benign lesions, e. g. renal adenomas were diagnosed. Using CEUS, 10 lesions were falsely identified as malignant or benign, whereas 8 lesions were false positive and 2 lesions false negative. Conclusion CEUS is an useful method which can be additionally used to clinically differentiate between malignant and benign renal lesions. CEUS shows a comparable sensitivity, specificity, PPV and NPV to CT and MRI. In daily clinical routine, patients with contraindications for other imaging modalities can particularly benefit using this method. Key Points: Citation Format
Background: In patients with poorly differentiated thyroid carcinoma, the clinical course and prognostic value of response to initial radioiodine therapy is evaluated. Methods: In 47 patients, clinical and imaging features were analyzed. Patients were stratified in no (NED), biochemical (B-ED) and structural evidence of disease (S-ED) assessed at the first diagnostic control and its impact on survival was evaluated. Further, possible risk factors for a shorter disease-specific survival rate (DSS) were analyzed. Results: In total, 17/47 patients consisted of NED, 10/47 were B-ED and 20/47 S-ED patients. At the last follow-up, 18/47 patients were NED, 2/47 patients B-ED and 27/47 patients S-ED. The median survival time was only reached for the S-ED group (median 3.9 years, 95%CI 2.8–5.1 years) and was not reached in the B-ED and NED groups. Metastases were diagnosed by a 18F-FDG-PET/CT scan in all cases and a multivariate analysis showed that the PET-positivity of metastases was the only significant predictor of DSS (p = 0.036). Conclusion: The response to initial surgery and radioiodine therapy in PDTC patients can achieve an excellent outcome and a further follow-up should be refined based on findings at the first diagnostic control. However, patients with an incomplete response and metastatic patients who become mostly radioiodine refractory show a significantly shorter survival, which makes accurate staging by 18F-FDG-PET/CT imaging crucial.
Background The aim of this retrospective study was to compare the diagnostic accuracy of somatostatin receptor (SSR)-PET/CT to liver MRI as reference standard in the evaluation of hepatic involvement in neuroendocrine tumors (NET). Methods An institutional database was screened for “SSR” imaging studies between 2006 and 2021. 1000 NET Patients (grade 1/2) with 2383 SSR-PET/CT studies and matching liver MRI in an interval of +3 months were identified. Medical reports of SSR-PET/CT and MRI were retrospectively evaluated regarding hepatic involvement and either confirmed by both or observed in MRI but not in SSR-PET/CT (false-negative) or in SSR-PET but not in MRI (false-positive). Results Metastatic hepatic involvement was reported in 1650 (69.2%) of the total 2383 SSR-PET/CT imaging studies, whereas MRI detected hepatic involvement in 1685 (70.7%) cases. There were 51 (2.1%) false-negative and 16 (0.7%) false-positive cases. In case of discrepant reports, MRI and PET/CT were reviewed side by side for consensus reading. SSR-PET/CT demonstrated a sensitivity of 97.0% (95%CI: 96.0%, 97.7%), a specificity of 97.7% (95%CI: 96.3%, 98.7%), a PPV of 99.0% (95%CI: 98.4%, 99.4%) and NPV of 93.0% (95%CI: 91.0, 94.8%) in identifying hepatic involvement. The most frequent reason for false-negative results was the small size of lesions with the majority < 0.6 cm. Conclusion This study confirms the high diagnostic accuracy of SSR-PET/CT in the detection of hepatic involvement in NET patients based on a patient-based analysis of metastatic hepatic involvement with a high sensitivity and specificity using liver MRI imaging as reference standard. However, one should be aware of possible pitfalls when a single imaging method is used in evaluating neuroendocrine liver metastases in patients.
Objectives The recently proposed standardized reporting and data system for somatostatin receptor (SSTR)–targeted PET/CT SSTR-RADS 1.0 showed promising first results in the assessment of diagnosis and treatment planning with peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET). This study aimed to determine the intra- and interreader agreement of SSTR-RADS 1.0. Methods SSTR-PET/CT scans of 100 patients were independently evaluated by 4 readers with different levels of expertise according to the SSTR-RADS 1.0 criteria at 2 time points within 6 weeks. For each scan, a maximum of five target lesions were freely chosen by each reader (not more than three lesions per organ) and stratified according to the SSTR-RADS 1.0 criteria. Overall scan score and binary decision on PRRT were assessed. Intra- and interreader agreement was determined using the intraclass correlation coefficient (ICC). Results Interreader agreement using SSTR-RADS 1.0 for identical target lesions (ICC ≥ 0.91) and overall scan score (ICC ≥ 0.93) was excellent. The decision to state “functional imaging fulfills requirements for PRRT and qualifies patient as potential candidate for PRRT” also demonstrated excellent agreement among all readers (ICC ≥ 0.86). Intrareader agreement was excellent even among different experience levels when comparing target lesion–based scores (ICC ≥ 0.98), overall scan score (ICC ≥ 0.93), and decision for PRRT (ICC ≥ 0.88). Conclusion SSTR-RADS 1.0 represents a highly reproducible and accurate system for stratifying SSTR-targeted PET/CT scans with high intra- and interreader agreement. The system is a promising approach to standardize the diagnosis and treatment planning in NET patients. Key Points • SSTR-RADS 1.0 offers high reproducibility and accuracy. • SSTR-RADS 1.0 is a promising method to standardize diagnosis and treatment planning for patients with NET.
Stone treatment decisions are guided by stone size and stone density. We have previously shown that automated stone volume measurements are more precise than manual size measurements. We tested a novel dedicated renal stone software program that provides a comprehensive radiographic stone profile with a single click.METHODS: Urinary stones identified on CT scans were measured by a single reader to obtain the longest length on axial images and coronal images. A region of interest (ROI) was drawn inside of the stone to obtain minimum, maximum, average and standard deviation densities. The same stones were then assessed with an automated comprehensive radiographic stone profile software. This software produces the minimum and maximum linear diameter; minimum, maximum, and average stone density as well as stone volume. Maximum linear diameter, maximum density and average densities were compared between the manual measurements and the automated software data to obtain the percent difference between the measurements. The longer of either the axial or coronal manual measurements was used to compare with the maximum linear diameter from the stone profile software.RESULTS: 17 patients were identified who had a total of 42 CT scans with 85 unique stones. Patients had an average of 2.5 scans with an average of 5 stones. Stone sizes ranged from 1.9 mm to 21 mm in length with a mean of 8 mm. The average density measurement was 451 . Volume obtained from the stone profile software averaged 182 mm3 (2.8-2668 mm3). The maximum diameter between the manual and software differed by an average of 19.1% (0-54.8%). Maximum density differed by an average of 11% (0-66.6%) and average density differed by an average of 24% (0-78%).CONCLUSIONS: Automated comprehensive radiographic stone profiling can be accomplished with a single click and closely approximates manual measurements which can be laborious, requiring the reader to measure length on 2 different CT scan reconstructions and carefully place a region of interest around the stone. Automated stone profiling was able to assess stones as small as 1.9mm as well as stones with complex geometry. Stone volume was obtained in true maximum length, and density information thus facilitating rapid and accurate "one click measurements" for clinical decision making.
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