Background Patients with urolithiasis undergo radiation overexposure from computed tomography (CT) scans. Improvement of image reconstruction is necessary for radiation dose reduction. Purpose To evaluate a deep learning-based reconstruction algorithm for CT (DLIR) in the detection of urolithiasis at low-dose non-enhanced abdominopelvic CT. Material and Methods A total of 75 patients who underwent low-dose abdominopelvic CT for urolithiasis were retrospectively included. Each examination included three reconstructions: DLIR; filtered back projection (FBP); and hybrid iterative reconstruction (IR; ASiR-V 70%). Image quality was subjectively and objectively assessed using attenuation and noise measurements in order to calculate the signal-to-noise ratio (SNR), absolute contrast, and contrast-to-noise ratio (CNR). Attenuation of the largest stones were also compared. Detectability of urinary stones was assessed by two observers. Results Image noise was significantly reduced with DLIR: 7.2 versus 17 and 22 for ASiR-V 70% and FBP, respectively. Similarly, SNR and CNR were also higher compared to the standard reconstructions. When the structures had close attenuation values, contrast was lower with DLIR compared to ASiR-V. Attenuation of stones was also lowered in the DLIR series. Subjective image quality was significantly higher with DLIR. The detectability of all stones and stones >3 mm was excellent with DLIR for the two observers (intraclass correlation [ICC] = 0.93 vs. 0.96 and 0.95 vs. 0.99). For smaller stones (<3 mm), results were different (ICC = 0.77 vs. 0.86). Conclusion For low-dose abdominopelvic CT, DLIR reconstruction exhibited image quality superior to ASiR-V and FBP as well as an excellent detection of urinary stones.
Background
In the "treat-to-target" era, the development of non-invasive markers to assess endoscopic healing in ulcerative colitis (UC) is essential. Fecal calprotectin (FC) and intestinal ultrasound (IUS) are alternatives to colonoscopy to assess UC activity. The objective of this study was to evaluate the performance of IUS and FC to assess endoscopic mucosal healing in UC patient.
Methods
All consecutive patients between January 2021 and August 2022 with UC who underwent (1) a complete colonoscopy (2) an intestinal ultrasound and/or (3) a fecal calprotectin (4) within 4 weeks were included in a prospective cohort. Bowel wall thickness (BWT) and color doppler signal (CDS) were assessed on each segment. Endoscopic mucosal healing was defined by a MAYO score of 0-1.
Results
A total of 57 patients were included, 57.9% had endoscopic healing (22/57 MAYO 0 and 11/57 MAYO 1). Thirty-two (56.1%) were female, the median age and disease duration were respectively 43 years (IQR, 30-58) and 29 years (IQR, 18-39). Respectively 16 (16/57, 28.1%) and 41 (41/57, 71.9%) patients had BWT < 3 mm and an absence of Doppler signal. The sensitivity (Se), specificity (Sp), positive predictive value (PPV) and negative predictive value (NPV) of BWT < 3 mm to predict endoscopic mucosal healing were 37%, 77%, 72% and 44%. The association of the absence of CDS with normal BWT did not modify these performances. The same values for fecal calprotectin < 150 µg/g were respectively 81%, 78%, 84% and 74%. The association of a fecal calprotectin < 150 µg/g, with a BWT < 3mm and the absence of Doppler signal increased the specificity and the PPV (Se 33%, Sp 94%, PPV 89%, VPN 48%). The same values were found for patients classified as MAYO 0 or MAYO 0-1 (Table 1).
Conclusion
The combination of intestinal ultrasound and fecal calprotectin is effective to identify endoscopic mucosal healing in UC.
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