Comparison of dual-energy computed tomography (DECT) polychromatic and monochromatic images with and without iterative metal artifact reduction algorithm in patients with dental implants.

Background: Dual-energy computed tomography (DECT) and iterative metal artifact reduction (iMAR) algorithms are valuable tools for reducing metal artifacts. Different parameters of these technologies and their combination can achieve different performance. This study compared various polychromatic and monochromatic images obtained via DECT with and without using iMAR algorithm to reduce artifacts in patients with dental implants. Methods: This study included 30 patients with dental implants who underwent DECT for head and neck imaging. The computed tomography (CT) image sets comprised DECT polychromatic image sets [dual-energy (DE) polychromatic] that linearly blended 100 kV and tin-filtered 140 kV images using composition ratios of -1, -0.6, -0.3, 0, and 0.6, and virtual monochromatic images (DE monochromatic) at 90, 110, 130, 150, and 170 keV. These image sets were obtained with and without using iMAR, resulting in a total of 20 image sets. For subjective analysis, metal artifacts and image quality were assessed using a 5-point Likert scale. For objective analysis, CT attenuation, standard deviation (SD), contrast-to-noise ratio (CNR) and artifact index (AI) were evaluated. In addition, subgroup analysis was performed based on implant size. Results: In the subjective evaluation, iMAR + DE polychromatic (-0.3) images exhibited the lowest metal artifact scores [median (interquartile range): 2 (2-3)]. iMAR + DE monochromatic (110 keV) images demonstrated optimal image quality scores [median (interquartile range): 2 (2-3)]. In the objective evaluation, none of the images demonstrated a significant difference in the CNR, except polychromatic images with a composition of -1 and 0.6. iMAR + DE polychromatic (0) exhibited the lowest AI [median (interquartile range): 8.7 (5.9-14.5)]. There was no significant difference between the two groups with different implant sizes for the techniques combined with iMAR (all P>0.05). Conclusion: iMAR + DE polychromatic (-0.3 and 0) and iMAR + DE monochromatic (110 keV) images exhibited better image quality and substantial metal artifact reduction (MAR) compared with the other image sets. The performance of the techniques combined with iMAR was not affected by the size of the implant.

Upfront surgery for stage IIIA/B non-small cell lung cancer: retrospective cohort study.

BACKGROUND: Stage III non-small cell lung cancer is a heterogeneous disease. Several international guidelines recommend neoadjuvant treatment before surgery; however, upfront surgery is the preferred approach for technically resectable non-small cell lung cancer in East Asia. The aim of this retrospective study was to evaluate the long-term outcomes of curative-intent upfront surgery in stage IIIA/B non-small cell lung cancer. METHODS: Patients who underwent curative-intent upfront surgery with stage cIIIA/B non-small cell lung cancer were identified. The clinical and pathological variables and survival outcomes were evaluated. RESULTS: Overall, 664 patients were identified, of whom 320 (48.8%) had N2 disease, 66.7% were males, 49.4% had a smoking history, and 61.2% had lung adenocarcinoma. Lobectomy was the most performed surgical procedure (84.9%). A total of 40 patients (6.02%) had positive margins (R1/R2). The grade III adverse event rate was 2.0% (13 of 664). The median follow-up was 30.6 (range 1.9-97.7) months. At follow-up, the mortality rate was 13.3% (88 of 664) and 37.2% of patients (247 of 664) had recurrence. Lung (101 of 247 (40.9%)) and brain (53 of 247 (21.5%)) were the most common sites of recurrence. The median overall survival was 60.0 (95% c.i. 51.5 to 67.6) months, with overall survival probability at 1, 2, 3, and 5 years being 89.6%, 77.8%, 67.2%, and 49.0% respectively. The R0 cohort showed an improved median overall survival compared with the R1/R2 cohort (67.4 versus 26.5 months respectively; P = greater than 0.001). The multivariable analysis revealed that age greater than or equal to 65 years (HR 1.51, 95% c.i. 1.08 to 2.12; reference = age less than 65 years), tumour size (greater than or equal to 5 cm (HR 2.13, 95% c.i. 1.41 to 3.21) and greater than or equal to 3 cm but less than 5 cm (HR 1.15, 95% c.i. 0.78 to 1.71); reference = less than 3 cm), and adjuvant treatment (chemotherapy (HR 0.69, 95% c.i. 0.49 to 0.96) and targeted therapy (HR 0.30, 95% c.i. 0.12 to 0.76); reference = none) significantly predicted overall survival. CONCLUSION: Upfront surgery is an option for the management of stage IIIA/B non-small cell lung cancer.

Pancreatic fat fraction in dual-energy computed tomography as a potential quantitative parameter in the detection of type 2 diabetes mellitus.

PURPOSE: To investigate the clinical value of measuring pancreatic fat fraction using dual-energy computed tomography (DECT) in association with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: This retrospective study included patients who underwent abdominal DECT between September 2021 and July 2022. The fat fractions in the head, body, and tail of the pancreas were calculated using fat maps generated from unenhanced DECT images, and CT values were measured at the same locations. The intraclass correlation coefficient (ICC) was used to analyze the reproducibility of measurements from two observers. Diagnostic performance was assessed using receiver operating characteristic curves. RESULTS: Seventy-eight patients, including 45 T2DM patients and 33 controls, were enrolled. The fat fractions of the pancreas were significantly higher in the T2DM group than in the control group (pancreatic head: 8.4 ± 6.3 % vs 5.1 ± 3.9 %; pancreatic body: 4.8 ± 4.0 % vs 2.7 ± 3.9 %; and pancreatic tail: 5.3 ± 3.2 % vs 2.7 ± 2.9 %, all p < 0.05). And the CT values of the pancreas were significantly lower in the T2DM group than in the control group (pancreatic head: 41.1 ± 8.5 HU vs 45.7 ± 4.6 HU; pancreatic body: 44.4 ± 5.0 HU vs 47.4 ± 3.7 HU; and pancreatic tail: 44.5 ± 5.0 HU vs 47.6 ± 3.2 HU, all p < 0.05). The fat fraction of the pancreatic tail was the best indicator for distinguishing T2DM patients from the controls (area under the curve: 0.716 (95 % CI: 0.601, 0.832), sensitivity: 64.4 % (95 % CI: 48.7 %, 77.7 %), and specificity: 78.8 % (95 % CI: 60.6 %, 90.4 %)). CONCLUSION: The DECT fat fractions of the pancreas could be a valuable additional parameter in the detection of T2DM.