Malignancies of the nasal cavity and paranasal sinuses account for 1% of all malignancies and 3% of malignancies of the upper aerodigestive tract. In the sinonasal tract, nearly half of all malignancies arise in the nasal cavity, whereas most of the remaining malignancies arise in the maxillary or ethmoid sinus. Squamous cell carcinoma is the most common histological subtype of malignant tumors occurring in this area, followed by other epithelial carcinomas, lymphomas, and malignant soft tissue tumors. Although many of these tumors present with nonspecific symptoms, each tumor exhibits characteristic imaging features. Although complex anatomy and various normal variants of the sinonasal tract cause difficulty in identifying the origin and extension of large sinonasal tumors, the invasion of vital structures such as the brain, optic nerves, and internal carotid artery affects patients’ prognosis. Thus, diagnostic imaging plays a key role in predicting the histological subtype and in evaluating a tumor extension into adjacent structures. This article describes the computed tomography and magnetic resonance imaging findings for malignant sinonasal tumors.

Objectives: To evaluate image quality and lesion detection capabilities of low-dose (LD) portal venous phase whole-body computed tomography (CT) using deep learning image reconstruction (DLIR). Methods: The study cohort of 59 consecutive patients (mean age, 67.2 years) who underwent whole-body LD CT and a prior standard-dose (SD) CT reconstructed with hybrid iterative reconstruction (SD-IR) within one year for surveillance of malignancy were assessed. The LD CT images were reconstructed with hybrid iterative reconstruction of 40% (LD-IR) and DLIR (LD-DLIR). The radiologists independently evaluated image quality (5-point scale) and lesion detection. Attenuation values in Hounsfield units (HU) of the liver, pancreas, spleen, abdominal aorta, and portal vein; the background noise and signal-to-noise ratio (SNR) of the liver, pancreas, and spleen were calculated. Qualitative and quantitative parameters were compared between the SD-IR, LD-IR, and LD-DLIR images. The CT dose-index volumes (CTDIvol) and dose-length product (DLP) were compared between SD and LD scans. Results: The image quality and lesion detection rate of the LD-DLIR was comparable to the SD-IR. The image quality was significantly better in SD-IR than in LD-IR (p < 0.017). The attenuation values of all anatomical structures were comparable between the SD-IR and LD-DLIR (p = 0.28–0.96). However, background noise was significantly lower in the LD-DLIR (p < 0.001) and resulted in improved SNRs (p < 0.001) compared to the SD-IR and LD-IR images. The mean CTDIvol and DLP were significantly lower in the LD (2.9 mGy and 216.2 mGy•cm) than in the SD (13.5 mGy and 1011.6 mGy•cm) (p < 0.0001). Conclusion: LD CT images reconstructed with DLIR enable radiation dose reduction of >75% while maintaining image quality and lesion detection rate and superior SNR in comparison to SD-IR. Advances in knowledge: Deep learning image reconstruction algorithm enables around 80% reduction in radiation dose while maintaining the image quality and lesion detection compared to standard-dose whole-body CT.

Objective: To evaluate the feasibility of a simultaneous reduction of radiation and iodine doses in dual-energy thoraco-abdomino-pelvic CT reconstructed with deep learning image reconstruction (DLIR). Methods: Thoraco-abdomino-pelvic CT was prospectively performed in 111 participants; 52 participants underwent a standard-dose single-energy CT with a standard iodine dose (600 mgI/kg; SD group), while 59 underwent a low-dose dual-energy CT with a reduced iodine dose [300 mgI/kg; double low-dose (DLD) group]. CT data were reconstructed with a hybrid iterative reconstruction in the SD group and a high-strength level of DLIR at 40 keV in the DLD group. Two radiologists measured the CT numbers of the descending and abdominal aorta, portal vein, hepatic vein, inferior vena cava, liver, pancreas, spleen, and kidney, and background noise. Two other radiologists assessed diagnostic acceptability using a 5-point scale. The CT dose-index volume (CTDIvol), iodine weight, CT numbers of anatomical structures, background noise, and diagnostic acceptability were compared between the two groups using Mann–Whitney U test. Results: The median CTDIvol [10 mGy; interquartile range (IQR), 9–13 mGy vs 4 mGy; IQR, 4–5 mGy] and median iodine weight (35 g; IQR, 31–38 g vs 16 g; IQR, 14–18 g) were lower in the DLD group than in the SD group (p < 0.001 for each). The CT numbers of all anatomical structures and background noise were higher in the DLD group than in the SD group (p < 0.001 for all). The diagnostic image quality was obtained in 100% (52/52) of participants in the SD group and 95% (56/59) of participants in the DLD group. Conclusion: Virtual monochromatic images at 40 keV reconstructed with DLIR could achieve half doses of radiation and iodine while maintaining diagnostic image quality. Advances in knowledge: Virtual monochromatic images at 40 keV reconstructed with DLIR algorithm allowed to reduce the doses of radiation and iodine while maintaining diagnostic image quality.

Objective: Standard treatment for progressive gastric cancer with bleeding includes hemostatic radiotherapy (RT); however, the only prospective study using a fixed dose with fractions during hemostatic RT did not introduce re-irradiation. Therefore, we determined the utility of RT including re-irradiation for gastric cancer. Methods: In this study, 31 patients with gastric cancer and bleeding were treated with an initial dose of 20 Gy/5 fractions for the whole stomach and a salvage dose of 15 Gy/5 fractions for the partial stomach. Patients achieving hemostasis, defined as a stable hemoglobin level within 30 days following irradiation, were considered responders, whereas those with no cessation of bleeding and those with re-bleeding within 30 days of irradiation were considered non-responders. We evaluated response rate, disease-free survival, overall survival (OS), re-irradiation, and adverse events (AEs). Results: The response rate of initial RT was 80% (25/31). 6 of the 25 patients underwent re-irradiation, and all 6 were responders (100%). The median OS was significantly different among the entire cohort and one-time irradiation and re-irradiation groups (91, 76, and 112 days, respectively). No AEs of grade ≥3 were observed. Initial low-dose RT followed by reirradiation was effective in reducing AEs and did not cause any further AEs. Conclusion: Hemostatic RT was an effective approach with low toxicity, and re-irradiation was effective and tolerable, with no patients developing severe AEs. Further, randomized controlled studies are warranted to determine the ideal dose and number of fractions for initial RT in patients with gastric cancer and bleeding. Advances in knowledge: In this prospective study on hemostatic radiotherapy for gastric cancer, the response rate was 80% using a fixed dose of 20 Gy/5 fractions and the salvage dose of 15 Gy for re-bleeding was effective. Future comparative studies should include other doses with 20 Gy as a control.

Objectives: To assess the feasibility of whole-body dual-energy computed tomographic angiography (DECTA) at 40 keV with 50% reduced iodine dose protocol. Methods: Whole-body CTA was performed in 65 patients; 31 of these patients underwent 120 kVp single-energy computed tomographic angiography (SECTA) with standard iodine dose (600 mgI/kg) and 34 with 40 keV DECTA with 50% reduced iodine dose (300 mgI/kg). SECTA data were reconstructed with adaptive statistical iterative reconstruction of 40% (SECTA group), and DECTA data were reconstructed with adaptive statistical iterative reconstruction of 40% (DECTA-40% group) and 80% (DECTA-80% group). CT numbers of the thoracic and abdominal aorta, iliac artery, background noise, signal-to-noise ratio (SNR), and arterial depiction were compared among the three groups. The CT dose index volumes (CTDIvol) for the thorax, abdomen, and pelvis were compared between SECTA and DECTA protocols. Results: The vascular CT numbers and background noise were found to be significantly higher in DECTA groups than in the SECTA group (p < 0.001). SNR was significantly higher in the order corresponding to DECTA-80%, SECTA, and DECTA-40% (p < 0.001). The arterial depiction was comparable in almost all arteries; however, intrapelvic arterial depiction was significantly worse in DECTA groups than in the SECTA group (p < 0.0001–0.017). Unlike the pelvic region (p = 0.055), CTDIvol for the thorax (p < 0.0001) and abdomen (p = 0.0031) were significantly higher in the DECTA protocol than in the SECTA protocol. Conclusion: DECTA at 40 keV with 50% reduced iodine dose provided higher vascular CT numbers and SNR than SECTA, and almost comparable arterial depiction, but had a degraded intrapelvic arterial depiction and required a larger radiation dose. Advances in knowledge: DECTA enables 50% reduction of iodine dose while maintaining image quality, arterial depiction in almost all arteries, vascular CT numbers, and SNR; however, it does not allow clear visualization of intrapelvic arteries, requiring a slightly larger radiation dose compared with SECTA with standard iodine dose.

This study aimed to develop and validate an automated segmentation method for surface muscles using a three-dimensional (3D) U-Net based on selective voxel patches from whole-body computed tomography (CT) images. Our method defined a voxel patch (VP) as the input images, which consisted of 56 slices selected at equal intervals from the whole slices. In training, one VP was used for each case. In the test, multiple VPs were created according to the number of slices in the test case. Segmentation was then performed for each VP and the results of each VP merged. The proposed method achieved a segmentation accuracy mean dice coefficient of 0.900 for 8 cases. Although challenges remain in muscles adjacent to visceral organs and in small muscle areas, VP is useful for surface muscle segmentation using whole-body CT images with limited annotation data. The limitation of our study is that it is limited to cases of muscular disease with atrophy. Future studies should address whether the proposed method is effective for other modalities or using data with different imaging ranges.