Faster acquisition of magnetic resonance imaging sequences of the knee via deep learning reconstruction: a volunteer study.

AIM: To evaluate whether deep learning reconstruction (DLR) can accelerate the acquisition of magnetic resonance imaging (MRI) sequences of the knee for clinical use. MATERIALS AND METHODS: Using a 1.5-T MRI scanner, sagittal fat-suppressed T2-weighted imaging (fs-T2WI), coronal proton density-weighted imaging (PDWI), and coronal T1-weighted imaging (T1WI) were performed. DLR was applied to images with a number of signal averages (NSA) of 1 to obtain 1DLR images. Then 1NSA, 1DLR, and 4NSA images were compared subjectively, and by noise (standard deviation of intra-articular water or medial meniscus) and contrast-to-noise ratio between two anatomical structures or between an anatomical structure and intra-articular water. RESULTS: Twenty-seven healthy volunteers (age: 40.6 ± 11.9 years) were enrolled. Three 1DLR image sequences were obtained within 200 s (approximately 12 minutes for 4NSA image). According to objective evaluations, PDWI 1DLR images showed the smallest noise and significantly higher contrast than 1NSA and 4NSA images. For fs-T2WI, smaller noise and higher contrast were observed in the order of 4NSA, 1DLR, and 1NSA images. According to the subjective analysis, structure visibility, image noise, and overall image quality were significantly better for PDWI 1DLR than 1NSA images; moreover, the visibility of the meniscus and bone, image noise, and overall image quality were significantly better for 1DLR than 4NSA images. Fs-T2WI and T1WI 1DLR images showed no difference between 1DLR and 4NSA images. CONCLUSION: Compared to PDWI 4NSA images, PDWI 1DLR images were of higher quality, while the quality of fs-T2WI and T1WI 1DLR images was similar to that of 4NSA images.

Impact of deep learning on radiologists and radiology residents in detecting breast cancer on CT: a cross-vendor test study.

AIM: To investigate the effect of deep learning on the diagnostic performance of radiologists and radiology residents in detecting breast cancers on computed tomography (CT). MATERIALS AND METHODS: In this retrospective study, patients undergoing contrast-enhanced chest CT between January 2010 and December 2020 using equipment from two vendors were included. Patients with confirmed breast cancer were categorised as the training (n=201) and validation (n=26) group and the testing group (n=30) using processed CT images from either vendor. The trained deep-learning model was applied to test group patients with (30 females; mean age = 59.2 ± 15.8 years) and without (19 males, 21 females; mean age = 64 ± 15.9 years) breast cancer. Image-based diagnostic performance of the deep-learning model was evaluated with the area under the receiver operating characteristic curve (AUC). Two radiologists and three radiology residents were asked to detect malignant lesions by recording a four-point diagnostic confidence score before and after referring to the result from the deep-learning model, and their diagnostic performance was evaluated using jackknife alternative free-response receiver operating characteristic analysis by calculating the figure of merit (FOM). RESULTS: The AUCs of the trained deep-learning model on the validation and test data were 0.976 and 0.967, respectively. After referencing with the result of the deep learning model, the FOMs of readers significantly improved (reader 1/2/3/4/5: from 0.933/0.962/0.883/0.944/0.867 to 0.958/0.968/0.917/0.947/0.900; p=0.038). CONCLUSION: Deep learning can help radiologists and radiology residents detect breast cancer on CT.

Cosmetic surgery procedures accessed by Nigerian women at a single private cosmetic surgery practice: A retrospective review.

Background: Little is known about the cosmetic surgery procedures sought by Nigerian women. Aim: We sought to report the proportion of cosmetic surgery procedures accessed by Nigerian women and determine any associations between the demographics and cosmetic procedures accessed. Patients and Methods: A retrospective review was conducted between January 2020 and July 2021 of all cosmetic surgery procedures at a single private cosmetic surgery practice. Data were analyzed using means, Mann-Whitney U-test, chi square test, and Fisher's exact test as appropriate. The statistical significance was set at P ≤ 0.05. Results: Of the 392 consultations for cosmetic procedures, 245 (62.5%) patients accessed cosmetic surgery. Most were women (239 (97.6%)) and single (178 (72.7%)). The median age of the patients at surgery was 29.0 years (IQR 26-33), the median weight was 78.8 kg (IQR 71.4-88.8), and the median body mass index (BMI) was 28.1 (IQR 25.7-32.3). Liposuction was the procedure accessed by nearly all the patients (224 (91.4%)). Next to this was bilateral buttock augmentation (199 (81.2%)). Other cosmetic procedures such as tummy tuck, facial cosmetic surgery, umbilicoplasty, and labiaplasty each constituted less than three percent of the patients. The abdomen (224 (91.4%)), back (219 (89.4%)), and arms (79 (32.2%)) were the most common regions of the body sought for liposuction, while the calves (2 (0.8%)) were the least. Liposuction of the arms was associated with the BMI (p < 0.003). Conclusion: Liposuction and bilateral buttock augmentation are the most common cosmetic surgery procedures accessed by this cohort of Nigerian women.

Usefulness of deep learning-based noise reduction for 1.5 T MRI brain images.

AIM: To evaluate 1.5 T magnetic resonance imaging (MRI) brain images with denoising procedures using deep learning-based reconstruction (dDLR) relative to the original 1.5 and 3 T images. MATERIALS AND METHODS: Eleven volunteers underwent MRI at 3 and 1.5 T. Two-dimensional fast spin-echo T2-weighted imaging (T2WI), fluid-attenuated inversion recovery (FLAIR) imaging and diffusion-weighted imaging (DWI) sequences were performed. The dDLR method was applied to the 1.5 T data (dDLR-1.5 T), then the image quality of the dDLR-1.5 T data relative to the original 1.5 T and 3 T data was qualitatively and quantitatively assessed based on the structure similarity (SSIM) index; the signal-to-noise ratios (SNRs) of the grey matter (GM) and white matter (WM); and the contrast-to-noise ratios (CNRs) between the GM and WM (CNRgm-wm) and between the striatum (ST) and WM (CNRst-wm). RESULTS: The perceived image quality, and SNRs and CNRs were significantly higher for the dDLR-1.5 T images versus the 1.5 T images for all sequences and almost comparable or even superior to those of the 3 T images. For DWI, the SNRs and CNRst-wm were significantly higher for the dDLR-1.5 T images versus the 3 T images. CONCLUSION: The dDLR technique improved the image quality of 1.5 T brain MRI images. With respect to qualitative and quantitative measurements, the denoised 1.5 T brain images were almost equivalent or even superior to the 3 T brain images.

Alcohol abuse has a potential association with unfavourable clinical course and brain atrophy in patients with status epilepticus.

AIM: To evaluate chronological changes on serial magnetic resonance imaging (MRI) examinations and clinical prognosis in patients with status epilepticus (SE), as well as the effect of alcohol abuse and heavy alcohol use on clinicoradiological findings. MATERIALS AND METHODS: This retrospective, single-centre study was approved by the institutional review board. Among 345 patients with seizures between January 2010 and October 2021, 27 patients with SE who had undergone both initial MRI (within a week after onset) and follow-up MRI (within 1 month after the initial MRI) were included. Five and three patients with concurrent or previous alcohol abuse and heavy alcohol-use history were included, respectively, and they were classified into the AL (Alcohol use) group. The remaining 19 patients were classified into the non-AL group. Two neuroradiologists independently evaluated both initial and follow-up MRI examinations of each patient; MRI findings were compared between the AL and non-AL groups using Fisher's exact test. In 15 patients, including four patients from the AL group, clinical information 6 months after the onset of SE was available; this information was compared between the two groups. RESULTS: Brain atrophy (5/8 versus 2/19, p=0.011; odds ratio, 12.29 [95% confidence interval, 1.32-189.2]) and unfavourable clinical course with uncontrollable seizures (3/4 versus 1/11, p=0.033; odds ratio, 30[1.43-638.19]) were significantly more frequent in the AL group than in the non-AL group. CONCLUSION: Among patients with SE, alcohol abuse and heavy alcohol-use history were associated with unfavourable seizure control and brain atrophy.

3D Quantitative Synthetic MRI in the Evaluation of Multiple Sclerosis Lesions.

BACKGROUND AND PURPOSE: Synthetic MR imaging creates multiple contrast-weighted images based on a single time-efficient quantitative scan, which has been mostly performed for 2D acquisition. We assessed the utility of 3D synthetic MR imaging in patients with MS by comparing its diagnostic image quality and lesion volumetry with conventional MR imaging. MATERIALS AND METHODS: Twenty-four patients with MS prospectively underwent 3D quantitative synthetic MR imaging and conventional T1-weighted, T2-weighted, FLAIR, and double inversion recovery imaging, with acquisition times of 9 minutes 3 seconds and 18 minutes 27 seconds for the synthetic MR imaging and conventional MR imaging sequences, respectively. Synthetic phase-sensitive inversion recovery images and those corresponding to conventional MR imaging contrasts were created for synthetic MR imaging. Two neuroradiologists independently assessed the image quality on a 5-point Likert scale. The numbers of cortical lesions and lesion volumes were quantified using both synthetic and conventional image sets. RESULTS: The overall diagnostic image quality of synthetic T1WI and double inversion recovery images was noninferior to that of conventional images (P = .23 and .20, respectively), whereas that of synthetic T2WI and FLAIR was inferior to that of conventional images (both Ps < .001). There were no significant differences in the number of cortical lesions (P = .17 and .53 for each rater) or segmented lesion volumes (P = .61) between the synthetic and conventional image sets. CONCLUSIONS: Three-dimensional synthetic MR imaging could serve as an alternative to conventional MR imaging in evaluating MS with a reduced scan time.

MRI Findings of Immune Checkpoint Inhibitor-Induced Hypophysitis: Possible Association with Fibrosis.

BACKGROUND AND PURPOSE: Hypophysitis is one of the well-known adverse effects of immune checkpoint inhibitors. Immune checkpoint inhibitor-induced hypophysitis frequently causes irreversible hypopituitarism, which requires long-term hormone replacement. Despite the high frequency and clinical significance, characteristic MR imaging findings of immune checkpoint inhibitor-induced hypophysitis have not been established. In the present study, we aimed to review and extract the MR imaging features of immune checkpoint inhibitor-induced hypophysitis. MATERIALS AND METHODS: This retrospective international multicenter study comprised 20 patients with melanoma who were being treated with immune checkpoint inhibitors and clinically diagnosed with immune checkpoint inhibitor-induced hypophysitis. Three radiologists evaluated the following MR imaging findings: enlargement of the pituitary gland and stalk; homogeneity of enhancement of the pituitary gland; presence/absence of a well-defined poorly enhanced area and, if present, its location, shape, and signal intensity in T2WI; and enhancement pattern in contrast-enhanced dynamic MR imaging. Clinical symptoms and hormone levels were also recorded. RESULTS: Enlargement of the pituitary gland and stalk was observed in 12 and 20 patients, respectively. Nineteen patients showed poorly enhanced lesions (geographic hypoenhancing lesions) in the anterior lobe, and 11 of these lesions showed hypointensity on T2WI. Thyrotropin deficiency and corticotropin deficiency were observed in 19/20 and 12/17 patients, respectively, which persisted in 12/19 and 10/12 patients, respectively, throughout the study period. CONCLUSIONS: Pituitary geographic hypoenhancing lesions in the anterior lobe of the pituitary gland are characteristic and frequent MR imaging findings of immune checkpoint inhibitor-induced hypophysitis. They reflect fibrosis and are useful in distinguishing immune checkpoint inhibitor-induced hypophysitis from other types of hypophysitis/tumors.

Utility of computed tomography and 18 F-fluorodeoxyglucose with positron emission tomography/computed tomography for distinguishing appendiceal mucocele caused by mucinous adenocarcinoma from other pathologies.

AIM: Differentiating appendiceal mucocele with mucinous adenocarcinoma from other pathologies before surgery is difficult. The objective of this study was to evaluate the utility of CT and 18 F-fluorodeoxyglucose (FDG) with positron emission tomography (PET)/CT for differentiating mucinous adenocarcinoma of appendiceal mucocele from other pathologies. METHOD: The study included 25 patients who underwent surgery for clinically diagnosed appendiceal mucoceles detected on CT at the University of Tokyo Hospital. Among these patients, 19 underwent FDG-PET/CT preoperatively. We compared features of the CT imaging findings and maximum standard uptake values (SUVmax ) detected by FDG-PET/CT between mucocele with mucinous adenocarcinoma and other pathologies. RESULTS: A total of 13 men (52%) and 12 women (48%) were included in this study, with a median age of 65 years (range 34-83). There were six patients (24%) with pathologically confirmed mucinous adenocarcinoma, 15 patients (60%) with appendiceal mucinous neoplasm and four patients (16%) with simple mucocele caused by chronic inflammation. On the CT findings, wall irregularity was the only significant feature for the two groups in this study (83.3% vs 0.0%, P < 0.01). There was a significant difference in the SUVmax levels on PET/CT between the two groups (100.0% vs 20.0%, P < 0.01). CONCLUSION: Distinguishing between mucocele with mucinous adenocarcinoma and other pathologies using imaging modalities is challenging. Our results suggest that wall irregularity on CT and elevated SUVmax on PET/CT are useful factors that can be employed for such discrimination.

White Matter Abnormalities in Multiple Sclerosis Evaluated by Quantitative Synthetic MRI, Diffusion Tensor Imaging, and Neurite Orientation Dispersion and Density Imaging.

BACKGROUND AND PURPOSE: A number of MR-derived quantitative metrics have been suggested to assess the pathophysiology of MS, but the reports about combined analyses of these metrics are scarce. Our aim was to assess the spatial distribution of parameters for white matter myelin and axon integrity in patients with relapsing-remitting MS by multiparametric MR imaging. MATERIALS AND METHODS: Twenty-four patients with relapsing-remitting MS and 24 age- and sex-matched controls were prospectively scanned by quantitative synthetic and 2-shell diffusion MR imaging. Synthetic MR imaging data were used to retrieve relaxometry parameters (R1 and R2 relaxation rates and proton density) and myelin volume fraction. Diffusion tensor metrics (fractional anisotropy and mean, axial, and radial diffusivity) and neurite orientation and dispersion index metrics (intracellular volume fraction, isotropic volume fraction, and orientation dispersion index) were retrieved from diffusion MR imaging data. These data were analyzed using Tract-Based Spatial Statistics. RESULTS: Patients with MS showed significantly lower fractional anisotropy and myelin volume fraction and higher isotropic volume fraction in widespread white matter areas. Areas with different isotropic volume fractions were included within areas with lower fractional anisotropy. Myelin volume fraction showed no significant difference in some areas with significantly decreased fractional anisotropy in MS, including in the genu of the corpus callosum and bilateral anterior corona radiata, whereas myelin volume fraction was significantly decreased in some areas where fractional anisotropy showed no significant difference, including the bilateral posterior limb of the internal capsule, external capsule, sagittal striatum, fornix, and uncinate fasciculus. CONCLUSIONS: We found differences in spatial distribution of abnormality in fractional anisotropy, isotropic volume fraction, and myelin volume fraction distribution in MS, which might be useful for characterizing white matter in patients with MS.