OBJECTIVE: To develop and validate a model for predicting suboptimal debulking surgery (SDS) of serous ovarian carcinoma (SOC) using radiomics method, clinical and MRI features.
METHODS: 228 patients eligible from institution A (randomly divided into the training and internal validation cohorts) and 45 patients from institution B (external validation cohort) were collected and retrospectively analyzed. All patients underwent abdominal pelvic enhanced MRI scan, including T2-weighted imaging fat-suppressed fast spin-echo (T2FSE), T1-weighted dual-echo magnetic resonance imaging (T1DEI), diffusion weighted imaging (DWI), and T1 with contrast enhancement (T1CE). We extracted, selected and eliminated highly correlated radiomic features for each sequence. Then, Radiomic models were made by each single sequence, dual-sequence (T1CE + T2FSE), and all-sequence, respectively. Univariate and multivariate analyses were performed to screen the clinical and MRI independent predictors. The radiomic model with the highest area under the curve (AUC) was used to combine the independent predictors as a combined model.
RESULTS: The optimal radiomic model was based on dual sequences (T2FSE + T1CE) among the five radiomic models (AUC = 0.720, P < 0.05). Serum carbohydrate antigen 125, the relationship between sigmoid colon/rectum and ovarian mass or mass implanted in Douglas\' pouch, diaphragm nodules, and peritoneum/mesentery nodules were considered independent predictors. The AUC of the radiomic-clinical-radiological model was higher than either the optimal radiomic model or the clinical-radiological model in the training cohort (AUC = 0.908 vs. 0.720/0.854).
CONCLUSIONS: The radiomic-clinical-radiological model has an overall algorithm reproducibility and may help create individualized treatment programs and improve the prognosis of patients with SOC.

Inhalation of welding fumes can cause metal accumulation in the brain, leading to Parkinsonian-like symptoms. Metal accumulation and altered neurochemical profiles have been observed using magnetic resonance imaging (MRI) in highly exposed welders, being associated with decreased motor function and cognition. While MRI is impractical to use as a health risk assessment tool in occupational settings, toenail metal levels are easier to assess and have been demonstrated to reflect an exposure window of7-12 months in the past. Yet, it is unclear whether toenail metal levels are associated with brain metal levels or changes in metabolism, which are the root of potential health concerns. This study investigates whether toenail manganese (Mn) and iron (Fe) levels, assessed at several time points, correlate with brain Mn and Fe levels, measured by MRI, as well as brain GABA, glutamate (Glu), and glutathione (GSH) levels, measured by Magnetic Resonance Spectroscopy (MRS), in seventeen Mn-exposed welders. Quantitative T1 and R2* MRI maps of the whole brain, along with GABA, Glu, and GSH MRS measurements from the thalamus and cerebellum were acquired at baseline (T0). Toenail clippings were collected at T0 and every three months after the MRI for a year to account for different exposure periods being reflected by toenail clippings and MRI. Spearman correlations of toenail metal levels were run against brain metal and metabolite levels, but no significant associations were found for Mn at any timepoint. Cerebellar GSH positively correlated with toenail Fe clipped twelve months after the MRI (p = 0.05), suggesting an association with Fe exposure at the time of the MRI. Neither thalamic GABA nor Glu correlated with toenail Fe levels. In conclusion, this study cannot support toenail Mn as a proxy for brain Mn levels or metabolic changes, while toenail Fe appears linked to brain metabolic alterations, underscoring the importance of considering other metals, including Fe, in studying Mn neurotoxicity.

BACKGROUND: This study evaluated a pilot intervention to reduce low-value Magnetic Resonance Imaging (MRI) referrals for Low Back Pain (LBP).
METHODS: This before-after intervention study analysed MRI referrals for LBP at two private imaging centres in Norway. MRI referrals for LBP obtained before and after an intervention of information campaigns and sending a return letter to clinicians for declined referrals were evaluated on information, quality, and justification rates. Four radiologists and two radiographers assessed the referrals. A point system was used to calculate referral quality. Each referral was given a score \'good\' when rated above 5.5 and \'poor\' below 2.5. Justification was based on assessors categorised rating as justified, unjustified or need more information. Stata Statistical Software (Release 18) was used for analysis. A mixed model analysed variations of the referrals pre- and post-intervention. A p-value of <.05 in variations was considered statistically significant.
RESULTS: A total n = 300 patients\' referrals (150 referrals pre- and post-intervention) were collected and assessed. Post-intervention, 68% of referrals were justified, up from 63% pre-intervention. The assessment showed a 4% decrease in referrals with poor scores and a 2% increase in those rated as good or intermediate quality post-intervention. These changes were not statistically significant.
CONCLUSIONS: It is important to state that it was not possible in our study to identify the subgroup of referrals that are known to be from clinicians who had received a return letter, although the information campaign targeted all referrers. Despite the limitations our findings suggest that providing reasons for declined referrals can serve as an educational tool for clinicians and contribute to the reduction of low value MRI for LBP.
CONCLUSIONS: Radiology department initiatives that raise awareness and offer referral criteria guidance to clinicians can serve as valuable educational tools, and further emphasize the importance of providing comprehensive information in MRI referrals for LBP.

OBJECTIVE: To describe ED neuroimaging trends across the time-period spanning the early adoption of endovascular therapy for acute stroke (2013-2018).
METHODS: We performed a retrospective, cross-sectional study of ED visits using the 2013-2018 National Emergency Department Sample, a 20% sample of ED encounters in the United States. Neuroimaging use was determined by Common Procedural Terminology (CPT) code for non-contrast head CT (NCCT), CT angiography head (CTA), CT perfusion (CTP), and MRI brain (MRI) in non-admitted ED patients. Data was analyzed according to sampling weights and imaging rates were calculated per 100,000 ED visits. Multivariate logistic regression analysis was performed to identify hospital-level factors associated with imaging utilization.
RESULTS: Study population comprised 571,935,906 weighted adult ED encounters. Image utilization increased between 2013 and 2018 for all modalities studied, although more pronounced in CTA (80.24/100,000 ED visits to 448.26/100,000 ED visits (p < 0.001)) and CTP (1.75/100,000 ED visits to 28.04/100,000 ED visits p < 0.001)). Regression analysis revealed that teaching hospitals were associated with higher odds of high CTA utilization (OR 1.88 for 2018, p < 0.05), while low-volume EDs and public hospitals showed the reverse (OR 0.39 in 2018, p < 0.05).
CONCLUSIONS: We identified substantial increases in overall neuroimaging use in a national sample of non-admitted emergency department encounters between 2013 and 2018 with variability in utilization according to both patient and hospital properties. Further investigation into the appropriateness of this imaging is required to ensure that access to acute stroke treatment is balanced against the timing and cost of over-imaging.

OBJECTIVE: The accurate and timely assessment of the collateral perfusion status is crucial in the diagnosis and treatment of patients with acute ischemic stroke. Previous works have shown that collateral imaging, derived from CT angiography, MR perfusion, and MR angiography, aids in evaluating the collateral status. However, such methods are time-consuming and/or sub-optimal due to the nature of manual processing and heuristics. Recently, deep learning approaches have shown to be promising for generating collateral imaging. These, however, suffer from the computational complexity and cost.
METHODS: In this study, we propose a mobile, lightweight deep regression neural network for collateral imaging in acute ischemic stroke, leveraging dynamic susceptibility contrast MR perfusion (DSC-MRP). Built based upon lightweight convolution and Transformer architectures, the proposed model manages the balance between the model complexity and performance.
RESULTS: We evaluated the performance of the proposed model in generating the five-phase collateral maps, including arterial, capillary, early venous, late venous, and delayed phases, using DSC-MRP from 952 patients. In comparison with various deep learning models, the proposed method was superior to the competitors with similar complexity and was comparable to the competitors of high complexity.
CONCLUSIONS: The results suggest that the proposed model is able to facilitate rapid and precise assessment of the collateral status of patients with acute ischemic stroke, leading to improved patient care and outcome.

OBJECTIVE: Deep learning has firmly established its dominance in medical imaging applications. However, careful consideration must be exercised when transitioning a trained source model to adapt to an entirely distinct environment that deviates significantly from the training set. The majority of the efforts to mitigate this issue have predominantly focused on classification and segmentation tasks. In this work, we perform a domain adaptation of a trained source model to reconstruct high-resolution intervertebral disc meshes from low-resolution MRI.
METHODS: To address the outlined challenges, we use MRI2Mesh as the shape reconstruction network. It incorporates three major modules: image encoder, mesh deformation, and cross-level feature fusion. This feature fusion module is used to encapsulate local and global disc features. We evaluate two major domain adaptation techniques: adaptive batch normalization (AdaBN) and adaptive instance normalization (AdaIN) for the task of shape reconstruction.
RESULTS: Experiments conducted on distinct datasets, including data from different populations, machines, and test sites demonstrate the effectiveness of MRI2Mesh for domain adaptation. MRI2Mesh achieved up to a 14% decrease in Hausdorff distance (HD) and a 19% decrease in the point-to-surface (P2S) metric for both AdaBN and AdaIN experiments, indicating improved performance.
CONCLUSIONS: MRI2Mesh has demonstrated consistent superiority to the state-of-the-art Voxel2Mesh network across a diverse range of datasets, populations, and scanning protocols, highlighting its versatility. Additionally, AdaBN has emerged as a robust method compared to the AdaIN technique. Further experiments show that MRI2Mesh, when combined with AdaBN, holds immense promise for enhancing the precision of anatomical shape reconstruction in domain adaptation.

Assessing the extent of the intramedullary lesion after spinal cord injury (SCI) might help to improve prognostication. However, since the neurological level of injury (NLI) impacts the recovery potential of SCI patients, the question arises whether lesion size parameters and predictive models based on those parameters are affected as well. In this retrospective observational study, the extent of the intramedullary lesion between individuals who sustained cervical and thoracolumbar SCI was compared and its relation to clinical recovery was assessed. 154 patients with sub-acute SCI (89 individuals with cervical lesions and 65 individuals with thoracolumbar lesions) underwent conventional clinical magnetic resonance imaging (MRI) 1 month after injury and clinical examination at 1 and 12 months. The morphology of the focal lesion within the spinal cord was manually assessed on the midsagittal slice of T2-weighted MR images and compared between cervical and thoracolumbar SCI patients as well as between patients who improved at least one American Spinal Injury Association Impairment Scale (AIS) grade (converters) and patients without AIS grade improvement (non-converters). The predictive value of lesion parameters including lesion length, lesion width, and preserved tissue bridges for predicting AIS grade conversion was assessed using regression models (conditional inference tree analysis). Lesion length was two times longer in thoracolumbar compared to cervical SCI patients (F = 39.48, p < 0.0001), while lesion width and tissue bridges\' width did not differ. When comparing AIS grade converters and non-converters, converters showed a smaller lesion length (F = 5.46, p = 0.021), a smaller lesion width (F = 13.75, p = 0.0003) and greater tissue bridges (F = 12.87, p = 0.0005). Using regression models, tissue bridges allowed more refined subgrouping of the heterogenous patient population according to individual recovery profiles between 1 month and 12 months after SCI, while lesion length added no additional information for further subgrouping. This study characterizes differences in the anteroposterior and craniocaudal lesion extent after SCI. The two times greater lesion length in thoracolumbar compared to cervical SCI might be related to differences in the anatomy, biomechanics, and perfusion between the cervical and thoracic spine. Preserved tissue bridges were less influenced by the lesion level, while closely related to the clinical impairment. These results highlight the robustness and utility of tissue bridges as a neuroimaging biomarker for predicting clinical outcome after SCI in heterogeneous patient populations and for patient stratification in clinical trials.

UNASSIGNED: Cervical foraminal stenosis on MRI may be assessed using the Kim, modified Kim or Siller methods. This study aimed to investigate which morphological features of cervical foraminal stenosis in patients with cervical radiculopathy correlated best with pre-operative and post-operative surgical outcome following Anterior Cervical Discectomy (ACD) or a Posterior Cervical Foraminotomy (PCF).
UNASSIGNED: Pre-operative MRIs of adults with cervical radiculopathy were assessed by six raters. The following measurements were made; uncompressed nerve root diameter, maximal compressed nerve root diameter, anterior & posterior compression, length of the neuroforaminal canal where the diameter was less than the uncompressed nerve root diameter and the distance of maximum compression from the apex of the ligamentum flavum. The Kim, modified Kim and Siller grades were calculated. Neck Disability Index (NDI) was measured pre-operatively and six weeks post-operatively. The radiological measurements and grades were compared to the pre-operative and change in NDI.
UNASSIGNED: Mean NDI was higher in female (58.2) than male patients (45.6) p = 0.05. No other baseline, operative or radiological factors where significantly associated with the pre-operative NDI. The mean [±SD] post-operative NDI was 14.3 [±22.5]. This represents a change of 37.8 (p < 0.001). The pre-operative NDI correlated strongly with the post-operative NDI but no other patient, operation or radiological factors correlated significantly. Neither pre-operative NDI or change in NDI was statistically different in those treated with ACD and those treated with PCF.
UNASSIGNED: There was no association between pre-operative NDI and any of the radiological measurements or radiological grades. Furthermore, whilst surgery significantly improved NDI, for those patients with anterior compression, there was no difference in outcome between those treated with an ACD and those treated with a PCF. Current axial MRIs do not adequately assess the cervical nerve root foramina or predict surgical approach, 3D isotropic acquisition and DTI should be explored.

OBJECTIVE: Glioblastomas (GBM) are the most common primary invasive neoplasms of the brain. Distinguishing between lesion recurrence and different types of treatment related changes in patients with GBM remains challenging using conventional MRI imaging techniques. Therefore, accurate and precise differentiation between true progression or pseudoresponse is crucial in deciding on the appropriate course of treatment. This retrospective study investigated the potential of apparent diffusion coefficient (ADC) map values derived from diffusion-weighted imaging (DWI) as a noninvasive method to increase diagnostic accuracy in treatment response.
METHODS: A cohort of 21 glioblastoma patients (mean age: 59.2 ± 11.8, 12 Male, 9 Female) that underwent treatment with bevacizumab were selected. The ADC values were calculated from the DWI images obtained from a standardized brain protocol across 1.5-T and 3-T MRI scanners. Ratios were calculated for rADC values. Lesions were classified as bevacizumab-induced cytotoxicity based on characteristic imaging features (well-defined regions of restricted diffusion with persistent diffusion restriction over the course of weeks without tissue volume loss and absence of contrast enhancement). The rADC value was compared to these values in radiation necrosis and recurrent lesions, which were concluded in our prior study. The nonparametric Wilcoxon signed rank test with p < 0.05 was used for significance.
RESULTS: The mean ± SD age of the selected patients was 59.2 ± 11.8. ADC values and corresponding mean rADC values for bevacizumab-induced cytotoxicity were 248.1 ± 67.2 and 0.39 ± 0.10, respectively. These results were compared to the ADC values and corresponding mean rADC values of tumor progression and radiation necrosis. Significant differences between rADC values were observed in all three groups (p < 0.001). Bevacizumab-induced cytotoxicity had statistically significant lower ADC values compared to both tumor recurrence and radiation necrosis.
CONCLUSIONS: The study demonstrates the potential of ADC values as noninvasive imaging biomarkers for differentiating recurrent glioblastoma from radiation necrosis and bevacizumab-induced cytotoxicity.

OBJECTIVE: Simultaneous positron emission tomography/magnetic resonance imaging (PET-MRI) combines the high sensitivity of PET with the high specificity of MRI and is a tool for the assessment of gastroenteropancreatic neuroendocrine neoplasms (G-NENs). However, it remains poorly evaluated with no clear recommendations in current guidelines. Thus, we evaluated the prognostic impact of PET-MRI in G-NEN patients.
METHODS: From June 2017 to December 2021, 71 G-NEN patients underwent whole-body PET-MRI for staging and/or follow-up purposes. A whole-body emission scan with 18F-6-fluoro-L-dihydroxyphenylalanine (18FDOPA, n = 30), 18F-fluoro-2-deoxy-D-glucose (18FDG, n = 21), or 68Ga-(DOTA(0)-Phe(1)-Tyr(3))-octreotide (68Ga-DOTATOC, n = 20) with the simultaneous acquisition of a T1-Dixon sequence and diffusion-weighed imaging (DWI), followed by a dedicated step of MRI sequences with a Gadolinium contrast was performed. The patients underwent PET-MRI every 6-12 months during the follow-up period until death. Over this period, 50 patients with two or more PET-MRI were evaluated.
RESULTS: The mean age was 61 [extremes, 31-92] years. At the baseline, PET-MRI provided new information in 12 cases (17%) as compared to conventional imaging: there were more metastases in eight, an undescribed location (myocardia) in two, and an unknown primary location in two cases. G grading at the baseline influenced overall survival. During the follow-up (7-381 months, mean 194), clinical and therapy managements were influenced by PET-MRI in three (6%) patients due to new metastases findings when neither overall, nor disease-free survivals in these two subgroups (n = 12 vs. n = 59), were different.
CONCLUSIONS: Our study suggests that using PET/MRI with the appropriate radiotracer improves the diagnostic performance with no benefit on survival. Further studies are warranted to evaluate the cost-effectiveness of this procedure.