The Use of Artificial Intelligence in Head and Neck Cancers: A Multidisciplinary Survey.

Artificial intelligence (AI) approaches have been introduced in various disciplines but remain rather unused in head and neck (H&N) cancers. This survey aimed to infer the current applications of and attitudes toward AI in the multidisciplinary care of H&N cancers. From November 2020 to June 2022, a web-based questionnaire examining the relationship between AI usage and professionals' demographics and attitudes was delivered to different professionals involved in H&N cancers through social media and mailing lists. A total of 139 professionals completed the questionnaire. Only 49.7% of the respondents reported having experience with AI. The most frequent AI users were radiologists (66.2%). Significant predictors of AI use were primary specialty (V = 0.455; p < 0.001), academic qualification and age. AI's potential was seen in the improvement of diagnostic accuracy (72%), surgical planning (64.7%), treatment selection (57.6%), risk assessment (50.4%) and the prediction of complications (45.3%). Among participants, 42.7% had significant concerns over AI use, with the most frequent being the 'loss of control' (27.6%) and 'diagnostic errors' (57.0%). This survey reveals limited engagement with AI in multidisciplinary H&N cancer care, highlighting the need for broader implementation and further studies to explore its acceptance and benefits.

Deep Learning Accelerated Brain Diffusion-Weighted MRI with Super Resolution Processing.

OBJECTIVES: To investigate the clinical feasibility and image quality of accelerated brain diffusion-weighted imaging (DWI) with deep learning image reconstruction and super resolution. METHODS: 85 consecutive patients with clinically indicated MRI at a 3 T scanner were prospectively included. Conventional diffusion-weighted data (c-DWI) with four averages were obtained. Reconstructions of one and two averages, as well as deep learning diffusion-weighted imaging (DL-DWI), were accomplished. Three experienced readers evaluated the acquired data using a 5-point Likert scale regarding overall image quality, overall contrast, diagnostic confidence, occurrence of artefacts and evaluation of the central region, basal ganglia, brainstem, and cerebellum. To assess interrater agreement, Fleiss' kappa (Ï°) was determined. Signal intensity (SI) levels for basal ganglia and the central region were estimated via automated segmentation, and SI values of detected pathologies were measured. RESULTS: Intracranial pathologies were identified in 35 patients. DL-DWI was significantly superior for all defined parameters, independently from applied averages (p-value <0.001). Optimum image quality was achieved with DL-DWI by utilizing a single average (p-value <0.001), demonstrating very good (80.9%) to excellent image quality (14.5%) in nearly all cases, compared to 12.5% with very good and 0% with excellent image quality for c-MRI (p-value <0.001). Comparable results could be shown for diagnostic confidence. Inter-rater Fleiss' Kappa demonstrated moderate to substantial agreement for virtually all defined parameters, with good accordance, particularly for the assessment of pathologies (p = 0.74). Regarding SI values, no significant difference was found. CONCLUSION: Ultra-fast diffusion-weighted imaging with super resolution is feasible, resulting in highly accelerated brain imaging while increasing diagnostic image quality.

Fast 5-minute shoulder MRI protocol with accelerated TSE-sequences and deep learning image reconstruction for the assessment of shoulder pain at 1.5 and 3 Tesla.

Purpose: The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to compare the image quality and diagnostic performance to that of a standard 2D TSE protocol. Methods: Patients undergoing shoulder MRI between October 2020 and June 2021 were prospectively enrolled. Each patient underwent two MRI examinations: first a standard, fully sampled TSE (TSES) protocol reconstructed with a standard reconstruction followed by a second fast, prospectively undersampled TSE protocol with a conventional parallel imaging undersampling pattern reconstructed with a DL reconstruction (TSEDL). Image quality and visualization of anatomic structures as well as diagnostic performance with respect to shoulder lesions were assessed using a 5-point Likert-scale (5 = best). Interchangeability analysis, Wilcoxon signed-rank test and kappa statistics were performed to compare the two protocols. Results: A total of 30 participants was included (mean age 50±15 years; 15 men). Overall image quality was evaluated to be superior in TSEDL versus TSES (p<0.001). Noise and edge sharpness were evaluated to be significantly superior in TSEDL versus TSES (noise: p<0.001, edge sharpness: p<0.05). No difference was found concerning qualitative diagnostic confidence, assessability of anatomical structures (p>0.05), and quantitative diagnostic performance for shoulder lesions when comparing the two sequences. Conclusions: A fast 5-minute TSEDL MRI protocol of the shoulder is feasible in routine clinical practice at 1.5 and 3 T, with interchangeable results concerning the diagnostic performance, allowing a reduction in scan time of more than 50% compared to the standard TSES protocol.

Sex-specific Impact of the first COVID-19 Lockdown on Age Structure and Case Acuity at Admission in a Patient Population in southwestern Germany: a retrospective comparative Study in Neuroradiology.

OBJECTIVES: A hard lockdown was presumed to lead to delayed diagnosis and treatment of serious diseases, resulting in higher acuity at admission. This should be elaborated based on the estimated acuity of the cases, changes in findings during hospitalisation, age structure and biological sex. DESIGN: Retrospective monocentric cross-sectional study. SETTING: German Neuroradiology Department at a . PARTICIPANTS: In 2019, n=1158 patients were admitted in contrast to n=884 during the first hard lockdown in 2020 (11th-13th week). MAIN OUTCOME MEASURES: Three radiologists evaluated the initial case acuity, classified them into three groups (not acute, subacute and acute), and evaluated if there was a relevant clinical deterioration. The data analysis was conducted using non-parametric methods and multivariate regression analysis. RESULTS: A 24% decrease in the number of examinations from 2019 to 2020 (p=0.025) was revealed. In women, the case acuity increased by 21% during the lockdown period (p=0.002). A 30% decrease in acute cases in men was observable (in women 5% decrease). Not acute cases decreased in both women and men (47%; 24%), while the subacute cases remained stable in men (0%) and decreased in women (28%). Regression analysis revealed the higher the age, the higher the acuity (p<0.001 in both sexes), particularly among women admitted during the lockdown period (p=0.006). CONCLUSION: The lockdown led to a decrease in neuroradiological consultations, with delays in seeking medical care. In women, the number of most severe cases remained stable, whereas the mean case acuity and age increased. This could be due to greater pandemic-related anxiety among women, however, with severe symptoms they were seeking for medical help. In contrast in men, the absolute number of most severe cases decreased, whereas the mean acuity and age remained nearly unaffected. This could be attributable to a reduced willingness to seek for medical consultation.

Ultrafast Brain MRI with Deep Learning Reconstruction for Suspected Acute Ischemic Stroke.

Background Deep learning (DL)-accelerated MRI can substantially reduce examination times. However, studies prospectively evaluating the diagnostic performance of DL-accelerated MRI reconstructions in acute suspected stroke are lacking. Purpose To investigate the interchangeability of DL-accelerated MRI with conventional MRI in patients with suspected acute ischemic stroke at 1.5 T. Materials and Methods In this prospective study, 211 participants with suspected acute stroke underwent clinically indicated MRI at 1.5 T between June 2022 and March 2023. For each participant, conventional MRI (including T1-weighted, T2-weighted, T2*-weighted, T2 fluid-attenuated inversion-recovery, and diffusion-weighted imaging; 14 minutes 18 seconds) and DL-accelerated MRI (same sequences; 3 minutes 4 seconds) were performed. The primary end point was the interchangeability between conventional and DL-accelerated MRI for acute ischemic infarction detection. Secondary end points were interchangeability regarding the affected vascular territory and clinically relevant secondary findings (eg, microbleeds, neoplasm). Three readers evaluated the overall occurrence of acute ischemic stroke, affected vascular territory, clinically relevant secondary findings, overall image quality, and diagnostic confidence. For acute ischemic lesions, size and signal intensities were assessed. The margin for interchangeability was chosen as 5%. For interrater agreement analysis and interrater reliability analysis, multirater Fleiss κ and the intraclass correlation coefficient, respectively, was determined. Results The study sample consisted of 211 participants (mean age, 65 years ± 16 [SD]); 123 male and 88 female). Acute ischemic stroke was confirmed in 79 participants. Interchangeability was demonstrated for all primary and secondary end points. No individual equivalence indexes (IEIs) exceeded the interchangeability margin of 5% (IEI, -0.002 [90% CI: -0.007, 0.004]). Almost perfect interrater agreement was observed (P > .91). DL-accelerated MRI provided higher overall image quality (P < .001) and diagnostic confidence (P < .001). The signal properties of acute ischemic infarctions were similar in both techniques and demonstrated good to excellent interrater reliability (intraclass correlation coefficient, ≥0.8). Conclusion Despite being four times faster, DL-accelerated brain MRI was interchangeable with conventional MRI for acute ischemic lesion detection. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Haller in this issue.

Pre-treatment 18F-FDG-PET/CT parameters as biomarkers for progression free survival, best overall response and overall survival in metastatic melanoma patients undergoing first-line immunotherapy.

BACKGROUND: Checkpoint inhibitors have drastically improved the therapy of patients with advanced melanoma. 18F-FDG-PET/CT parameters might act as biomarkers for response and survival and thus can identify patients that do not benefit from immunotherapy. However, little literature exists on the association of baseline 18F-FDG-PET/CT parameters with progression free survival (PFS), best overall response (BOR), and overall survival (OS). MATERIALS AND METHODS: Using a whole tumor volume segmentation approach, we investigated in a retrospective registry study (n = 50) whether pre-treatment 18F-FDG-PET/CT parameters of three subgroups (tumor burden, tumor glucose uptake and non-tumoral hematopoietic tissue metabolism), can act as biomarkers for the primary endpoints PFS and BOR as well as for the secondary endpoint OS. RESULTS: Compared to the sole use of clinical parameters, baseline 18F-FDG-PET/CT parameters did not significantly improve a Cox proportional-hazard model for PFS (C-index/AIC: 0.70/225.17 and 0.68/223.54, respectively; p = 0.14). A binomial logistic regression analysis for BOR was not statistically significant (χ2(15) = 16.44, p = 0.35), with a low amount of explained variance (Nagelkerke's R2 = 0.38). Mean FDG uptake of the spleen contributed significantly to a Cox proportional-hazard model for OS (HR 3.55, p = 0.04). CONCLUSIONS: The present study could not confirm the capability of the pre-treatment 18F-FDG-PET/CT parameters tumor burden, tumor glucose uptake and non-tumoral hematopoietic tissue metabolism to act as biomarkers for PFS and BOR in metastatic melanoma patients receiving first-line immunotherapy. The documented potential of 18F-FDG uptake by immune-mediating tissues such as the spleen to act as a biomarker for OS has been reproduced.

Gender differences in self-assessed performance and stress level during training of basic interventional radiology maneuvers.

OBJECTIVES: Gender differences have been reported to influence medical training. We investigated gender differences encountered during training in interventional radiology maneuvers. METHODS: Catheter handling was analyzed under standardized conditions in 64 participants naïve to endovascular procedures (26 women, 38 men). Objective (e.g., catheter pathway, catheter movements, required time) and subjective parameters (stress level) were recorded. The NASA-Task Load Index (NASA-TLX; 1-20 points) was used to assess participants' stress levels and perceived workload. RESULTS: In the easier tasks, no significant differences between male and female participants regarding catheter handling were observed. In the most complex task, female participants took themselves more time (688 ± 363 vs. 501 ± 230 s; p = 0.02), asked for help more frequently (n = 19 vs. n = 8) and earlier than men (203 ± 94 vs. 305 ± 142 s; p = 0.049), whereas men stood out by more agitated catheter handling (6.0 ± 1.8 vs. 4.8 ± 1.6 movements/s; p = 0.005). Overall, female participants perceived tasks to be more difficult (11.5 ± 4.2 vs. 9.6 ± 3.3; p = 0.016), perceived higher stress levels (8.9 ± 4.9 vs. 6.3 ± 4.4; p = 0.037), and rated their own performance lower (9.12 ± 3.3 vs. 11.3 ± 3.3; p = 0.009). However, female participants were able to correlate self-assessed with objective parameters correctly (r between -0.555 and -0.469; p = 0.004-0.018), whereas male participants failed to correctly rate their performance (p between 0.34 and 0.73). Stress levels correlated with objective parameters in males (r between 0.4 and 0.587; p < 0.005), but not in female participants. CONCLUSION: Perceived stress levels, self-evaluation skills, and catheter handling differ greatly between untrained male and female participants trying to solve interventional radiological tasks. These gender-specific differences should be considered in interventional radiology training. CLINICAL RELEVANCE STATEMENT: As psychological aspects may influence individual working strategies gender-specific differences in self-perception while learning interventional radiology maneuvers could be essential regarding success in teaching and treatment outcomes. KEY POINTS: • After performing standardized training, 38 male and 26 female volunteers showed significant differences regarding objective and self-assessed performance, as well as in perceived workload while performing simulated endovascular catheter maneuvers. • After solving simulated endovascular radiological tasks, female participants were able to self-assess their objective performance much more accurately than male participants. • Women took more time to solve simulated endovascular tasks and asked earlier and more frequently for help than men.

Reduction of Distortion Artifacts in Brain MRI Using a Field Map-based Correction Technique in Diffusion-weighted Imaging : A Prospective Study.

PURPOSE: The aim of this study was to evaluate the image quality and feasibility of a field map-based technique to correct for susceptibility-induced geometric distortions which are typical for diffusion EPI brain imaging. METHODS: We prospectively included 52 patients during clinical routine in this single-center study. All scans were performed on a 3T MRI. Patients' indications for MRI mainly consisted of suspected stroke due to the clinical presentation. For the morphological comparison of the corrected and uncorrected EPI diffusion, three experienced radiologists assessed the image quality of the sequences in a blinded and randomized fashion using a Likert scale (1 being poor; 5 being excellent). To ensure comparability of the two methods, an additional quantitative analysis of the apparent diffusion coefficient (ADC) was performed. RESULTS: Corrected EPI diffusion was rated significantly superior in all the selected categories: overall level of artifacts (p < 0.001), degree of distortion at the frontal, temporal, occipital and brainstem levels (p < 0.001), conspicuousness of ischemic lesions (p < 0.001), image quality (p < 0.001), naturality (p < 0.001), contrast (p < 0.001), and diagnostic confidence (p < 0.001). CONCLUSION: Corrected EPI diffusion offers a significant reduction of geometric distortion in all evaluated brain regions and an improved conspicuousness of ischemic lesions. Image quality, overall artifacts, naturality, contrast and diagnostic confidence were also rated superior in comparison to uncorrected EPI diffusion.

Prognostic value of single-subject grey matter networks in early multiple sclerosis.

The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.

Improvement of Neurovascular Imaging Using Ultra-High-Resolution Computed Tomography Angiography.

OBJECTIVE: To evaluate diagnostic image quality of ultra-high-resolution computed tomography angiography (UHR-CTA) in neurovascular imaging as compared to normal resolution CT-angiography (NR-CTA). MATERIAL AND METHODS: In this retrospective single-center study brain and neck CT-angiography was performed using an ultra-high-resolution computed tomography scanner (n = 82) or a normal resolution CT scanner (NR-CTA; n = 73). Ultra-high-resolution images were reconstructed with a 1024â€¯× 1024 matrix and a slice thickness of 0.25 mm, whereas NR-CT images were reconstructed with a 512â€¯× 512 matrix and a slice thickness of 0.5 mm. Three blinded neuroradiologists assessed overall image quality, artifacts, image noise, overall contrast and diagnostic confidence using a 4-point Likert scale. Furthermore, the visualization and delineation of supra-aortic arteries with an emphasis on the visualization of small intracerebral vessels was assessed using a cerebral vascular score, also utilizing a 4-point Likert scale. Quantitative analyses included signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), noise and the steepness of gray value transition. Radiation exposure was determined by comparison of computed tomography dose index (CTDIvol), dose length product (DLP) and mean effective dose. Interrater agreement was evaluated via determining Fleiss-Kappa. RESULTS: Ultra-high-resolution CT-angiography (UHR-CTA) yielded excellent image quality with superior quantitative (SNR: p < 0.001, CNR: p < 0.001, steepness of gray value transition: p < 0.001) and qualitative results (overall image quality: 4 (Inter quartile range (IQR) = 4-4); p < 0.001, diagnostic confidence: 4 (IQR = 4-4); p < 0.001) compared to NR-CT (overall image quality: 3 (IQR = 3-3), diagnostic confidence: 3 (IQR = 3-4)). Furthermore, UHR-CT enabled significantly superior delineation and visualization of all vascular segments, from proximal extracranial vessels to the smallest peripheral cerebral branches (e.g. , UHR-CTA PICA: 4 (3-4) vs. NR-CTA PICA: 3 (2-3); UHR-CTA P4: 4 (IQR = 3-4) vs. NR-CTA P4: 2 (IQR = 2-3); UHR-CTA M4: 4 (IQR = 4-4) vs. NR-CTA M4: 3 (IQR = 2-3); UHR-CTA A4: 4 (IQR = 3-4) vs. NR-CTA A4: 2 (IQR = 2-3); all p < 0.001). Noteworthy, a reduced mean effective dose was observed when applying UHR-CT (NR-CTA: 1.8 ± 0.3 mSv; UHR-CTA: 1.5 ± 0.5 mSv; p < 0.001). CONCLUSION: Ultra-high-resolution CT-angiography improves image quality in neurovascular imaging allowing the depiction and evaluation of small peripheral cerebral arteries. It may thus improve the detection of pathologies in small cerebrovascular lesions and the resulting diagnosis.

Comparison of Ultra-High-Resolution and Normal-Resolution CT-Angiography for Intracranial Aneurysm Detection in Patients with Subarachnoid Hemorrhage.

RATIONALE AND OBJECTIVES: Ruptured intracranial aneurysms (IAs) are the leading cause for atraumatic subarachnoid hemorrhage. In case of aneurysm rupture, patients may face life-threatening complications and require aneurysm occlusion. Detection of the aneurysm in computed tomography (CT) imaging is therefore essential for patient outcome. This study provides an evaluation of the diagnostic accuracy of Ultra-High-Resolution Computed Tomography Angiography (UHR-CTA) and Normal-Resolution Computed Tomography Angiography (NR-CTA) concerning IA detection and characterization. MATERIALS AND METHODS: Consecutive patients with atraumatic subarachnoid hemorrhage who received Digital Subtraction Angiography (DSA) and either UHR-CTA or NR-CTA were retrospectively included. Three readers evaluated CT-Angiography regarding image quality, diagnostic confidence and presence of IAs. Sensitivity and specificity were calculated on patient-level and segment-level with reference standard DSA-imaging. CTA patient radiation exposure (effective dose) was compared. RESULTS: One hundred and eight patients were identified (mean age = 57.8 ±â€¯14.1 years, 65 women). UHR-CTA revealed significantly higher image quality and diagnostic confidence (P < 0.001) for all readers and significantly lower effective dose (P < 0.001). Readers correctly classified ≥55/56 patients on UHR-CTA and ≥44/52 patients on NR-CTA. We noted significantly higher patient-level sensitivity for UHR-CTA compared to NR-CTA for all three readers (reader 1: 41/41 [100%] vs. 28/34 [82%], reader 2: 41/41 [100%] vs. 30/34 [88%], reader 3: 41/41 [100%] vs. 30/34 [88%], P ≤ 0.04). Segment-level analysis also revealed significantly higher sensitivity for UHR-CTA compared to NR-CTA for all three readers (reader 1: 47/49 [96%] vs. 34/45 [76%], reader 2: 47/49 [96%] vs. 37/45 [82%], reader 3: 48/49 [98%] vs. 37/45 [82%], P ≤ 0.04). Specificity was comparable for both techniques. CONCLUSION: We found Ultra-High-Resolution CT-Angiography to provide higher sensitivity than Normal-Resolution CT-Angiography for the detection of intracranial aneurysms in patients with aneurysmal subarachnoid hemorrhage while improving image quality and reducing patient radiation exposure.

Quantitative multi-energy micro-CT: A simulation and phantom study for simultaneous imaging of four different contrast materials using an energy integrating detector.

Emerging from the development of single-energy Computed Tomography (CT) and Dual-Energy Computed Tomography, Multi-Energy Computed Tomography (MECT) is a promising tool allowing advanced material and tissue decomposition and thereby enabling the use of multiple contrast materials in preclinical research. The scope of this work was to evaluate whether a usual preclinical micro-CT system is applicable for the decomposition of different materials using MECT together with a matrix-inversion method and how different changes of the measurement-environment affect the results. A matrix-inversion based algorithm to differentiate up to five materials (iodine, iron, barium, gadolinium, residual material) by applying four different acceleration voltages/energy levels was established. We carried out simulations using different ratios and concentrations (given in fractions of volume units, VU) of the four different materials (plus residual material) at different noise-levels for 30 keV, 40 keV, 50 keV, 60 keV, 80 keV and 100 keV (monochromatic). Our simulation results were then confirmed by using region of interest-based measurements in a phantom-study at corresponding acceleration voltages. Therefore, different mixtures of contrast materials were scanned using a micro-CT. Voxel wise evaluation of the phantom imaging data was conducted to confirm its usability for future imaging applications and to estimate the influence of varying noise-levels, scattering, artifacts and concentrations. The analysis of our simulations showed the smallest deviation of 0.01 (0.003-0.15) VU between given and calculated concentrations of the different contrast materials when using an energy-combination of 30 keV, 40 keV, 50 keV and 100 keV for MECT. Subsequent MECT phantom measurements, however, revealed a combination of acceleration voltages of 30 kV, 40 kV, 60 kV and 100 kV as most effective for performing material decomposition with a deviation of 0.28 (0-1.07) mg/ml. The feasibility of our voxelwise analyses using the proposed algorithm was then confirmed by the generation of phantom parameter-maps that matched the known contrast material concentrations. The results were mostly influenced by the noise-level and the concentrations used in the phantoms. MECT using a standard micro-CT combined with a matrix inversion method is feasible at four different imaging energies and allows the differentiation of mixtures of up to four contrast materials plus an additional residual material.

Can Whole-Body Baseline CT Radiomics Add Information to the Prediction of Best Response, Progression-Free Survival, and Overall Survival of Stage IV Melanoma Patients Receiving First-Line Targeted Therapy: A Retrospective Register Study.

BACKGROUND: The aim of this study was to investigate whether the combination of radiomics and clinical parameters in a machine-learning model offers additive information compared with the use of only clinical parameters in predicting the best response, progression-free survival after six months, as well as overall survival after six and twelve months in patients with stage IV malignant melanoma undergoing first-line targeted therapy. METHODS: A baseline machine-learning model using clinical variables (demographic parameters and tumor markers) was compared with an extended model using clinical variables and radiomic features of the whole tumor burden, utilizing repeated five-fold cross-validation. Baseline CTs of 91 stage IV malignant melanoma patients, all treated in the same university hospital, were identified in the Central Malignant Melanoma Registry and all metastases were volumetrically segmented (n = 4727). RESULTS: Compared with the baseline model, the extended radiomics model did not add significantly more information to the best-response prediction (AUC [95% CI] 0.548 (0.188, 0.808) vs. 0.487 (0.139, 0.743)), the prediction of PFS after six months (AUC [95% CI] 0.699 (0.436, 0.958) vs. 0.604 (0.373, 0.867)), or the overall survival prediction after six and twelve months (AUC [95% CI] 0.685 (0.188, 0.967) vs. 0.766 (0.433, 1.000) and AUC [95% CI] 0.554 (0.163, 0.781) vs. 0.616 (0.271, 1.000), respectively). CONCLUSIONS: The results showed no additional value of baseline whole-body CT radiomics for best-response prediction, progression-free survival prediction for six months, or six-month and twelve-month overall survival prediction for stage IV melanoma patients receiving first-line targeted therapy. These results need to be validated in a larger cohort.

Enhanced Image Processing Using Complex Averaging in Diffusion-Weighted Imaging of the Prostate: The Impact on Image Quality and Lesion Detectability.

Diffusion-weighted images of the prostate can suffer from a "hazy" background in low signal-intensity areas. We hypothesize that enhanced image processing (EIP) using complex averaging reduces artifacts, noise, and distortion in conventionally acquired diffusion-weighted images and synthesized high b-value images, thus leading to higher image quality and better detection of potentially malignant lesions. Conventional DWI trace images with a b-value of 1000 s/mm2 (b1000), calculated images with a b-value of 2000 s/mm2 (cb2000), and ADC maps of 3T multiparametric prostate MRIs in 53 patients (age 68.8 ± 10 years) were retrospectively evaluated. Standard images were compared to images using EIP. In the standard images, 36 lesions were detected in the peripheral zone and 20 in the transition zone. In 13 patients, EIP led to the detection of 8 additional lesions and the upgrading of 6 lesions; 6 of these patients were diagnosed with prostate carcinoma Gleason 7 or 8. EIP improved qualitative ratings for overall image quality and lesion detectability. Artifacts were significantly reduced in the cb2000 images. Quantitative measurements for lesion detectability expressed as an SI ratio were significantly improved. EIP using complex averaging led to image quality improvements in acquired and synthesized DWI, potentially resulting in elevated diagnostic accuracy and management changes.

DSA-Based 2D Perfusion Measurements in Delayed Cerebral Ischemia to Estimate the Clinical Outcome in Patients with Aneurysmal Subarachnoid Hemorrhage: A Technical Feasibility Study.

(1) Background: To predict clinical outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) and delayed cerebral ischemia (DCI) by assessment of the cerebral perfusion using a 2D perfusion angiography (2DPA) time-contrast agent (CA) concentration model. (2) Methods: Digital subtraction angiography (DSA) data sets of n = 26 subjects were acquired and post-processed focusing on changes in contrast density using a time-concentration model at three time points: (i) initial presentation with SAH (T0); (ii) vasospasm-associated acute clinical impairment (T1); and (iii) directly after endovascular treatment (T2) of SAH-associated large vessel vasospasm (LVV), which resulted in n = 78 data sets. Maximum slope (MS in SI/ms), time-to-peak (TTP in ms), and maximum amplitude of a CA bolus (dSI) were measured in brain parenchyma using regions of interest (ROIs). First, acquired parameters were standardized to the arterial input function (AIF) and then statistically analyzed as mean values. Additionally, data were clustered into two subsets consisting of patients with regredient or with stable/progredient symptoms (or Doppler signals) after endovascular treatment (n = 10 vs. n = 16). (3) Results: Perfusion parameters (MS, TTP, and dSI) differed significantly between T0 and T1 (p = 0.003 each). Significant changes between T1 and T2 were only detectable for MS (0.041 ± 0.016 vs. 0.059 ± 0.026; p = 0.011) in patients with regredient symptoms at T2 (0.04 ± 0.012 vs. 0.066 ± 0.031; p = 0.004). For dSI, there were significant differences between T0 and T2 (5095.8 ± 2541.9 vs. 3012.3 ± 968.3; p = 0.001), especially for those with stable symptoms at T2 (5685.4 ± 2967.2 vs. 3102.8 ± 1033.2; p = 0.02). Multiple linear regression analysis revealed that a) the difference in MS between T1 and T2 and b) patient's age (R = 0.6; R2 = 0.34; p = 0.009) strongly predict the modified Rankin Scale (mRS) at discharge. (4) Conclusions: 2DPA allows the direct measurement of treatment effects in SAH associated DCI and may be used to predict outcomes in these critically ill patients.

Longitudinal monitoring of Apparent Diffusion Coefficient (ADC) in patients with prostate cancer undergoing MR-guided radiotherapy on an MR-Linac at 1.5 T: a prospective feasibility study.

BACKGROUND: Hybrid MRI linear accelerators (MR-Linac) might enable individualized online adaptation of radiotherapy using quantitative MRI sequences as diffusion-weighted imaging (DWI). The purpose of this study was to investigate the dynamics of lesion apparent diffusion coefficient (ADC) in patients with prostate cancer undergoing MR-guided radiation therapy (MRgRT) on a 1.5T MR-Linac. The ADC values at a diagnostic 3T MRI scanner were used as the reference standard. PATIENTS AND AND METHODS: In this prospective single-center study, patients with biopsy-confirmed prostate cancer who underwent both an MRI exam at a 3T scanner (MRI3T) and an exam at a 1.5T MR-Linac (MRL) at baseline and during radiotherapy were included. Lesion ADC values were measured by a radiologist and a radiation oncologist on the slice with the largest lesion. ADC values were compared before vs. during radiotherapy (during the second week) on both systems via paired t-tests. Furthermore, Pearson correlation coefficient and inter-reader agreement were computed. RESULTS: A total of nine male patients aged 67 ± 6 years [range 60 - 67 years] were included. In seven patients, the cancerous lesion was in the peripheral zone, and in two patients the lesion was in the transition zone. Inter-reader reliability regarding lesion ADC measurement was excellent with an intraclass correlation coefficient of (ICC) > 0.90 both at baseline and during radiotherapy. Thus, the results of the first reader will be reported. In both systems, there was a statistically significant elevation of lesion ADC during radiotherapy (mean MRL-ADC at baseline was 0.97 ± 0.18 × 10-3 mm2/s vs. mean MRL-ADC during radiotherapy 1.38 ± 0.3 × 10-3 mm2/s, yielding a mean lesion ADC elevation of 0.41 ± 0.20 × 10-3 mm2/s, p < 0.001). Mean MRI3T-ADC at baseline was 0.78 ± 0.165 × 10-3 mm2/s vs. mean MRI3T-ADC during radiotherapy 0.99 ± 0.175 × 10-3 mm2/s, yielding a mean lesion ADC elevation of 0.21 ± 0.96 × 10-3 mm2/s p < 0.001). The absolute ADC values from MRL were consistently significantly higher than those from MRI3T at baseline and during radiotherapy (p < = 0.001). However, there was a strong positive correlation between MRL-ADC and MRI3T-ADC at baseline (r = 0.798, p = 0.01) and during radiotherapy (r = 0.863, p = 0.003). CONCLUSIONS: Lesion ADC as measured on MRL increased significantly during radiotherapy and ADC measurements of lesions on both systems showed similar dynamics. This indicates that lesion ADC as measured on the MRL may be used as a biomarker for evaluation of treatment response. In contrast, absolute ADC values as calculated by the algorithm of the manufacturer of the MRL showed systematic deviations from values obtained on a diagnostic 3T MRI system. These preliminary findings are promising but need large-scale validation. Once validated, lesion ADC on MRL might be used for real-time assessment of tumor response in patients with prostate cancer undergoing MR-guided radiation therapy.

Ultra-High-Resolution CT of the Head and Neck with Deep Learning Reconstruction-Assessment of Image Quality and Radiation Exposure and Intraindividual Comparison with Normal-Resolution CT.

OBJECTIVES: To assess the benefits of ultra-high-resolution CT (UHR-CT) with deep learning-based image reconstruction engine (AiCE) regarding image quality and radiation dose and intraindividually compare it to normal-resolution CT (NR-CT). METHODS: Forty consecutive patients with head and neck UHR-CT with AiCE for diagnosed head and neck malignancies and available prior NR-CT of a different scanner were retrospectively evaluated. Two readers evaluated subjective image quality using a 5-point Likert scale regarding image noise, image sharpness, artifacts, diagnostic acceptability, and assessability of various anatomic regions. For reproducibility, inter-reader agreement was analyzed. Furthermore, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and slope of the gray-value transition between different tissues were calculated. Radiation dose was evaluated by comparing CTDIvol, DLP, and mean effective dose values. RESULTS: UHR-CT with AiCE reconstruction led to significant improvement in subjective (image noise and diagnostic acceptability: p < 0.000; ICC ≥ 0.91) and objective image quality (SNR: p < 0.000; CNR: p < 0.025) at significantly lower radiation doses (NR-CT 2.03 ± 0.14 mSv; UHR-CT 1.45 ± 0.11 mSv; p < 0.0001) compared to NR-CT. CONCLUSIONS: Compared to NR-CT, UHR-CT combined with AiCE provides superior image quality at a markedly lower radiation dose. With improved soft tissue assessment and potentially improved tumor detection, UHR-CT may add further value to the role of CT in the assessment of head and neck pathologies.

Virtual Monoenergetic Imaging of Lower Extremities Using Dual-Energy CT Angiography in Patients with Diabetes Mellitus.

BACKGROUND: Type 2 diabetes mellitus (DM) is the most common metabolic disorder in the world and an important risk factor for peripheral arterial disease (PAD). CT angiography represents the method of choice for the diagnosis, pre-operative planning, and follow-up of vascular disease. Low-energy dual-energy CT (DECT) virtual mono-energetic imaging (VMI) has been shown to improve image contrast, iodine signal, and may also lead to a reduction in contrast medium dose. In recent years, VMI has been improved with the use of a new algorithm called VMI+, able to obtain the best image contrast with the least possible image noise in low-keV reconstructions. PURPOSE: To evaluate the impact of VMI+ DECT reconstructions on quantitative and qualitative image quality in the evaluation of the lower extremity runoff. MATERIALS AND METHODS: We evaluated DECT angiography of lower extremities in patients suffering from diabetes who had undergone clinically indicated DECT examinations between January 2018 and January 2023. Images were reconstructed with standard linear blending (F_0.5) and low VMI+ series were generated from 40 to 100 keV, in an interval of 15 keV. Vascular attenuation, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated for objective analysis. Subjective analysis was performed using five-point scales to evaluate image quality, image noise, and diagnostic assessability of vessel contrast. RESULTS: Our final study cohort consisted of 77 patients (41 males). Attenuation values, CNR, and SNR were higher in 40-keV VMI+ reconstructions compared to the remaining VMI+ and standard F_0.5 series (HU: 1180.41 ± 45.09; SNR: 29.91 ± 0.99; CNR: 28.60 ± 1.03 vs. HU 251.32 ± 7.13; SNR: 13.22 ± 0.44; CNR: 10.57 ± 0.39 in standard F_0.5 series) (p < 0.0001). Subjective image rating was significantly higher in 55-keV VMI+ images compared to the other VMI+ and standard F_0.5 series in terms of image quality (mean score: 4.77), image noise (mean score: 4.39), and assessability of vessel contrast (mean value: 4.57) (p < 0.001). CONCLUSIONS: DECT 40-keV and 55-keV VMI+ showed the highest objective and subjective parameters of image quality, respectively. These specific energy levels for VMI+ reconstructions could be recommended in clinical practice, providing high-quality images with greater diagnostic suitability for the evaluation of lower extremity runoff, and potentially needing a lower amount of contrast medium, which is particularly advantageous for diabetic patients.

Ultrafast Brain MRI Protocol at 1.5 T Using Deep Learning and Multi-shot EPI.

RATIONALE AND OBJECTIVES: To evaluate clinical feasibility and image quality of a comprehensive ultrafast brain MRI protocol with multi-shot echo planar imaging and deep learning-enhanced reconstruction at 1.5T. MATERIALS AND METHODS: Thirty consecutive patients who underwent clinically indicated MRI at a 1.5 T scanner were prospectively included. A conventional MRI (c-MRI) protocol, including T1-, T2-, T2*-, T2-FLAIR, and diffusion-weighted images (DWI)-weighted sequences were acquired. In addition, ultrafast brain imaging with deep learning-enhanced reconstruction and multi-shot EPI (DLe-MRI) was performed. Subjective image quality was evaluated by three readers using a 4-point Likert scale. To assess interrater agreement, Fleiss' kappa (Ï°) was determined. For objective image analysis, relative signal intensity levels for grey matter, white matter, and cerebrospinal fluid were calculated. RESULTS: Time of acquisition (TA) of c-MRI protocols added up to 13:55 minutes, whereas the TA of DLe-MRI-based protocol added up to 3:04 minutes, resulting in a time reduction of 78%. All DLe-MRI acquisitions yielded diagnostic image quality with good absolute values for subjective image quality. C-MRI demonstrated slight advantages for DWI in overall subjective image quality (c-MRI: 3.93 [+/- 0.25] vs DLe-MRI: 3.87 [+/- 0.37], P = .04) and diagnostic confidence (c-MRI: 3.93 [+/- 0.25] vs DLe-MRI: 3.83 [+/- 3.83], P = .01). For most evaluated quality scores, moderate interobserver agreement was found. Objective image evaluation revealed comparable results for both techniques. CONCLUSION: DLe-MRI is feasible and allows for highly accelerated comprehensive brain MRI within 3minutes at 1.5 T with good image quality. This technique may potentially strengthen the role of MRI in neurological emergencies.