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Objectives: Positron emission tomography (PET) is currently considered the non-invasive reference standard for lymph node (N-)staging in lung cancer. However, not all patients can undergo this diagnostic procedure due to high costs, limited availability, and additional radiation exposure. The purpose of this study was to predict the PET result from traditional contrast-enhanced computed tomography (CT) and to test different feature extraction strategies. Methods: In this study, 100 lung cancer patients underwent a contrast-enhanced \(^{18}\)F-fluorodeoxyglucose (FDG) PET/CT scan between August 2012 and December 2019. We trained machine learning models to predict FDG uptake in the subsequent PET scan. Model inputs were composed of (i) traditional “hand-crafted” radiomics features from the segmented lymph nodes, (ii) deep features derived from a pretrained EfficientNet-CNN, and (iii) a hybrid approach combining (i) and (ii). Results: In total, 2734 lymph nodes [555 (20.3%) PET-positive] from 100 patients [49% female; mean age 65, SD: 14] with lung cancer (60% adenocarcinoma, 21% plate epithelial carcinoma, 8% small-cell lung cancer) were included in this study. The area under the receiver operating characteristic curve (AUC) ranged from 0.79 to 0.87, and the scaled Brier score (SBS) ranged from 16 to 36%. The random forest model (iii) yielded the best results [AUC 0.871 (0.865–0.878), SBS 35.8 (34.2–37.2)] and had significantly higher model performance than both approaches alone (AUC: p < 0.001, z = 8.8 and z = 22.4; SBS: p < 0.001, z = 11.4 and z = 26.6, against (i) and (ii), respectively). Conclusion: Both traditional radiomics features and transfer-learning deep radiomics features provide relevant and complementary information for non-invasive N-staging in lung cancer.
Magnetic Particle Imaging (MPI) is a promising new tomographic modality for fast as well as three-dimensional visualization of magnetic material. For anatomical or structural information an additional imaging modality such as computed tomography (CT) is required. In this paper, the first hybrid MPI-CT scanner for multimodal imaging providing simultaneous data acquisition is presented.
The aim of this study was to explore the applicability of fast MR techniques to routine paediatric abdominopelvic MRI at 1.5 Tesla. "Controlled Aliasing in Parallel Imaging Results in Higher Acceleration-" (CAIPIRINHA-) accelerated contrast-enhanced-T1w 3D FLASH imaging was compared to standard T1w 2D FLASH imaging with breath-holding in 40 paediatric patients and to respiratory-triggered T1w TSE imaging in 10 sedated young children. In 20 nonsedated patients, we compared T2w TIRM to fat-saturated T2w HASTE imaging. Two observers performed an independent and blinded assessment of overall image quality. Acquisition time was reduced by the factor of 15 with CAIPIRINHA-accelerated T1w FLASH and by 7 with T2w HASTE. With CAIPIRINHA and with HASTE, there were significantly less motion artefacts in nonsedated patients. In sedated patients, respiratory-triggered T1w imaging in general showed better image quality. However, satisfactory image quality was achieved with CAIPIRINHA in two sedated patients where respiratory triggering failed. In summary, fast scanning with CAIPIRINHA and HASTE presents a reliable high quality alternative to standard sequences in paediatric abdominal MRI. Paediatric patients, in particular, benefit greatly from fast image acquisition with less breath-hold cycles or shorter sedation.
Objective:
Over the past decade, myocardial triglyceride content has become an accepted biomarker for chronic metabolic and cardiac disease. The purpose of this study was to use proton (hydrogen 1)-magnetic resonance spectroscopy (\(^{1}\)H-MRS) at 3Tesla (3 T) field strength to assess potential gender-related differences in myocardial triglyceride content in healthy individuals.
Methods:
Cardiac MR imaging was performed to enable accurate voxel placement and obtain functional and morphological information. Double triggered (i.e., ECG and respiratory motion gating) \(^{1}\)H-MRS was used to quantify myocardial triglyceride levels for each gender. Two-sample t-test and Mann-Whitney U-test were used for statistical analyses.
Results:
In total, 40 healthy volunteers (22 male, 18 female; aged >18 years and age matched) were included in the study. Median myocardial triglyceride content was 0.28% (interquartile range [IQR] 0.17–0.42%) in male and 0.24% (IQR 0.14–0.45%) in female participants, and no statistically significant difference was observed between the genders. Furthermore, no gender-specific difference in ejection fraction was observed, although on average, male participants presented with a higher mean ± SD left ventricular mass (136.3 ± 25.2 g) than female participants (103.9 ± 16.1 g).
Conclusions:
The study showed that \(^{1}\)H-MRS is a capable, noninvasive tool for acquisition of myocardial triglyceride metabolites. Myocardial triglyceride concentration was shown to be unrelated to gender in this group of healthy volunteers.
Background
Salvage radiotherapy (SRT) is clinically established in prostate cancer (PC) patients with PSA persistence or biochemical relapse (BCR) after prior radical surgery. PET/CT imaging prior to SRT may be performed to localize disease recurrence. The recently introduced \(^{68}\)Ga-PSMA outperforms other PET tracers for detection of recurrence and is therefore expected also to impact radiation planning.
Forty-five patients with PSA persistence (16 pts) or BCR (29 pts) after prior prostatectomy, scheduled to undergo SRT of the prostate bed, underwent \(^{68}\)Ga-PSMA PET/CT. The median PSA level was 0.67 ng/ml. The impact of \(^{68}\)Ga-PSMA PET/CT on the treatment decision was assessed. Patients with oligometastatic (≤5 lesions) PC underwent radiotherapy (RT), with the extent of the RT area and dose escalation being based on PET positivity.
Results
Suspicious lesions were detected in 24/45 (53.3 %) patients. In 62.5 % of patients, lesions were only detected by 68Ga-PSMA PET. Treatment was changed in 19/45 (42.2 %) patients, e.g., extending SRT to metastases (9/19), administering dose escalation in patients with morphological local recurrence (6/19), or replacing SRT by systemic therapy (2/19). 38/45 (84.4 %) followed the treatment recommendation, with data on clinical follow-up being available in 21 patients treated with SRT. All but one showed biochemical response (mean PSA decline 78 ± 19 %) within a mean follow-up of 8.12 ± 5.23 months.
Conclusions
\(^{68}\)Ga-PSMA PET/CT impacts treatment planning in more than 40 % of patients scheduled to undergo SRT. Future prospective studies are needed to confirm this significant therapeutic impact on patients prior to SRT.
Background
Partial segmental thrombosis of the corpus cavernosum (PSTCC) is a rare disease predominantly occurring in young men. Cardinal symptoms are pain and perineal swelling. Although several risk factors are described in the literature, the exact etiology of penile thrombosis remains unclear in most cases. MRI or ultrasound (US) is usually used for diagnosing this condition.
Case presentation
We report a case of penile thrombosis after left-sided varicocele ligature in a young patient. The diagnosis was established using contrast-enhanced ultrasound (CEUS) and was confirmed by contrast-enhanced magnetic resonance imaging (ceMRI). Successful conservative treatment consisted of systemic anticoagulation using low molecular weight heparin and acetylsalicylic acid.
Conclusion
PSTCC is a rare condition in young men and appears with massive pain and perineal swelling. In case of suspected PSTCC utilization of CEUS may be of diagnostic benefit.
Mapping the longitudinal relaxation time \(T_1\) has widespread applications in clinical MRI as it promises a quantitative comparison of tissue properties across subjects and scanners. Due to the long scan times of conventional methods, however, the use of quantitative MRI in clinical routine is still very limited. In this work, an acceleration of Inversion-Recovery Look-Locker (IR-LL) \(T_1\) mapping is presented. A model-based algorithm is used to iteratively enforce an exponential relaxation model to a highly undersampled radially acquired IR-LL dataset obtained after the application of a single global inversion pulse. Using the proposed technique, a \(T_1\) map of a single slice with 1.6mm in-plane resolution and 4mm slice thickness can be reconstructed from data acquired in only 6s. A time-consuming segmented IR experiment was used as gold standard for \(T_1\) mapping in this work. In the subsequent validation study, the model-based reconstruction of a single-inversion IR-LL dataset exhibited a \(T_1\) difference of less than 2.6% compared to the segmented IR-LL reference in a phantom consisting of vials with \(T_1\) values between 200ms and 3000ms. In vivo, the \(T_1\) difference was smaller than 5.5% in WM and GM of seven healthy volunteers. Additionally, the \(T_1\) values are comparable to standard literature values. Despite the high acceleration, all model-based reconstructions were of a visual quality comparable to fully sampled references. Finally, the reproducibility of the \(T_1\) mapping method was demonstrated in repeated acquisitions. In conclusion, the presented approach represents a promising way for fast and accurate \(T_1\) mapping using radial IR-LL acquisitions without the need of any segmentation.
Background: Giant cell arteritis (GCA) is the most common systemic vasculitis in persons aged 50 and above (incidence, 3.5 per 100 000 per year). It affects cranial arteries, the aorta, and arteries elsewhere in the body, e.g., in the limbs.
Methods: We selectively review the pertinent literature, including guidelines and recommendations from Germany and abroad.
Results: The typical symptoms of new-onset GCA are bi-temporal headaches, jaw claudiacation, scalp tenderness, visual disturbances, systemic symptoms such as fever and weight loss, and polymyalgia. The diagnostic assessment comprises laboratory testing (erythrocyte sedimentation rate, C-reactive protein), imaging studies (duplex sonography, high-resolution magnetic resonance imaging, positron-emission tomography), and temporal artery biopsy. The standard treatment is with corticosteroids (adverse effects: diabetes mellitus, osteoporosis, cataract, arterial hypertension). A meta-analysis of three randomized controlled trials led to a recommendation for treatment with methotrexate to lower the recurrence rate and spare steroids. Patients for whom methotrexate is contraindicated or who cannot tolerate the drug can be treated with azathioprine instead.
Conclusion: Giant cell arteritis, if untreated, progresses to involve the aorta and its collateral branches, leading to various complications. Late diagnosis and treatment can have serious consequences, including irreversible loss of visual function.
Aims Acute myocardial infarction (MI) is the major cause of chronic heart failure. The activity of blood coagulation factor XIII (FXIIIa) plays an important role in rodents as a healing factor after MI, whereas its role in healing and remodelling processes in humans remains unclear. We prospectively evaluated the relevance of FXIIIa after acute MI as a potential early prognostic marker for adequate healing.
Methods and results This monocentric prospective cohort study investigated cardiac remodelling in patients with ST-elevation MI and followed them up for 1 year. Serum FXIIIa was serially assessed during the first 9 days after MI and after 2, 6, and 12 months. Cardiac magnetic resonance imaging was performed within 4 days after MI (Scan 1), after 7 to 9 days (Scan 2), and after 12 months (Scan 3). The FXIII valine-to-leucine (V34L) single-nucleotide polymorphism rs5985 was genotyped. One hundred forty-six patients were investigated (mean age 58 ± 11 years, 13% women). Median FXIIIa was 118 % (quartiles, 102–132%) and dropped to a trough on the second day after MI: 109%(98–109%; P < 0.001). FXIIIa recovered slowly over time, reaching the baseline level after 2 to 6 months and surpassed baseline levels only after 12 months: 124 % (110–142%). The development of FXIIIa after MI was independent of the genotype. FXIIIa on Day 2 was strongly and inversely associated with the relative size of MI in Scan 1 (Spearman’s ρ = –0.31; P = 0.01) and Scan 3 (ρ = –0.39; P < 0.01) and positively associated with left ventricular ejection fraction: ρ = 0.32 (P < 0.01) and ρ = 0.24 (P = 0.04), respectively.
Conclusions FXIII activity after MI is highly dynamic, exhibiting a significant decline in the early healing period, with reconstitution 6 months later. Depressed FXIIIa early after MI predicted a greater size of MI and lower left ventricular ejection fraction after 1 year. The clinical relevance of these findings awaits to be tested in a randomized trial.
Due to the low frequency of abnormalities affecting the spleen, this organ is often overlooked during radiological examinations. Here, we report on the unexpected finding, that the spleen signal on diffusion-weighted MRI (DW-MRI) is associated with clinical parameters in patients with plasma cell dyscrasias. Methods: We investigated the spleen signal on DW-MRI together with clinical and molecular parameters in 295 transplant-eligible newly diagnosed Multiple Myeloma (NDMM) patients and in 72 cases with monoclonal gammopathy of undetermined significance (MGUS). Results: Usually, the spleen is the abdominal organ with the highest intensities on DW-MRI. Yet, significant signal loss on DW-MRI images was seen in 71 of 295 (24%) NDMM patients. This phenomenon was associated with the level of bone marrow plasmacytosis (P=1x10(-10)) and International Staging System 3 (P=0.0001) but not with gain(1q), and del(17p) or plasma cell gene signatures. The signal was preserved in 72 individuals with monoclonal gammopathy of undetermined significance and generally re-appeared in MM patients responding to treatment, suggesting that lack of signal reflects increased tumor burden. While absence of spleen signal in MM patients with high risk disease defined a subgroup with very poor outcome, re-appearance of the spleen signal after autologous stem cell transplantation was seen in patients with improved outcome. Our preliminary observation suggests that extramedullary hematopoiesis in the spleen is a factor that modifies the DW-MRI signal of this organ. Conclusions: The DW-MRI spleen signal is a promising marker for tumor load and provides prognostic information in MM.
Purpose
To fully automatically derive quantitative parameters from late gadolinium enhancement (LGE) cardiac MR (CMR) in patients with myocardial infarction and to investigate if phase sensitive or magnitude reconstructions or a combination of both results in best segmentation accuracy.
Methods
In this retrospective single center study, a convolutional neural network with a U-Net architecture with a self-configuring framework (“nnU-net”) was trained for segmentation of left ventricular myocardium and infarct zone in LGE-CMR. A database of 170 examinations from 78 patients with history of myocardial infarction was assembled. Separate fitting of the model was performed, using phase sensitive inversion recovery, the magnitude reconstruction or both contrasts as input channels.
Manual labelling served as ground truth. In a subset of 10 patients, the performance of the trained models was evaluated and quantitatively compared by determination of the Sørensen-Dice similarity coefficient (DSC) and volumes of the infarct zone compared with the manual ground truth using Pearson’s r correlation and Bland-Altman analysis.
Results
The model achieved high similarity coefficients for myocardium and scar tissue. No significant difference was observed between using PSIR, magnitude reconstruction or both contrasts as input (PSIR and MAG; mean DSC: 0.83 ± 0.03 for myocardium and 0.72 ± 0.08 for scars). A strong correlation for volumes of infarct zone was observed between manual and model-based approach (r = 0.96), with a significant underestimation of the volumes obtained from the neural network.
Conclusion
The self-configuring nnU-net achieves predictions with strong agreement compared to manual segmentation, proving the potential as a promising tool to provide fully automatic quantitative evaluation of LGE-CMR.
Objectives
Trauma evaluation of extremities can be challenging in conventional radiography. A multi-use x-ray system with cone-beam CT (CBCT) option facilitates ancillary 3-D imaging without repositioning. We assessed the clinical value of CBCT scans by analyzing the influence of additional findings on therapy.
Methods
Ninety-two patients underwent radiography and subsequent CBCT imaging with the twin robotic scanner (76 wrist/hand/finger and 16 ankle/foot/toe trauma scans). Reports by on-call radiologists before and after CBCT were compared regarding fracture detection, joint affliction, comminuted injuries, and diagnostic confidence. An orthopedic surgeon recommended therapy based on reported findings. Surgical reports (N = 52) and clinical follow-up (N = 85) were used as reference standard.
Results
CBCT detected more fractures (83/64 of 85), joint involvements (69/53 of 71), and multi-fragment situations (68/50 of 70) than radiography (all p < 0.001). Six fractures suspected in radiographs were ruled out by CBCT. Treatment changes based on additional information from CBCT were recommended in 29 patients (31.5%). While agreement between advised therapy before CBCT and actual treatment was moderate (κ = 0.41 [95% confidence interval 0.35–0.47]; p < 0.001), agreement after CBCT was almost perfect (κ = 0.88 [0.83–0.93]; p < 0.001). Diagnostic confidence increased considerably for CBCT studies (p < 0.001). Median effective dose for CBCT was 4.3 μSv [3.3–5.3 μSv] compared to 0.2 μSv [0.1–0.2 μSv] for radiography.
Conclusions
CBCT provides advantages for the evaluation of acute small bone and joint trauma by detecting and excluding extremity fractures and fracture-related findings more reliably than radiographs. Additional findings induced therapy change in one third of patients, suggesting substantial clinical impact.
Objectives
Vessel wall enhancement (VWE) may be commonly seen on MRI images of asymptomatic subjects. This study aimed to characterize the VWE of the proximal internal carotid (ICA) and vertebral arteries (VA) in a non-vasculitic elderly patient cohort.
Methods
Cranial MRI scans at 3 Tesla were performed in 43 patients (aged ≥ 50 years) with known malignancy for exclusion of cerebral metastases. For vessel wall imaging (VWI), a high-resolution compressed-sensing black-blood 3D T1-weighted fast (turbo) spin echo sequence (T1 CS-SPACE prototype) was applied post gadolinium with an isotropic resolution of 0.55 mm. Bilateral proximal intradural ICA and VA segments were evaluated for presence, morphology, and longitudinal extension of VWE.
Results
Concentric VWE of the proximal intradural ICA was found in 13 (30%) patients, and of the proximal intradural VA in 39 (91%) patients. Mean longitudinal extension of VWE after dural entry was 13 mm in the VA and 2 mm in the ICA. In 14 of 39 patients (36%) with proximal intradural VWE, morphology of VWE was suggestive of the mere presence of vasa vasorum. In 25 patients (64 %), morphology indicated atherosclerotic lesions in addition to vasa vasorum.
Conclusions
Vasa vasorum may account for concentric VWE within the proximal 2 mm of the ICA and 13 mm of the VA after dural entry in elderly subjects. Concentric VWE in these locations should not be confused with large artery vasculitis. Distal to these segments, VWE may be more likely related to pathologic conditions such as vasculitis.
Purpose
Image acquisition and subsequent manual analysis of cardiac cine MRI is time-consuming. The purpose of this study was to train and evaluate a 3D artificial neural network for semantic segmentation of radially undersampled cardiac MRI to accelerate both scan time and postprocessing.
Methods
A database of Cartesian short-axis MR images of the heart (148,500 images, 484 examinations) was assembled from an openly accessible database and radial undersampling was simulated. A 3D U-Net architecture was pretrained for segmentation of undersampled spatiotemporal cine MRI. Transfer learning was then performed using samples from a second database, comprising 108 non-Cartesian radial cine series of the midventricular myocardium to optimize the performance for authentic data. The performance was evaluated for different levels of undersampling by the Dice similarity coefficient (DSC) with respect to reference labels, as well as by deriving ventricular volumes and myocardial masses.
Results
Without transfer learning, the pretrained model performed moderately on true radial data [maximum number of projections tested, P = 196; DSC = 0.87 (left ventricle), DSC = 0.76 (myocardium), and DSC =0.64 (right ventricle)]. After transfer learning with authentic data, the predictions achieved human level even for high undersampling rates (P = 33, DSC = 0.95, 0.87, and 0.93) without significant difference compared with segmentations derived from fully sampled data.
Conclusion
A 3D U-Net architecture can be used for semantic segmentation of radially undersampled cine acquisitions, achieving a performance comparable with human experts in fully sampled data. This approach can jointly accelerate time-consuming cine image acquisition and cumbersome manual image analysis.
Background
Morphology and glenoid involvement determine the necessity of surgical management in scapula fractures. While being present in only a small share of patients with shoulder trauma, numerous classification systems have been in use over the years for categorization of scapula fractures. The purpose of this study was to evaluate the established AO/OTA classification in comparison to the classification system of Euler and Rüedi (ER) with regard to interobserver reliability and confidence in clinical practice.
Methods
Based on CT imaging, 149 patients with scapula fractures were retrospectively categorized by two trauma surgeons and two radiologists using the classification systems of ER and AO/OTA. To measure the interrater reliability, Fleiss kappa (κ) was calculated independently for both fracture classifications. Rater confidence was stated subjectively on a five-point scale and compared with Wilcoxon signed rank tests. Additionally, we computed the intraclass correlation coefficient (ICC) based on absolute agreement in a two-way random effects model to assess the diagnostic confidence agreement between observers.
Results
In scapula fractures involving the glenoid fossa, interrater reliability was substantial (κ = 0.722; 95% confidence interval [CI] 0.676–0.769) for the AO/OTA classification in contrast to moderate agreement (κ = 0.579; 95% CI 0.525–0.634) for the ER classification system. Diagnostic confidence for intra-articular fracture patterns was superior using the AO/OTA classification compared to ER (p < 0.001) with higher confidence agreement (ICC: 0.882 versus 0.831). For extra-articular fractures, ER (κ = 0.817; 95% CI 0.771–0.863) provided better interrater reliability compared to AO/OTA (κ = 0.734; 95% CI 0.692–0.776) with higher diagnostic confidence (p < 0.001) and superior agreement between confidence ratings (ICC: 0.881 versus 0.912).
Conclusions
The AO/OTA classification is most suitable to categorize intra-articular scapula fractures with glenoid involvement, whereas the classification system of Euler and Rüedi appears to be superior in extra-articular injury patterns with fractures involving only the scapula body, spine, acromion and coracoid process.
Purpose
The reliable detection of tumor-infiltrated axillary lymph nodes for breast cancer [BC] patients plays a decisive role in further therapy. We aimed to find out whether cross-sectional imaging techniques could improve sensitivity for pretherapeutic axillary staging in nodal-positive BC patients compared to conventional imaging such as mammography and sonography.
Methods
Data for breast cancer patients with tumor-infiltrated axillary lymph nodes having received surgery between 2014 and 2020 were included in this study.
All examinations (sonography, mammography, computed tomography [CT] and magnetic resonance imaging [MRI]) were interpreted by board-certified specialists in radiology. The sensitivity of different imaging modalities was calculated, and binary logistic regression analyses were performed to detect variables influencing the detection of positive lymph nodes.
Results
All included 382 breast cancer patients had received conventional imaging, while 52.61% of the patients had received cross-sectional imaging.
The sensitivity of the combination of all imaging modalities was 68.89%. The combination of MRI and CT showed 63.83% and the combination of sonography and mammography showed 36.11% sensitivity.
Conclusion
We could demonstrate that cross-sectional imaging can improve the sensitivity of the detection of tumor-infiltrated axillary lymph nodes in breast cancer patients. Only the safe detection of these lymph nodes at the time of diagnosis enables the evaluation of the response to neoadjuvant therapy, thereby allowing access to prognosis and improving new post-neoadjuvant therapies.
Objective
Blindness is a feared complication of giant cell arteritis (GCA). However, the spectrum of pathologic orbital imaging findings on magnetic resonance imaging (MRI) in GCA is not well understood. In this study, we assess inflammatory changes of intraorbital structures on black blood MRI (BB-MRI) in patients with GCA compared to age-matched controls.
Methods
In this multicenter case-control study, 106 subjects underwent BB-MRI. Fifty-six patients with clinically or histologically diagnosed GCA and 50 age-matched controls without clinical or laboratory evidence of vasculitis were included. All individuals were imaged on a 3-T MR scanner with a post-contrast compressed-sensing (CS) T1-weighted sampling perfection with application-optimized contrasts using different flip angle evolution (SPACE) BB-MRI sequence. Imaging results were correlated with available clinical symptoms.
Results
Eighteen of 56 GCA patients (32%) showed inflammatory changes of at least one of the intraorbital structures. The most common finding was enhancement of at least one of the optic nerve sheaths (N = 13, 72%). Vessel wall enhancement of the ophthalmic artery was unilateral in 8 and bilateral in 3 patients. Enhancement of the optic nerve was observed in one patient. There was no significant correlation between imaging features of inflammation and clinically reported orbital symptoms (p = 0.10). None of the age-matched control patients showed any inflammatory changes of intraorbital structures.
Conclusions
BB-MRI revealed inflammatory findings in the orbits in up to 32% of patients with GCA. Optic nerve sheath enhancement was the most common intraorbital inflammatory change on BB-MRI. MRI findings were independent of clinically reported orbital symptoms.
Key Points
• Up to 32% of GCA patients shows signs of inflammation of intraorbital structures on BB-MRI.
• Enhancement of the optic nerve sheath is the most common intraorbital finding in GCA patients on BB-MRI.
• Features of inflammation of intraorbital structures are independent of clinically reported symptoms.
Purpose
The aim of this study was to compare the wave‐CAIPI (controlled aliasing in parallel imaging) trajectory to the Cartesian sampling for accelerated free‐breathing 4D lung MRI.
Methods
The wave‐CAIPI k‐space trajectory was implemented in a respiratory self‐gated 3D spoiled gradient echo pulse sequence. Trajectory correction applying the gradient system transfer function was used, and images were reconstructed using an iterative conjugate gradient SENSE (CG SENSE) algorithm. Five healthy volunteers and one patient with squamous cell carcinoma in the lung were examined on a clinical 3T scanner, using both sampling schemes. For quantitative comparison of wave‐CAIPI and standard Cartesian imaging, the normalized mutual information and the RMS error between retrospectively accelerated acquisitions and their respective references were calculated. The SNR ratios were investigated in a phantom study.
Results
The obtained normalized mutual information values indicate a lower information loss due to acceleration for the wave‐CAIPI approach. Average normalized mutual information values of the wave‐CAIPI acquisitions were 10% higher, compared with Cartesian sampling. Furthermore, the RMS error of the wave‐CAIPI technique was lower by 19% and the SNR was higher by 14%. Especially for short acquisition times (down to 1 minute), the undersampled Cartesian images showed an increased artifact level, compared with wave‐CAIPI.
Conclusion
The application of the wave‐CAIPI technique to 4D lung MRI reduces undersampling artifacts, in comparison to a Cartesian acquisition of the same scan time. The benefit of wave‐CAIPI sampling can therefore be traded for shorter examinations, or enhancing image quality of undersampled 4D lung acquisitions, keeping the scan time constant.
Background
Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentation of lung images which were scanned by a fast UTE sequence exploiting the stack-of-spirals trajectory can provide sufficiently good accuracy for the calculation of functional parameters.
Methods
In this study, lung images were acquired in 20 patients suffering from cystic fibrosis (CF) and 33 healthy volunteers, by a fast UTE sequence with a stack-of-spirals trajectory and a minimum echo-time of 0.05 ms. A convolutional neural network was then trained for semantic lung segmentation using 17,713 2D coronal slices, each paired with a label obtained from manual segmentation. Subsequently, the network was applied to 4920 independent 2D test images and results were compared to a manual segmentation using the Sørensen–Dice similarity coefficient (DSC) and the Hausdorff distance (HD). Obtained lung volumes and fractional ventilation values calculated from both segmentations were compared using Pearson’s correlation coefficient and Bland Altman analysis.
To investigate generalizability to patients outside the CF collective, in particular to those exhibiting larger consolidations inside the lung, the network was additionally applied to UTE images from four patients with pneumonia and one with lung cancer.
Results
The overall DSC for lung tissue was 0.967 ± 0.076 (mean ± standard deviation) and HD was 4.1 ± 4.4 mm. Lung volumes derived from manual and deep learning based segmentations as well as values for fractional ventilation exhibited a high overall correlation (Pearson’s correlation coefficent = 0.99 and 1.00). For the additional cohort with unseen pathologies / consolidations, mean DSC was 0.930 ± 0.083, HD = 12.9 ± 16.2 mm and the mean difference in lung volume was 0.032 ± 0.048 L.
Conclusions
Deep learning-based image segmentation in stack-of-spirals based lung MRI allows for accurate estimation of lung volumes and fractional ventilation values and promises to replace the time-consuming step of manual image segmentation in the future.