Synthetic temporal bone CT generation from UTE-MRI using a cycleGAN-based deep learning model: advancing beyond CT-MR imaging fusion.

OBJECTIVES: The aim of this study is to develop a deep-learning model to create synthetic temporal bone computed tomography (CT) images from ultrashort echo-time magnetic resonance imaging (MRI) scans, thereby addressing the intrinsic limitations of MRI in localizing anatomic landmarks in temporal bone CT. MATERIALS AND METHODS: This retrospective study included patients who underwent temporal MRI and temporal bone CT within one month between April 2020 and March 2023. These patients were randomly divided into training and validation datasets. A CycleGAN model for generating synthetic temporal bone CT images was developed using temporal bone CT and pointwise encoding-time reduction with radial acquisition (PETRA). To assess the model's performance, the pixel count in mastoid air cells was measured. Two neuroradiologists evaluated the successful generation rates of 11 anatomical landmarks. RESULTS: A total of 102 patients were included in this study (training dataset, n = 54, mean age 58 ± 14, 34 females (63%); validation dataset, n = 48, mean age 61 ± 13, 29 females (60%)). In the pixel count of mastoid air cells, no difference was observed between synthetic and real images (679 ± 342 vs 738 ± 342, p = 0.13). For the six major anatomical sites, the positive generation rates were 97-100%, whereas those of the five major anatomical structures ranged from 24% to 83%. CONCLUSION: We developed a model to generate synthetic temporal bone CT images using PETRA MRI. This model can provide information regarding the major anatomic sites of the temporal bone using MRI. CLINICAL RELEVANCE STATEMENT: The proposed algorithm addresses the primary limitations of MRI in localizing anatomic sites within the temporal bone. KEY POINTS: CT is preferred for imaging the temporal bone, but has limitations in differentiating pathology there. The model achieved a high success rate in generating synthetic images of six anatomic sites. This can overcome the limitations of MRI in visualizing key anatomic sites in the temporal skull.

Bright diffusion sign: A sensitive and specific radiologic biomarker for multinodular and vacuolating neuronal tumor.

BACKGROUND AND PURPOSE: Accurate differentiation between multinodular and vacuolating neuronal tumor (MVNT) and dysembryoplastic neuroepithelial tumor (DNET) is important for treatment decision-making. We aimed to develop an accurate radiologic diagnostic model for differentiating MVNT from DNET using T2WI and diffusion-weighted imaging (DWI). MATERIALS AND METHODS: A total of 56 patients (mean age, 47.48±17.78 years; 31 women) diagnosed with MVNT (n = 37) or DNET (n = 19) who underwent brain MRI, including T2WI and DWI, were included. Two board-certified neuroradiologists performed qualitative (bubble appearance, cortical involvement, bright diffusion sign, and bright apparent diffusion coefficient [ADC] sign) and quantitative (nDWI and nADC) assessments. A diagnostic tree model was developed with significant and reliable imaging findings using an exhaustive chi-squared Automatic Interaction Detector (CHAID) algorithm. RESULTS: In visual assessment, the imaging features that showed high diagnostic accuracy and interobserver reliability were the bright diffusion sign and absence of cortical involvement (bright diffusion sign: accuracy, 94.64 %; sensitivity, 91.89 %; specificity, 100.00 %; interobserver agreement, 1.00; absence of cortical involvement: accuracy, 92.86 %; sensitivity, 89.19 %; specificity, 100.00 %; interobserver agreement, 1.00). In quantitative analysis, nDWI was significantly higher in MVNT than in DENT (1.52 ± 0.34 vs. 0.91 ± 0.27, p < 0.001), but the interobserver agreement was fair (intraclass correlation coefficient = 0.321). The overall diagnostic accuracy of the tree model with visual assessment parameters was 98.21 % (55/56). CONCLUSION: The bright diffusion sign and absence of cortical involvement are accurate and reliable imaging findings for differentiating MVNT from DNET. By using simple, intuitive, and reliable imaging findings, such as the bright diffusion sign, MVNT can be accurately differentiated from DNET.

Synthetic Time of Flight Magnetic Resonance Angiography Generation Model Based on Cycle-Consistent Generative Adversarial Network Using PETRA-MRA in the Patients With Treated Intracranial Aneurysm.

BACKGROUND: Pointwise encoding time reduction with radial acquisition (PETRA) magnetic resonance angiography (MRA) is useful for evaluating intracranial aneurysm recurrence, but the problem of severe background noise and low peripheral signal-to-noise ratio (SNR) remain. Deep learning could reduce noise using high- and low-quality images. PURPOSE: To develop a cycle-consistent generative adversarial network (cycleGAN)-based deep learning model to generate synthetic TOF (synTOF) using PETRA. STUDY TYPE: Retrospective. POPULATION: A total of 377 patients (mean age: 60 ± 11; 293 females) with treated intracranial aneurysms who underwent both PETRA and TOF from October 2017 to January 2021. Data were randomly divided into training (49.9%, 188/377) and validation (50.1%, 189/377) groups. FIELD STRENGTH/SEQUENCE: Ultra-short echo time and TOF-MRA on a 3-T MR system. ASSESSMENT: For the cycleGAN model, the peak SNR (PSNR) and structural similarity (SSIM) were evaluated. Image quality was compared qualitatively (5-point Likert scale) and quantitatively (SNR). A multireader diagnostic optimality evaluation was performed with 17 radiologists (experience of 1-18 years). STATISTICAL TESTS: Generalized estimating equation analysis, Friedman's test, McNemar test, and Spearman's rank correlation. P < 0.05 indicated statistical significance. RESULTS: The PSNR and SSIM between synTOF and TOF were 17.51 [16.76; 18.31] dB and 0.71 ± 0.02. The median values of overall image quality, noise, sharpness, and vascular conspicuity were significantly higher for synTOF than for PETRA (4.00 [4.00; 5.00] vs. 4.00 [3.00; 4.00]; 5.00 [4.00; 5.00] vs. 3.00 [2.00; 4.00]; 4.00 [4.00; 4.00] vs. 4.00 [3.00; 4.00]; 3.00 [3.00; 4.00] vs. 3.00 [2.00; 3.00]). The SNRs of the middle cerebral arteries were the highest for synTOF (synTOF vs. TOF vs. PETRA; 63.67 [43.25; 105.00] vs. 52.42 [32.88; 74.67] vs. 21.05 [12.34; 37.88]). In the multireader evaluation, there was no significant difference in diagnostic optimality or preference between synTOF and TOF (19.00 [18.00; 19.00] vs. 20.00 [18.00; 20.00], P = 0.510; 8.00 [6.00; 11.00] vs. 11.00 [9.00, 14.00], P = 1.000). DATA CONCLUSION: The cycleGAN-based deep learning model provided synTOF free from background artifact. The synTOF could be a versatile alternative to TOF in patients who have undergone PETRA for evaluating treated aneurysms. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.

Development and validation of visual grading system for stenosis in intracranial atherosclerotic disease on time-of-flight magnetic resonance angiography.

OBJECTIVES: Although the overestimation problem of time-of-flight magnetic resonance angiography (TOF-MRA) applying the warfarin-aspirin symptomatic intracranial disease (WASID) method to assess intracranial arterial stenosis has often been suggested, no pertinent grading system for TOF-MRA has been developed. We aimed to develop and evaluate the performance of a visual grading system for intracranial arterial stenosis on TOF-MRA (MRAVICAST). METHODS: This single-center cohort study analyzed prospective observational registry data from a comprehensive stroke center between January 2014 and February 2020. Patients with confirmed stenosis of the intracranial large arteries who underwent confirmative digital subtraction angiography (DSA) were included; a 4-point grading system was developed based on physical characteristics of TOF-MRA. The overall diagnostic accuracies of MRAVICAST for each grade, interobserver reproducibility, and positive predictive values for > 50% and > 70% stenoses were evaluated. RESULTS: We analyzed 132 segments with intracranial atherosclerotic stenosis from 71 patients (34 men and 37 women; mean age, 61.0 ± 15.25 years; range, 21-89 years). The overall diagnostic accuracy of MRAVICAST (93.9%, 124/132) was higher than that of MRAWASID (50.8%, 67/132) for each grade. The degree of stenosis did not differ significantly between MRAVICAST and DSAWASID (p = .849). Regarding reproducibility, MRAVICAST demonstrated excellent interobserver agreement (ICC, 0.989; 95% CI, 0.979-0.999). The positive predictive values of MRAVICAST for the diagnosis of > 50% and > 70% stenoses were 97.3% and 100.0%, respectively. CONCLUSIONS: The new intuitive grading system accurately and reliably determined the degree of stenosis in intracranial arterial atherosclerosis patients. MRAVICAST could be a versatile alternative to MRAWASID for evaluating intracranial arterial stenosis. KEY POINTS: • In this retrospective diagnostic study (sample: 132 stenotic segments), the overall accuracy of the visual grading system (MRAVICAST) was 94%, and positive predictive value for > 50% stenosis was 97%. • In the era of medical treatment for intracranial atherosclerotic stenosis, MRAVICAST could be a versatile alternative method to MRAWASID for evaluating intracranial arterial stenosis.

Clinical Relevance of Computed Tomography Perfusion-Estimated Infarct Volume in Acute Ischemic Stroke Patients within the 6-h Therapeutic Time Window.

INTRODUCTION: Although the estimated infarct volume on baseline computed tomography perfusion (CTP) can identify patients who are likely to benefit from endovascular thrombectomy (EVT) in late time window strokes, the role of CTP imaging in early time windows has not been established. We assessed the clinical impact of CTP-estimated infarct volume on long-term prognosis after EVT, particularly in patients with early time window stroke. METHODS: We retrospectively reviewed patients who underwent pretreatment CTP and EVT for large vessel occlusion in the anterior circulation within 6 h after symptom onset between March 2014 and February 2019. The infarct volume at baseline CTP was estimated using commercially available software (RAPID, iSchemaView, Menlo Park, CA, USA) with a cerebral blood flow threshold <30% of the normal brain. Risk factors for poor outcome after EVT were evaluated, and a receiver operating characteristic (ROC) curve analysis was used to identify CTP-estimated infarct volumes that optimally predicted the development of symptomatic intracranial hemorrhage (sICH) and poor outcomes (modified Rankin Scale [mRS] 3-6) at 90 days. RESULTS: Of 120 patients, successful recanalization was achieved in 89 (74.2%) patients, while 61 (50.8%) showed poor outcomes at 90 days. Among 89 patients with successful recanalization after EVT, age, diabetes, clinical stroke severity, CTP-estimated infarct volume, and sICH development were independently associated with 90-day clinical outcomes. ROC analysis identified infarct volumes of ≥88.5 mL and ≥74 mL as the optimal thresholds for predicting poor outcome and development of sICH, respectively. Patients with large infarct volumes showed poorer outcomes (odds ratio [OR], 7.704; 95% confidence interval [CI], 1.528-38.839) and higher rates of sICH development (OR, 10.857; 95% CI, 1.835-64.235). Among patients with large infarction volumes (≥88.5 mL), the 90-day mRS demonstrated a shift toward better outcomes in patients with successful recanalization. CONCLUSION: Larger initial infarct volumes are significantly associated with worse clinical outcomes in patients who underwent EVT because of early time window stroke. Furthermore, our study of 6-h data demonstrated that an initial infarction of more than a certain volume might be an independent risk factor for sICH development and poor outcomes even in patients with successful recanalization. However, we still observed benefits of EVT in patients with large ischemic cores. The CTP-estimated infarct volume might be an important prognostic factor after EVT rather than a biomarker predicting treatment effectiveness.

Cervical necrotic lymphadenopathy: a diagnostic tree analysis model based on CT and clinical findings.

OBJECTIVES: To establish a diagnostic tree analysis (DTA) model based on computed tomography (CT) findings and clinical information for differential diagnosis of cervical necrotic lymphadenopathy, especially in regions where tuberculous lymphadenitis and Kikuchi disease are common. METHODS: A total of 290 patients (147 men and 143 women; mean age (years), 46.2 ± 19.5; range, 3-91) with pathologically confirmed metastasis (n = 110), tuberculous lymphadenitis (n = 73), Kikuchi disease (n = 71), and lymphoma (n = 36) who underwent contrast-enhanced neck CT were included. The patients were randomly divided into training (86%, 248/290) and validation (14%, 42/290) datasets to assess diagnostic performance of the DTA model. Two sorts of DTA models were created using a classification and regression tree algorithm on the basis of CT findings alone and that combined with clinical findings. RESULTS: In the DTA model based on CT findings alone, perinodal infiltration, number of the necrotic foci, percentage of necrotic lymph node (LN), degree of necrosis, margin and shape of the necrotic portion, shape of the LN, and enhancement ratio (cutoff value, 1.93) were significant predictors for differential diagnosis of cervical necrotic lymphadenopathy. The overall accuracy was 80.6% and 73.8% in training and validation datasets. In the model based on imaging and clinical findings, tenderness, history of underlying malignancy, percentage of necrotic LN, degree of necrosis, and number of necrotic foci were significant predictors. The overall accuracy was 87.1% and 88.1% in training and external validation datasets. CONCLUSIONS: The DTA model based on CT imaging and clinical findings may be helpful for the diagnosis of cervical necrotic lymphadenopathy. KEY POINTS: • The diagnostic tree analysis model based on CT may be useful for differential diagnosis of cervical necrotic lymphadenopathy. • Perinodal infiltration, number of necrotic foci, percentage of necrotic lymph nodes, degree of necrosis, margin and shape of necrotic portion, lymph node shape, and enhancement ratio were the most significant predictors.

Differentiation of Acute Internal Carotid Artery Occlusion Etiology on Computed Tomography Angiography: Diagnostic Tree for Preparing Endovascular Treatment.

BACKGROUND AND PURPOSE: This study aimed to identify the imaging characteristics and discriminate the etiology of acute internal carotid artery occlusion (ICAO) on computed tomography angiography (CTA) in patients with acute ischemic stroke. MATERIALS AND METHODS: We retrospectively evaluated consecutive patients who underwent endovascular thrombectomy for acute ICAO. Contrast filling of the extracranial ICA in preprocedural CTA was considered apparent ICAO. Non-contrast filling of the extracranial ICA was evaluated according to the contrast-filled lumen configuration, lumen margin and location, Hounsfield units of the non-attenuating segment, and presence of calcification or an intimal flap. Digital subtraction angiography findings were the reference standard for ICAO etiology and the occlusion site. A diagnostic tree was derived using significant variables according to pseudo-occlusion, atherosclerotic vascular disease (ASVD), thrombotic occlusion, and dissection. RESULTS: A total of 114 patients showed apparent ICAO (n = 21), pseudo-occlusion (n = 51), ASVD (n = 27), thrombotic occlusion (n = 9), or dissection (n = 6). Most pseudo-occlusions (50/51, 98.0%) showed dependent locations with ill-defined contrast column margins and classic flame or beak shapes. The most common occlusion site of pseudo-occlusion was the petro-cavernous ICA (n = 32, 62.7%). Apparent ICAO mainly appeared in cases with occlusion distal to the posterior communicating artery orifice. ASVD showed beak or blunt shapes in the presence of low-density plaques or dense calcifications. Dissection revealed flame- or beak-shaped appearances with circumscribed margins. Thrombotic occlusions tended to appear blunt-shaped. The decision-tree model showed a 92.5% overall accuracy. CONCLUSIONS: CTA characteristics may help diagnose ICAO etiology. We provide a simple and easy decision-making model to inform endovascular thrombectomy.

Deep Learning-Based High-Resolution Magnetic Resonance Angiography (MRA) Generation Model for 4D Time-Resolved Angiography with Interleaved Stochastic Trajectories (TWIST) MRA in Fast Stroke Imaging.

PURPOSE: The purpose of this study is to improve the qualitative and quantitative image quality of the time-resolved angiography with interleaved stochastic trajectories technique (4D-TWIST-MRA) using deep neural network (DNN)-based MR image reconstruction software. MATERIALS AND METHODS: A total of 520 consecutive patients underwent 4D-TWIST-MRA for ischemic stroke or intracranial vessel stenosis evaluation. Four-dimensional DNN-reconstructed MRA (4D-DNR) was generated using commercially available software (SwiftMR v.3.0.0.0, AIRS Medical, Seoul, Republic of Korea). Among those evaluated, 397 (76.3%) patients received concurrent time-of-flight MRA (TOF-MRA) to compare the signal-to-noise ratio (SNR), image quality, noise, sharpness, vascular conspicuity, and degree of venous contamination with a 5-point Likert scale. Two radiologists independently evaluated the detection rate of intracranial aneurysm in TOF-MRA, 4D-TWIST-MRA, and 4D-DNR in separate sessions. The other 123 (23.7%) patients received 4D-TWIST-MRA due to a suspicion of acute ischemic stroke. The confidence level and decision time for large vessel occlusion were evaluated in these patients. RESULTS: In qualitative analysis, 4D-DNR demonstrated better overall image quality, sharpness, vascular conspicuity, and noise reduction compared to 4D-TWIST-MRA. Moreover, 4D-DNR exhibited a higher SNR than 4D-TWIST-MRA. The venous contamination and aneurysm detection rates were not significantly different between the two MRA images. When compared to TOF-MRA, 4D-CE-MRA underestimated the aneurysm size (2.66 ± 0.51 vs. 1.75 ± 0.62, p = 0.029); however, 4D-DNR showed no significant difference in size compared to TOF-MRA (2.66 ± 0.51 vs. 2.10 ± 0.41, p = 0.327). In the diagnosis of large vessel occlusion, 4D-DNR showed a better confidence level and shorter decision time than 4D-TWIST-MRA. CONCLUSION: DNN reconstruction may improve the qualitative and quantitative image quality of 4D-TWIST-MRA, and also enhance diagnostic performance for intracranial aneurysm and large vessel occlusion.

Early therapy evaluation of intra-arterial trastuzumab injection in a human breast cancer xenograft model using multiparametric MR imaging.

PURPOSE: To investigate the treatment efficacy of intra-arterial (IA) trastuzumab treatment using multiparametric magnetic resonance imaging (MRI) in a human breast cancer xenograft model. MATERIALS AND METHODS: Human breast cancer cells (BT474) were stereotaxically injected into the brains of nude mice to obtain a xenograft model. The mice were divided into four groups and subjected to different treatments (IA treatment [IA-T], intravenous treatment [IV-T], IA saline injection [IA-S], and the sham control group). MRI was performed before and at 7 and 14 d after treatment to assess the efficacy of the treatment. The tumor volume, apparent diffusion coefficient (ADC), and dynamic contrast-enhanced (DCE) MRI parameters (Ktrans, Kep, Ve, and Vp) were measured. RESULTS: Tumor volumes in the IA-T group at 14 d after treatment were significantly lower than those in the IV-T group (13.1 mm3 [interquartile range 8.48-16.05] vs. 25.69 mm3 [IQR 20.39-30.29], p = 0.005), control group (IA-S, 33.83 mm3 [IQR 32.00-36.30], p<0.01), and sham control (39.71 mm3 [IQR 26.60-48.26], p <0.001). The ADC value in the IA-T group was higher than that in the control groups (IA-T, 7.62 [IQR 7.23-8.20] vs. IA-S, 6.77 [IQR 6.48-6.87], p = 0.044 and vs. sham control, 6.89 [IQR 4.93-7.48], p = 0.004). Ktrans was significantly decreased following the treatment compared to that in the control groups (p = 0.002 and p<0.001 for vs. IA-S and sham control, respectively). Tumor growth was decreased in the IV-T group compared to that in the sham control group (25.69 mm3 [IQR 20.39-30.29] vs. 39.71 mm3 [IQR 26.60-48.26], p = 0.27); there was no significant change in the MRI parameters. CONCLUSION: IA treatment with trastuzumab potentially affects the early response to treatment, including decreased tumor growth and decrease of Ktrans, in a preclinical brain tumor model.

Integrative MR Imaging Interpretation in Cognitive Impairment with Alzheimer's Disease, Small Vessel Disease, and Glymphatic Function-Related MR Parameters.

RATIONALE AND OBJECTIVES: The role of MR imaging in patients with cognitive impairment is to evaluate each component of Alzheimer's disease (AD), small vessel disease (SVD), and glymphatic function. We want to validate the diagnostic performance of the comprehensive interpretation of these parameters to predict the cognitive impairment stage. MATERIALS AND METHODS: This retrospective single-center study included 359 patients with cognitive impairment who had undergone MRI (FLAIR, T2WI, 3D-T1WI, susceptibility-weighted imaging, and diffusion tensor imaging [DTI]) and a neuropsychological screening battery between January 2020 and July 2022. Each AD and SVD-related MR parameter was visually evaluated, and DTI analysis along the perivascular space (ALPS) index was calculated. Volumetry analysis was performed using Neurophet AQUA AI-based software. Using logistic regression analysis, four types of models were developed and compared by adding the components in the following order: (1) clinical factors and AD, (2) SVD, (3) glymphatic function-related MR parameters, and (4) volumetric data. Chi-square automatic interaction detection algorithm was used to develop diagnostic tree analysis (DTA) model to predict late-stage cognitive impairment. RESULTS: APOE4 status, years of education, medial temporal lobe atrophy score, Fazekas scale score, DTI-ALPS index, and white matter hyperintensity were significant predictors of late-stage cognitive impairment. The performance of the prediction model increased from Model 1 to Model 4 (AUC: 0.880, 0.899, 0.914, and 0.945, respectively). The overall accuracy of the DTA model was 87.47%. CONCLUSION: Integrative brain MRI assessments in patients with cognitive impairment, AD, SVD, and glymphatic function-related MR parameters, improve the prediction of late-stage cognitive impairment.

Deep Learning-Based Synthetic TOF-MRA Generation Using Time-Resolved MRA in Fast Stroke Imaging.

BACKGROUND AND PURPOSE: Time-resolved MRA enables collateral evaluation in acute ischemic stroke with large-vessel occlusion; however, a low SNR and spatial resolution impede the diagnosis of vascular occlusion. We developed a CycleGAN-based deep learning model to generate high-resolution synthetic TOF-MRA images using time-resolved MRA and evaluated its image quality and clinical efficacy. MATERIALS AND METHODS: This retrospective, single-center study included 397 patients who underwent both TOF- and time-resolved MRA between April 2021 and January 2022. Patients were divided into 2 groups for model development and image-quality validation. Image quality was evaluated qualitatively and quantitatively with 3 sequences. A multireader diagnostic optimality evaluation was performed by 16 radiologists. For clinical validation, we evaluated 123 patients who underwent fast stroke MR imaging to assess acute ischemic stroke. The diagnostic confidence level and decision time for large-vessel occlusion were also evaluated. RESULTS: Median values of overall image quality, noise, sharpness, venous contamination, and SNR for M1, M2, the basilar artery, and posterior cerebral artery are better with synthetic TOF than with time-resolved MRA. However, with respect to real TOF, synthetic TOF presents worse median values of overall image quality, sharpness, vascular conspicuity, and SNR for M3, the basilar artery, and the posterior cerebral artery. During the multireader evaluation, radiologists could not discriminate synthetic TOF images from TOF images. During clinical validation, both readers demonstrated increases in diagnostic confidence levels and decreases in decision time. CONCLUSIONS: A CycleGAN-based deep learning model was developed to generate synthetic TOF from time-resolved MRA. Synthetic TOF can potentially assist in the detection of large-vessel occlusion in stroke centers using time-resolved MRA.

Transient global amnesia: Signal alteration in 2D/3D T2-FLAIR sequences.

PURPOSE: Transient global amnesia (TGA) is one of the most enigmatic syndromes in clinical neurology. The detection rate of TGA lesions in 2D/3D FLAIR sequences has not been evaluated. METHODS: A total of 201 patients (44 men and 157 women; mean age, 60.34 ± 9.23 years; range, 22-91 years) diagnosed with TGA, who underwent diffusion-weighted imaging (DWI; b = 1000 s/mm2, b = 2000 s/mm2, 4 mm) and/or 2D/3D-FLAIR sequences (4 mm, 0.9 mm; respectively) using 3-T MRI within 28 days after onset of TGA symptoms, were included in this single-center, retrospective, cross-sectional study. Hippocampal lesions were visually assessed in all sequences and detection rates were analyzed according to imaging timing (1 day, 2-4 days, 5-7 days, 8-11 days, and 12-28 days) and kinds of sequences. RESULTS: The detection rates were highest 2-4 days after symptom onset in all sequences, and that was higher in order of b = 2000 (75.28% [67/89]), b = 1000 (63.92% [62/97]), 3D-FLAIR (59.38% [19/32]), and 2D-FLAIR (15.15% [15/99]). On FLAIR sequences, detectability was lower 5-7 days after onset than that 2-4 days after onset (2D-FLAIR, 15.15% [15/99] vs. 5.56% [1/18]; 3D-FLAIR, 59.38% [19/32] vs. 0.00% [0/1]). CONCLUSION: FLAIR signal changes occur in approximately 60% of TGA patients 2-4 days after symptom onset, and decrease after 5 days. It is postulated that the pathophysiology of TGA might differ from common ischemic changes.

Ultrashort Echo Time Magnetic Resonance Angiography in Follow-up of Intracranial Aneurysms Treated With Endovascular Coiling: Comparison of Time-of-Flight, Pointwise Encoding Time Reduction With Radial Acquisition, and Contrast-Enhanced Magnetic Resonance Angiography.

BACKGROUND: The optimal magnetic resonance angiography (MRA) sequence for assessing the aneurysm occlusion state or in-stent flow after endovascular coiling is not well established. OBJECTIVE: To evaluate the diagnostic performance of pointwise encoding time reduction with radial acquisition (PETRA)-MRA in patients who underwent endovascular coiling relative to that of time-of-flight (TOF)-MRA and contrast-enhanced (CE)-MRA. METHODS: We evaluated the aneurysm occlusion state using digital subtraction angiography (DSA) and MRA. In patients who underwent stent-assisted coiling, we estimated the visibility of in-stent flow. RESULTS: We enrolled 189 patients with assessable TOF, PETRA, and CE-MRAs after coiling. In patients who underwent simple coiling (128 patients), PETRA showed a higher sensitivity in the detection of residual flow than TOF and CE (PETRA, 100%; CE, 83%; TOF, 80%). There were no significant differences in the height of residual flow between DSA (0.68 ± 1.45 mm) and PETRA (0.70 ± 1.50 mm; P = 1.000). In patients who underwent stent-assisted coiling (61 patients), PETRA showed the highest sensitivity (88%) in detecting residual flow (CE, 56%; TOF, 31%). Regarding in-stent flow, PETRA, CE, and TOF showed visual scores of ≥3 with frequencies of 96.7%, 85.2%, and 37.7%, respectively. Relative signal-to-noise ratio of PETRA (0.62 ± 0.18) was significantly higher than that of CE (0.56 ± 0.12) and TOF (0.39 ± 0.12; P < .001 for both). CONCLUSION: PETRA-MRA showed excellent diagnostic performance in terms of residual flow detection and in-stent flow assessment. PETRA could be a versatile alternative sequence for following up patients with coiled aneurysm.

Wnt and the cancer niche: paracrine interactions with gastrointestinal cancer cells undergoing asymmetric cell division.

OBJECTIVE: Stem-like cancer cells contribute to cancer initiation and maintenance. Stem cells can self-renew by asymmetric cell division (ACD). ACD with non-random chromosomal cosegregation (ACD-NRCC) is one possible self-renewal mechanism. There is a paucity of evidence supporting ACD-NRCC in human cancer. Our aim was to investigate ACD-NRCC and its potential interactions with the cancer niche (microenvironment) in gastrointestinal cancers. DESIGN: We used DNA double and single labeling approaches with FACS to isolate live cells undergoing ACD-NRCC. RESULTS: Gastrointestinal cancers contain rare subpopulations of cells capable of ACD-NRCC. ACD-NRCC was detected preferentially in subpopulations of cells previously suggested to be stem-like/tumor-initiating cancer cells. ACD-NRCC was independent of cell-to-cell contact, and was regulated by the cancer niche in a heat-sensitive paracrine fashion. Wnt pathway genes and proteins are differentially expressed in cells undergoing ACD-NRCC vs. symmetric cell division. Blocking the Wnt pathway with IWP2 (WNT antagonist) or siRNA-TCF4 resulted in suppression of ACD-NRCC. However, using a Wnt-agonist did not increase the relative proportion of cells undergoing ACD-NRCC. CONCLUSION: Gastrointestinal cancers contain subpopulations of cells capable of ACD-NRCC. Here we show for the first time that ACD-NRCC can be regulated by the Wnt pathway, and by the cancer niche in a paracrine fashion. However, whether ACD-NRCC is exclusively associated with stem-like cancer cells remains to be determined. Further study of these findings might generate novel insights into stem cell and cancer biology. Targeting the mechanism of ACD-NRCC might engender novel approaches for cancer therapy.

Isolation of live label-retaining cells and cells undergoing asymmetric cell division via nonrandom chromosomal cosegregation from human cancers.

The ability to retain DNA labels over time is a property proposed to be associated with adult stem cells. Recently, label retaining cells (LRC) were indentified in cancer. LRC were suggested to be the result of either slow-cycling or asymmetric-cell-division with nonrandom-chromosomal-cosegregation (ACD-NRCC). ACD-NRCC is proposed to segregate the older template DNA strands into daughter stem cells and newly synthesized DNA into daughter cells destined for differentiation. The existence of cells undergoing ACD-NRCC and the stem-like nature of LRC remain controversial. Currently, to detect LRC and ACD-NRCC, cells need to undergo fixation. Therefore, testing the stem-cell nature and other functional traits of LRC and cells undergoing ACD-NRCC has been limited. Here, we show a method for labeling DNA with single and dual-color nucleotides in live human liver cancer cells avoiding the need for fixation. We describe a novel methodology for both the isolation of live LRC and cells undergoing ACD-NRCC via fluorescence-activated cell sorting with confocal microscopy validation. This has the potential to be a powerful adjunct to stem-cell and cancer research.