Evaluation of a single-breath-hold radial turbo-spin-echo sequence for T2 mapping of the liver at 3T

Bacterial association with metals enables in vivo monitoring of urogenital microbiota using magnetic resonance imaging

Bacteria constitute a significant part of the biomass of the human microbiota, but their interactions are complex and difficult to replicate outside the host. Exploiting the superior resolution of magnetic resonance imaging (MRI) to examine signal parameters of selected human isolates may allow tracking of their dispersion throughout the body. Here we investigate longitudinal and transverse MRI relaxation rates and found significant differences between several bacterial strains. Common commensal strains of lactobacilli display notably high MRI relaxation rates, partially explained by elevated cellular manganese content, while other species contain more iron than manganese. Lactobacillus crispatus show particularly high values, 4-fold greater than any other species; up to 60-fold greater signal than relevant tissue background; and a linear relationship between relaxation rate and fraction of live cells. Different bacterial strains have detectable, repeatable MRI relaxation rates that in the future may enable monitoring of their persistence in the human body for enhanced molecular imaging.

T1 and T2-mapping in pancreatic MRI: Current evidence and future perspectives

Conventional T1- and T2-weighted magnetic resonance imaging (MRI) of the pancreas can vary significantly due to factors such as scanner differences and pulse sequence variations. This review explores T1 and T2 mapping techniques, modern MRI methods providing quantitative information about tissue relaxation times. Various T1 and T2 mapping pulse sequences are currently under investigation. Clinical and research applications of T1 and T2 mapping in the pancreas include their correlation with fibrosis, inflammation, and neoplasms. In chronic pancreatitis, T1 mapping and extracellular volume (ECV) quantification demonstrate potential as biomarkers, aiding in early diagnosis and classification. T1 mapping also shows promise in evaluating pancreatic exocrine function and detecting glucose metabolism disorders. T2* mapping is valuable in quantifying pancreatic iron, offering insights into conditions like thalassemia major. However, challenges persist, such as the lack of consensus on optimal sequences and normal values for healthy pancreas relaxometry. Large-scale studies are needed for validation, and improvements in mapping sequences are essential for widespread clinical integration. The future holds potential for mixed qualitative and quantitative models, extending the applications of relaxometry techniques to various pancreatic lesions and enhancing routine MRI protocols for pancreatic pathology diagnosis and prognosis.

A short-TR single-echo spin-echo breath-hold method for assessing liver T2

OBJECTIVE

Conventional single-echo spin-echo T2 mapping used for liver iron quantification is too long for breath-holding. This study investigated a short TR (~100 ms) single-echo spin-echo T2 mapping technique wherein each image (corresponding to a single TE) could be acquired in ~17 s-short enough for a breath-hold. TE images were combined for T2 fitting. To avoid T1 bias, each TE acquisition incremented TR to maintain a constant TR-TE.

MATERIALS AND METHODS

Experiments at 1.5T validated the technique's accuracy in phantoms, 9 healthy volunteers, and 5 iron overload patients. In phantoms and healthy volunteers, the technique was compared to the conventional approach of constant TR for all TEs. Iron overload results were compared to FerriScan.

RESULTS

In phantoms, the constant TR-TE technique provided unbiased estimates of T2, while the conventional constant TR approach underestimated it. In healthy volunteers, there was no significant discrepancy at the 95% confidence level between constant TR-TE and reference T2 values, whereas there was for constant TR scans. In iron overload patients, there was a high correlation between constant TR-TE and FerriScan T2 values (r2 = 0.95), with a discrepancy of 0.6+/- 1.4 ms.

DISCUSSION

The short-TR single-echo breath-hold spin-echo technique provided unbiased estimates of T2 in phantoms and livers.

Simultaneous T1, T2 and T2⁎ mapping of the liver with multi-shot MI-SAGE

PURPOSE

To apply multi-shot high-resolution multi inversion spin and gradient echo (MI-SAGE) acquisition for simultaneous liver T1, T2 and T2* mapping.

METHODS

Inversion prepared spin- and gradient-echo EPI was developed with ascending slice order across measurements for efficient acquisition with T1, T2, and T2⁎ weighting. Multi-shot EPI was also implemented to minimize distortion and blurring while enabling high in-plane resolution. A dictionary-matching approach was used to fit the images to quantitative parameter maps, which were compared to T1 measured by modified Look-Locker (MOLLI), T1 measured by variable flip angle (VFA), T2 measured by multiple echo time-based Half Fourier Single-shot Turbo spin-Echo (HASTE), T2 measured by radial turbo-spin-echo (rTSE) and T2⁎ measured by multiple gradient echo (MGRE) sequences.

RESULTS

The multi-shot variant of the sequence achieved higher in-plane resolution of 1.7 × 1.7 mm2 with good image quality in 28 s. Derived quantitative maps showed comparable values to conventional mapping methods. As measured in phantom and in vivo, MOLLI, MESE and MGRE give closest values to MISAGE. VFA, HASTE and rTSE show obvious overestimation.

CONCLUSIONS

The proposed multi-shot inversion prepared spin- and gradient-echo EPI sequence allows for high-resolution quantitative T1, T2 and T2 liver tissue characterization in a single breath-hold scan.

Free-breathing and instantaneous abdominal T2 mapping via single-shot multiple overlapping-echo acquisition and deep learning reconstruction

OBJECTIVES

To develop a real-time abdominal T₂ mapping method without requiring breath-holding or respiratory-gating.

METHODS

The single-shot multiple overlapping-echo detachment (MOLED) pulse sequence was employed to achieve free-breathing T₂ mapping of the abdomen. Deep learning was used to untangle the non-linear relationship between the MOLED signal and T₂ mapping. A synthetic data generation flow based on Bloch simulation, modality synthesis, and randomization was proposed to overcome the inadequacy of real-world training set.

RESULTS

The results from simulation and in vivo experiments demonstrated that our method could deliver high-quality T₂ mapping. The average NMSE and R² values of linear regression in the digital phantom experiments were 0.0178 and 0.9751. Pearson's correlation coefficient between our predicted T₂ and reference T₂ in the phantom experiments was 0.9996. In the measurements for the patients, real-time capture of the T₂ value changes of various abdominal organs before and after contrast agent injection was realized. A total of 33 focal liver lesions were detected in the group, and the mean and standard deviation of T₂ values were 141.1 ± 50.0 ms for benign and 63.3 ± 16.0 ms for malignant lesions. The coefficients of variance in a test-retest experiment were 2.9%, 1.2%, 0.9%, 3.1%, and 1.8% for the liver, kidney, gallbladder, spleen, and skeletal muscle, respectively.

CONCLUSIONS

Free-breathing abdominal T₂ mapping is achieved in about 100 ms on a clinical MRI scanner. The work paved the way for the development of real-time dynamic T₂ mapping in the abdomen.

KEY POINTS

• MOLED achieves free-breathing abdominal T₂ mapping in about 100 ms, enabling real-time capture of T₂ value changes due to CA injection in abdominal organs. • Synthetic data generation flow mitigates the issue of lack of sizable abdominal training datasets.

Preoperative prediction of lymph node metastasis in nonfunctioning pancreatic neuroendocrine tumors from clinical and MRI features: a multicenter study

BACKGROUND

The extent of surgery in nonfunctioning pancreatic neuroendocrine tumors (NF-PNETs) has not well established, partly owing to the dilemma of precise prediction of lymph node metastasis (LNM) preoperatively. This study proposed to develop and validate the value of MRI features for predicting LNM in NF-PNETs.

METHODS

A total of 187 patients with NF-PNETs who underwent MR scan and subsequent lymphadenectomy from 4 hospitals were included and divided into training group (n = 66, 1 center) and validation group (n = 121, 3 centers). The clinical characteristics and qualitative MRI features were collected. Multivariate logistic regression model for predicting LNM in NF-PNETs was constructed using the training group and further tested using validation group.

RESULTS

Nodal metastases were reported in 41 patients (21.9%). Multivariate analysis showed that regular shape of primary tumor (odds ratio [OR], 4.722; p = .038) and the short axis of the largest lymph node in the regional area (OR, 1.488; p = .002) were independent predictors for LNM in the training group. The area under the receiver operating characteristic curve in the training group and validation group were 0.890 and 0.849, respectively. Disease-free survival was significantly different between model-defined LNM and non-LNM group.

CONCLUSIONS

The novel MRI-based model considering regular shape of primary tumor and short axis of largest lymph node in the regional area can accurately predict lymph node metastases preoperatively in NF-PNETs patients, which might facilitate the surgeons' decision on risk stratification.