Keywords: fMRI Analysis, Breast

Motivation: The lack of guidelines or recommendations for the ROI size of DWI and synthetic MRI.

Goal(s): To investigate the effect of different ROI positioning methods on both ADC and synthetic MRI measurements and to subsequently evaluate the diagnostic performance of differently shaped ROIs.

Approach: Four different ROI positioning methods on ADC and synthetic parameters measurements. 

Results: Square ROI showed the optimal AUC followed by freehand ROI. T2 + ADC were more diagnostic than ADC or T2 alone.

Impact: The different ROI positioning methods used had a significant impact on the quantitative measurements and the performance in differentiating benign from malignant breast tumors.

Keywords: Breast, Breast, diffusion magnetic resonance imaging; deep learning, Magnetic resonance imaging; kaiser score

Motivation: While the Kaiser score serves a pivotal role in diagnosing breast cancer, it still encounters scenarios where false positives necessitate biopsy confirmation.

Goal(s): This study aims to investigate approaches to enhance the diagnostic efficacy of the Kaiser score through MRI.

Approach: Leveraging deep learning to enhance both the quality of DWI images and diagnosis, we sought more effective indicators in conjunction with the Kaiser score.

Results: ADC values derived from DWI images reconstructed using deep learning, with a b-value of 800 s/mm², in tandem with the Kaiser score, significantly enhance the diagnostic performance nearing 1.

Impact: Integrating DWI under deep learning with the Kaiser score can elevate the accuracy of differentiating between benign and malignant breast cancers to almost 100%, leading to substantial improvements in breast cancer diagnosis and a reduction in unnecessary biopsies.

Keywords: fMRI Acquisition, Breast, Amide proton transfer weighted imaging, Diffusion kurtosis imaging

Motivation: Breast Imaging Reporting and Data System (BI-RADS) is an internationally recognized scoring standard for the diagnosis of breast lesions, but it is highly subjective.

Goal(s): To evaluate the diagnostic performance of amide proton transfer weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in terms of differentiating breast lesions and to compare them with the BI-RADS independently or jointly.

Approach: Prospective cohort study

Results:  APTWI and DKI can be used to distinguish  breast lesions. The combination with APTWI and DKI can significantly improve the AUC values and specificity when compared with BI-RADS alone. The APTWI+DKI+BI-RADS has the best diagnostic performance in distinguishing  breast lesions.

Impact: The combined APTWI and DKI outperformed BI-RADS alone in distinguishing benign and malignant breast lesions.

Keywords: fMRI Analysis, Breast, Cancer

Motivation: APTWI and DWI had still some controversies between their parameters and some biological status.

Goal(s): To assess the value of amide proton transfer-weighted imaging (APTWI) and diffusion weighted imaging (DWI) in differentiating biological subtypes and predicting the biological status of breast tumors.

Approach: The Kruskal-Wallis H test and Post-hoc pairwise comparison, Pearson's correlation analysis. Independent samples t-test. Receiver operating characteristic (ROC) analysis.
 

Results: MTRasym (3.5 ppm) was higher in breast tumours that were TN, ER-, PR-, and high-Ki-67. Compared to DWI, APTWI is more useful in predicting the biological status of breast cancers.

Impact:  Compared to DWI, APTWI is more useful in predicting the biological status of breast cancers.

Keywords: Breast, Cancer

Motivation: DWI’s challenging spatial resolution could be addressed by deep-learning-based image reconstruction, by reducing noise without increasing acquisition time.

Goal(s): To compare the image quality of the Echo-Planar-Imaging-Deep-Learning (EPI-DL) DWI sequence with the clinically used simultaneous-multi-slice (SMS) RESOLVE in breast lesions.

Approach: EPI-DL and RESOLVE breast images from 20 participants were qualitatively evaluated ed. Quantitative image quality metrics of SNR and CNR on both high b-value (b800) images and ADC maps were calculated.

Results: SNR in RESOLVE vs. EP-DL differed statistically significantly in manually delineations for b800 (p=0.006), ADC maps (p=0.001), and in ADC circularly delineations (p=0.001).

Impact: DWI-DL reconstruction may be clinically useful for addressing low-spatial resolution without compromising acquisition time and image quality. Such benefits coupled with the available methods of readout segmentation and SMS acquisitions may further enhance the value of DWI in breast imaging.

Keywords: Breast, Breast

Motivation: Noninvasive imaging methods capable of revealing molecular characteristic heterogeneity in breast cancer may help to compensate for the sampling errors of biopsy and guide tailored treatment.
  

Goal(s): To explore the value of T1ρ mapping in preoperatively predicting the status of ER, PR, HER-2 and Ki-67 in breast cancer.

Approach: This is a prospective diagnostic study. The differences of T1ρ values of tumors with different status of ER, PR, HER-2 and Ki-67 were compared between groups.

Results: The T1ρ values showed significant differences in ER (P<0.01), PR(P=0.01), HER-2 (P=0.04), and Ki-67(P=0.02) negative and positive groups, with respective AUCs of 0.867, 0.79, 0.77, and 0.75.

Impact: T1ρ mapping is expected to be a non-invasive tool to help evaluate ER, PR, HER-2, and Ki-67 status before surgery in breast cancer, and to provide assistance in individualized treatment.

Keywords: Segmentation, Machine Learning/Artificial Intelligence, Fibroglandular tissue; Background parenchymal enhancement; Breast cancer

Motivation: Fully automatic segmentation of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE) quantification methods with high generalizability for different FGT levels are still lacking.

Goal(s): We aimed to improve the segmentation accuracy and generalizability across various FGT levels that accurately quantify FGT density and BPE.

Approach: A novel anatomy-aware loss function based on the variations in FGT level was applied in a fully automatic segmentation model training on breast MRIs.

Results: The accuracy of breast tissue segmentation, FGT density estimation, and BPE quantification were improved at various FGT levels.

Impact: The anatomy-aware loss function can help improve the generalization of the breast tissue segmentation model on patients with different breast densities, thereby enabling the model to be more widely used in fibroglandular tissue density estimation and background parenchymal enhancement quantification.

Keywords: Breast, Breast, CEST, CEST-MRF, DRONE

Motivation: To enable quantitative CEST and MT maps in breast tissue for potential tumor characterization.

Goal(s): To explore the feasibility of simultaneously obtaining T1, T2, CEST and MT maps in breast tissue.

Approach: A CEST-MRF pulse sequence was used to measure the amide and semi-solid exchange rate and volume fractions. Quantitative maps were obtained using a neural network trained on physics-derived signals.

Results: The proposed approach yields water T1 and T2 relaxation maps, amide exchange and volume fraction maps, and semi-solid exchange and volume fraction maps in the breast in a scan time of less than 2 minutes.

Impact: Comprehensive quantitative T1, T2, amide CEST and MT bilateral breast imaging in under 2 minutes can improve the detection and characterization of breast cancer and the response to treatment in a clinical setting without the use of a contrast agent.

Keywords: Breast, Cancer, sodium, breast, inversion recovery, DCE-MRI

Motivation: Breast cancer MRI has high sensitivity but has an unmet need for increased specificity. Sodium MRI has the potential to improve tumor characterisation and thus treatments.

Goal(s): To determine whether there is a relationship between tissue permeability by correlating intracellular sodium fraction with pharmacokinetic parameters.

Approach: Conventional DCE-MRI parameters were acquired as well as intracellular sodium fraction maps (= inversion recovery sodium / total sodium concentration) in 17 breast cancer lesions (grade 1:n=3; grade 2: n=9; grade 3:n=7).

Results: The fraction of intracellular sodium to total sodium concentration had significant correlations (p-values <0.11) with K_trans and k_ep, and with cancer grade.

Impact: Breast cancer imaging has an unmet need to differentiate ductal carcinoma from benign and invasive lesions. Sodium MRI can provide intra- and extra-cellular sodium measurements, which may improve lesion differentiation by using endogenous contrast.

Keywords: Software Tools, Breast, background parenchymal enhancement

Motivation: Background parenchymal enhancement (BPE) is linked to cancer treatment outcomes. Unfortunately field strength, acquisition parameters, etc, influence BPE. More reliable methodology is needed.

Goal(s): We tested a novel BPE measure as contrast concentration to differentiate patient groups. Test1: pathologically complete response after neo-adjuvant therapy vs incomplete response. Test 2: pre- vs post-menopause.

Approach: From a large public imaging archive we randomly selected 32 exams each for Tests 1-2 to compare effect sizes for signal and concentration-based BPE.
 

Results: For both tests, group effects measured using Cohen-d were 2X larger for concentration-based BPE. BPE robustness is improved by converting MR signal to contrast concentration

Impact: Background parenchymal enhancement (BPE) is linked to cancer treatment outcomes. Unfortunately field strength, acquisition parameters, etc, influence conventionally acquired BPE. We propose and validate, using two independent datasets, a more reliable BPE methodology based on quantitative measurement of contrast concentration.

Keywords: Breast, Breast

Motivation: Elevated interstitial fluid pressure (IFP) or reduction in velocity (IFV) in breast cancer patients has been shown to contribute to treatment resistance, but its measurement is impractical in clinical practice.

Goal(s): Our goal is to map IFP and IFV from DCE breast MRI and to evaluate its association with treatment response.

Approach: We developed pharmacokinetic-fluid flow models to evaluate its association between IFP, IFV and neoadjuvant chemotherapy (NAC) responses.

Results: We observed small differences in IFP and IVF between NAC treatment cohorts. Initial data based on pre-NAC DCE-breast MRI suggest a potential for early prediction of treatment response of primary tumors.

Impact: Non-invasive pharmacokinetic and computational fluid dynamics modeling in breast DCE-MRI can provide information of tumor IFP and IFV. This approach has the potential to serve as a valuable non-invasive clinical tool for predicting early treatment response.

Keywords: Liver, Liver

Motivation: Liver metastases with contrast uptake on hepatobiliary phase images in patients with pancreatic ductal adenocarcinoma (PDAC) were related to poor prognosis. Prior study focused on visual assessment of the tumor, however, reliable quantitativeness is necessary.

Goal(s): To evaluate the relationship between the gadoxetic acid uptake in liver metastases and overall survival (OS) in patients with PDAC using histogram analysis.

Approach: The best quantitative parameter was analyzed comparable with visual assessment using receiver operating characteristic curve analysis.

Results: Patients with the entropy of >5.422 in the greatest liver metastasis exhibited lower OS rates than those with ≤5.422 (mean, 9.6 months vs 37.7 months).

Impact: Liver metastases with contrast uptake on hepatobiliary phase images were related to poor prognosis. Entropy on histogram features in the greatest liver metastasis can be a potential quantitative imaging biomarker to predict overall survival in patients with pancreatic ductal adenocarcinoma.

Keywords: Liver, Cancer

Motivation: Looking for an economical and convenient magnetic resonance imaging technique to detect whether hepatocellular carcinoma is complicated with venous tumor thrombi.

Goal(s): Using a 5.0T ultra-high field MRI imaging sequence to detect the presence of cancer thrombi in HCC patients without the use of contrast agents.

Approach: Statistical analysis of the accuracy of magnetic sensitivity weighted imaging (SWI) in the diagnosis of cancer thrombi using enhanced scanning as the diagnostic criteria.

Results: SWI has high diagnostic accuracy for cancer thrombi without the use of contrast agents.

Impact: Whether HCC with thrombi is crucial for determining clinical treatment plans. Some patients may not be able to use contrast agents, and the cost of contrast agents is high. SWI can effectively display tumor thrombi,  and can reduce patient costs.

Keywords: Cancer, Cancer, PDAC

Motivation: The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) creates an urgent need to identify new targets. PDAC is a metabolically active cancer that is glutamine avid.

Goal(s): We downregulated the glutamine transporter, SLC1A5, in the patient-derived human cancer cell line, Pa04C, and observed significant tumor growth delay.

Approach: High-field, high-resolution ¹H MRS was performed of extracts from wild type, empty vector, and SLC1A5 downregulated tumors that was mapped to transcriptomic analysis of the corresponding cells, and to mass spectrometry imaging (MSI) of human normal and PDAC tissue.

Results: Common pathways were identified from the analysis that identify new targets for PDAC.

Impact: This study contributes to our comprehension of how the glutamate transporter SLC1A5 impacts the transcriptomics of pancreatic cancer cells, influences tumor metabolism, and its connection to variations in human PDAC metabolism. These findings could provide new insights into PDAC cancer.

Keywords: fMRI Analysis, Cancer

Motivation: The T staging of rectal cancer mainly relies on high-resolution T2-weighted MRI sequences. However, there are cases of both over-staging and under-staging.

Goal(s): To investigate the preliminary application value of quantitative susceptibility mapping in the T staging of rectal cancer.

Approach: In addition to the conventional scanning sequences, horizontal axial T2-weighted imaging (T2WI) and QSM sequences were acquired. The tumor segmentation was done with reference to T2WI images at the QSM-weighted image. The magnetic susceptibility histogram data of tumor tissues were calculated with FireVoxel build 394D software.

Results: The differences of magnetic susceptibility histogram parameters in different T-stage rectal cancer were statistically significant.

Impact: Quantitative susceptibility histogram shows promise in aiding the T staging of rectal cancer.

Keywords: fMRI Analysis, Bladder

Motivation: The evaluation of muscular invasion in bladder cancer is essential for determining the optimal surgical approach for patients¹. The application of Synthetic magnetic resonance imaging (MAGic resonance imaging, MAGiC) in assessing muscular invasion has not been reported previously².

Goal(s): To assess the value of MAGiC in diagnosing muscular invasion in bladder cancer.

Approach: This study evaluated the differences of T1/T2/ADC and VI-RADS between non-muscle invasive and muscle invasive lesions and the differentiation performance of the indices. 

Results: Improved diagnosis performance was obtained with combined T2 relaxometry and VI-RADS in compared with each single index.

Impact: The findings of this study demonstrate that quantitative MRI parameters enhance the precision and objectivity of assessing muscular invasion in bladder cancer, exhibiting minimal dependence on the clinical experience of diagnostic physician, thus holding promise for their wide-ranging application.