Keywords: Microstructure, Diffusion/other diffusion imaging techniques, microstructure, IMPULSED

Motivation: The intraoperative frozen sections have shortcomings in distinguishing between high-grade serous ovarian cancer (HGSOC) and serous borderline ovarian tumor (SBOT). Time-dependent diffusion MRI (t_d-dMRI) can depict the microstructural parameters of tumors and might play a role in preoperative differentiation of HGSOC from SBOT.

Goal(s): To investigate the value of t_d-dMRI in discriminating HGSOC from SBOT.

Approach: T_d-dMRI uses the combination of oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE) sequences. T_d-dMRI signals were fitted by the IMPULSED model, to extract microstructural parameters. The diagnostic performance was evaluated.

Results: Microstructural parameters derived from t_d-dMRI had good diagnostic performance in differentiating HGSOC from SBOT.

Impact: Time-dependent diffusion MRI can depict the microstructural parameters of tumors. It may further assist in preoperative diagnosis and treatment decision-making in clinical practice in the future.

Keywords: DWI/DTI/DKI, Diffusion/other diffusion imaging techniques, Magnetic resonance imaging; Diffusion weighted imaging; Lung; Pulmonary lesions

Motivation: DWI has been used for pulmonary lesion assessment. But clinical single-shot (SS) EPI DWI for lung is prone to susceptibility distortions. FOCUS SS, MUSE, and FOCUS MUSE are improved EPI-based techniques which are less sensitive to susceptibility artifacts. However, their performance for lung DWI remains unknown.

Goal(s): Performance comparison among the four sequences for lung DWI.

Approach: 44 patients were recruited, and each was imaged with the four sequences. Image quality and diagnostic performance of benign and malignant lesion discrimination were compared.

Results: FOCUS MUSE had least distortions and best diagnostic performance.

Impact: Application of FOCUS MUSE would be beneficial for lung lesion assessment.

Keywords: Microstructure, Diffusion/other diffusion imaging techniques, apparent diffusion coefficient; MRI; breast lesions

Motivation: Time-dependent diffusion MRI (dMRI), thanks to its distinct advantages in characterizing tissue microstructure, has gained increasing popularity in clinical research in recent years.

Goal(s): However, its potential for distinguishing breast lesions remains uncertain.

Approach: The present study was conducted to compare the diagnostic performance of time-dependent dMRI parameters and ADC metrics derived from conventional DWI for breast lesions.

Results: The study results suggest that microstructural parameters based on time-dependent dMRI are superior to conventional DWI measurements in diagnosing breast lesions, and that the addition of time-dependent dMRI parameters improves the performance of conventional DWI in differentiating breast lesions.

Impact: Herein, the microstructural characteristics of breast lesions were investigated using time-dependent dMRI technique and compared with conventional DWI. It was found that that adding time-dependent dMRI parameters could improve the performance of conventional DWI in the diagnosis of breast cancer.

Keywords: Microstructure, Prostate

Motivation: VERDICT diffusion imaging and modelling for prostate cancer characterisation requires significant scan time which hinders its clinical practicality.

Goal(s): We aim to reduce the scan time requirement of VERDICT through paired model simplification and acquisition reduction whilst retaining model fitting accuracy and diagnostic performance.

Approach: We evaluated the model fitting accuracy and diagnostic performance of three simplified VERDICT schemes on 97 patients who underwent targeted biopsy.

Results: Our results demonstrate that a scan time reduction of ≈30% can be achieved with minimal impact to performance; model parameters were recovered with <5% mean bias and no significant change in diagnostic performance was observed.

Impact: Reducing the scan time of VERDICT diffusion imaging could help to enable integration of VERDICT into clinical practice which could help to reduce the number of healthy men referred for biopsy.

Keywords: Microstructure, Prostate, Time-dependent diffusion magnetic resonance imaging; microstructure;transition zone

Motivation: Time-dependent diffusion MRI (td-dMRI) has the potential to characterize the microstructure mapping of tissue in vivo.

Goal(s):  Whether it can benefit accurate and accessible risk stratification for prostate cancer especially in trasition zone has not been established.

Approach: In this study, patients who underwent prostate MRI including td-dMRI were enrolled. Correlation between the td-dMRI-based microstructural parameters and International Society of Urological Pathology grade groups (ISUP GG) were investigated and their performance in discriminating clinically significant prostate cancer (csPCa) from indolent disease was also evaluated. 

Results: The results showed that Td-dMRI measurements has good differential diagnostic power, and cellularity achieved the highest diagnostic performance.
 

Impact: Time-dependent diffusion MRI–derived microstructural parameters showed high discrimination between clinically significant prostate cancer from indolent disease in the transition zone, which might thereby add an extra dimension in the development of prostate cancer biomarkers.

Keywords: IVIM, Diffusion/other diffusion imaging techniques, IVIM，MRI, breast tumor, the HER2 factor, habitats

Motivation: Besides immunohistochemistry, a non-invasive method based on tumor habitats is worth exploring. It predicted the expression of HER2 factor in malignant breast cancer. 

Goal(s): We determined whether a prediction model, which was based on tumors habitats, could be used to predict the expression of HER2 factor. 

Approach: A predictive model based on tumors habitats was developed and used to diagnose HER2 status. The IVIM-based imaging technique could extract features. 

Results: The model of tumor habitats predicted the expression of HER2 factor in breast cancer by using the following parameters: AUC of 0.902, sensitivity of 0.709, and specificity of 0.909.

Impact: In this experiment, a predictive model based on features of habitats could determine the expression of HER2 factor in patients with malignant breast cancer. Thus, this non-invasive approach is a better treatment option in clinical practice.

Keywords: IVIM, Microstructure

Motivation: Multi-exponential signal analysis is utilised to identify underlying present diffusion components in diffusion-weighted MRI signals. Various techniques emerged in recent years, but a detailed in-vivo comparison of the fitting approaches employed in the kidney is still missing.

Goal(s): Thus, we comparatively applied frequently used fitting methods and novel techniques towards precise in-vivo appliance.

Approach: The study comprised 15 healthy volunteers, intended for comparison with tumour patients. Besides NLLS and NNLS techniques, the pyramidal approach was employed

Results: Results demonstrated improvements for renal in-vivo data, a distinction between cortex and medulla was also accomplished. These encouraging findings conduct further investigations and comparison with pathologies

Impact: Identifying the most reliable and stable MEDIA approaches will pave the way for novel techniques. These advancements will enhance in-vivo applications, potentially allowing to distinguish between healthy and diseased tissue, recognise pathologies and long-term replace the need for biopsies.

Keywords: Diffusion Acquisition, Digestive, ADC, clinicopathological, microsatellite instability, colorectal neoplasm

Motivation: Given that microsatellite instability (MSI) detection often involves invasive pathological biopsies, it is of paramount importance to find a non-invasive, individualized detection technology for accurately and effectively predicting the MSI status of colorectal cancer (CRC) patients prior to surgery. This approach could mitigate the limitations associated with biopsies and enhance the treatment of CRC patients.

Goal(s): To investigate the value of MRI-ADC mean values and clinicopathological features in predicting MSI in colorectal cancer.

Approach: The ADC model and ADC-clinicopathologic nomogram model were established by using MRI-ADC parameters and clinicopathological features.

Results: The combined ADC-clinicopathological nomogram model was the best predictor of CRC MSI.

Impact: Pathological testing for MSI status is often invasive and comes with a higher risk of complications. In contrast, the ADC-clinical combined nomogram model provides a noninvasive, comprehensive tool for preoperative prediction of CRC MSI and for guiding clinical treatment decisions. 

Keywords: Diffusion Modeling, Diffusion/other diffusion imaging techniques

Motivation: The unexplored potential of applying the continuous-time random walk (CTRW) model for clear cell renal cell carcinoma (ccRCC) grading, possibly surpassing the effectiveness of apparent diffusion coefficient (ADC).

Goal(s): To compare ADC and CTRW in diagnosing ccRCC grades via MRI.

Approach: This study involved 52 ccRCC patients and employed in-house software for CTRW and ADC maps. Statistical analysis employed Mann-Whitney U tests and ROC curves.

Results: D_CTRW outperformed ADC in grading ccRCC, effectively distinguishing between low- and high-grade cases, while α_CTRW and β_CTRW did not.

Impact: This research has the potential to shape clinical practices, offering more accurate ccRCC diagnoses, leading to better treatment decisions, and driving advancements in renal cell carcinoma research.

Keywords: Diffusion Modeling, Diffusion/other diffusion imaging techniques, hepatocellular carcinoma, intrahepatic cholangiocarcinoma, stretched-exponential model, fractional order calculus model

Motivation: The traditional apparent diffusion coefficient (ADC) value had limited value in differentiating hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). 

Goal(s):  To evaluate the value of stretched-exponential model (SEM) and fractional order calculus (FROC) diffusion model in differentiating HCC and ICC.

Approach: Parameters from SEM and FROC models and ADC value using multiple b-value DWI data were obtained, and were evaluated using t-test and ROC curve in differential diagnosis of HCC and ICC. 

Results: Distributed diffusion coefficient (DDC) from SEM and diffusion coefficient (D) from FROC had significant differences between HCC and ICC, and had higher performances  than the ADC. 

Impact: DDC from SEM and D from FROC model may be helpful to improve the accuracy of the preoperative imaging diagnosis and guide personalized treatment for liver tumor.

Keywords: DWI/DTI/DKI, Microstructure

Motivation: Microstructural characteristics of intestinal fibrosis is a crucial determinant impacting the selection of therapeutic strategies and prognosis of patients with Crohn’s disease (CD).

Goal(s): To evaluate the feasibility and efficacy of time-dependent diffusion MRI (TD-dMRI) based microstructural mapping for noninvasive characterization of intestinal fibrosis in intestinal strictures in CD.

Approach: TD-dMRI was performed in consecutive CD patients scheduled for surgery. TD-dMRI-based microstructural parameters acquired were compared with conventional apparent diffusion coefficient (ADC) and verified by histopathogical measures.

Results: Multiparametric TD-dMRI-based microstructural mapping correlates with pathological findings and demonstrates promise for characterizing intestinal fibrosis in CD.

Impact: Time-dependent diffusion MRI-based microstructural mapping demonstrates promise for noninvasively characterizing intestinal fibrosis of CD, with high accuracy against histopathologic standard, thus guiding treatment and predicting clinical outcome.

Keywords: DWI/DTI/DKI, Uterus, Endometrial fibrosis; Noninvasive evaluation

Motivation: Patients with endometrial fibrosis suffer from uterine infertility. Evaluating the degree of fibrotic endometrium can help clinicians to select the optimal treatment scheme.

Goal(s): To investigate the value of DWI in distinguishing the degree of endometrial fibrosis.

Approach: Mean intensity and standard deviation of endometrial ADC value in region of interest (ROI) (ADC_ROI and ADC-SD_ROI) and volume of interest (VOI) (ADC_VOI and ADC-SD_VOI) were measured and analyzed between healthy women, mild to moderate endometrial fibrosis (MMEF) patients and severe endometrial fibrosis (SEF) patients.

Results: Endometrial MRI parameters were significantly correlated to the degree of endometrial fibrosis, which can well differentiate each group.

Impact: This prospective study demonstrated the feasibility of DWI for quantitatively evaluating the degree of endometrial fibrosis, which can help clinicians to select the optimal treatment scheme and to perform dynamic follow-ups of therapy effect for patients with endometrial fibrosis.

Keywords: Diffusion Analysis & Visualization, Whole Body, Validation, Melanoma

Motivation: Maximum intensity projections (MIPs) generated from niceDWI could be beneficial as a survey tool in patients with soft-tissue disease, helping to save time in clinical reporting.

Goal(s): Perform a systematic clinical comparison of MIPs generated using niceDWI with MIPs generated using clinical DWI (clinDWI).

Approach: An experienced reader of whole-body MRI scored niceDWI and clinDWI MIPs in 20 patients with metastatic melanoma for SNR, CNR, artifacts, overall quality, and presence of disease in soft-tissues. ROC curves were plotted to assess disease detection.

Results: Image quality metrics were significantly worse in niceDWI, however there was no difference in ROC analysis of disease detection.

Impact: Whole-body MIPs using niceDWI did not improve disease detection in patients with soft-tissue disease, despite improved interstation homogeneity. Motion of soft-tissue lesions may limit SNR of niceDWI thus it may have higher clinical impact in surveillance of bone disease.

Keywords: Microstructure, Diffusion/other diffusion imaging techniques, cervical cancer, immunohistochemistry, time-dependent diffusion MRI, microstructural mapping, oscillating gradient spin-echo

Motivation: Some immunohistochemical (IHC) markers are gradually accepted as vital prognostic factors guiding therapy in cervical cancer (CC).

Goal(s): This study aimed to evaluate the relationship of time-dependent diffusion MRI (t_d-dMRI)-based microstructural mapping and IHC status of CC.

Approach: Quantitative information on cell microstructure are obtained by fitting the IMPULSED model to the t_d-dMRI data.

Results: Intracellular fraction (f_in) and cellularity were significantly correlated with the PD-L1 expression, respectively. In addition, f_in and cellularity were significantly correlated with Ki-67. The results suggested that microstructural mapping might facilitate the establishment of novel diffusion-derived biomarkers to estimate IHC status and orient treatment of CC.

Impact: The td-dMRI-based microstructural mapping showed the potential to estimate the IHC status of cervical cancer for the first time.

Keywords: Microstructure, Tumor

Motivation: Diffusion MRI is a non-invasive imaging method that depicts the water molecule diffusion, but its use for studying peripheral cancers has lagged behind that for deep cancers.

Goal(s): To develop a highly accurate MRI method of peripheral cancer diagnosis that is comparable to biopsy-based diagnosis.

Approach: To determine the differences in diffusion time-dependency between subcutaneous tumor tissues from normal tissues in tumor-bearing mouse models, we utilized a wide range of diffusion times and obtained information about intra- and inter-tumor cell microstructures.

Results: In subcutaneous tumor models, time-dependent diffusion MRI can discriminate tumor tissues and identify cancer cell lines.

Impact: The improved MRI method for non-invasive tumor diagnosis based on time-dependent diffusion MRI not only helps physicians determine the grade of malignancy, but also contributes to early detection by its ability to evaluate microstructures.