SpinFlowSim: A blood flow simulation framework for histology-informed diffusion MRI microvasculature mapping in cancer

Medical Image Analysis, Journal Year: 2025, Volume and Issue: 102, P. 103531 - 103531

Published: March 7, 2025

Diffusion Magnetic Resonance Imaging (dMRI) sensitises the MRI signal to spin motion. This includes Brownian diffusion, but also flow across intricate networks of capillaries. effect, intra-voxel incoherent motion (IVIM), enables microvasculature characterisation with dMRI, through metrics such as vascular fraction fV or Apparent Coefficient (ADC) D∗. The IVIM metrics, while sensitive perfusion, are protocol-dependent, and their interpretation can change depending on regime spins experience during dMRI measurements (e.g., diffusive vs ballistic), which is in general not known for a given voxel. These facts hamper practical clinical utility, innovative models needed enable vivo calculation biologically meaningful markers capillary flow. could have relevant applications cancer, assessment response anti-angiogenic therapies targeting tumour vessels. paper tackles this need by introducing SpinFlowSim, an open-source simulator signals arising from blood within pipe networks. tailored laminar patterns capillaries, synthesis highly-realistic microvascular signals, reconstructed histology. We showcase generating synthetic 15 networks, liver biopsies, containing cancerous non-cancerous tissue. Signals exhibit complex, non-mono-exponential behaviours, consistent patterns, pointing towards co-existence different regimes same network, well diffusion time dependence. demonstrate potential utility SpinFlowSim devising strategy property mapping informed focussing quantification velocity distribution moments apparent network branching index. were estimated silico vivo, healthy volunteers scanned at 1.5T 3T 13 cancer patients, 1.5T. In conclusion, realistic simulations, those enabled may play key role development next-generation methods mapping, immediate oncology.

Language: Английский

---

Metrology for MRI: the field you’ve never heard of

Magnetic Resonance Materials in Physics Biology and Medicine, Journal Year: 2025, Volume and Issue: unknown

Published: March 19, 2025

Quantitative MRI has been an active area of research for decades and produced a huge range approaches with enormous potential patient benefit. In many cases, however, there are challenges reproducibility which have hampered clinical translation. is form measurement like any other it requires supporting metrological framework to be fully consistent compatible the international system units. This means not just expressing results in terms seconds, meters, etc., but demonstrating consistency their internationally recognized definitions. Such yet complete, considerable amount work done towards building one. article describes current state art metrology, including detailed description principles how they relevant quantitative MRI. It also undertakes gap analysis where we versus need support focusses particularly on role activities national institutes across globe, illustrating genuinely collaborative nature field.

Language: Английский

---

Advanced diffusion-weighted imaging biomarkers for non-invasive assessment of tumor microenvironment in rectal cancer: restricted spectrum imaging

Abdominal Radiology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Language: Английский

---

Histogram analysis of continuous-time random walk and restrictive spectrum imaging for identifying hepatocellular carcinoma and intrahepatic cholangiocarcinoma

Frontiers in Oncology, Journal Year: 2025, Volume and Issue: 15

Published: March 10, 2025

Background To compare the ability and potential additional value of various diffusion models, including continuous-time random walk (CTRW), restrictive spectrum imaging (RSI), diffusion-weighted (DWI), as well their associated histograms, in distinguishing pathological subtypes liver cancer. Methods 40 patients with cancer were included this study. Histogram metrics derived from CTRW (D, α, β), RSI (f 1 , f 2 3 ), DWI (ADC) parameters across entire tumor volume. Statistical analyses Chi-square test, independent samples t-test, Mann-Whitney U ROC, logistic regression, Spearman correlation. Results Patients hepatocellular carcinoma exhibited higher values median 20th 40th 60th compared to intrahepatic cholangiocarcinoma, whereas D mean 80th percentiles lower (P<0.05). Among individual histogram parameters, percentile demonstrated highest accuracy (AUC = 0.717). Regarding combined single total model best diagnostic performance 0.792). Although showed efficacy than 0.731, 0.717), combination further improved 0.787), achieving superior sensitivity specificity (sensitivity 0.72, 0.80). Conclusion CTRW, RSI, corresponding distinguish between Moreover, whole-lesion provided more comprehensive statistical insights alone.

Language: Английский

---

Editorial for “Evaluating the Diagnostic Performance of MR Cytometry Imaging in Differentiating Benign and Malignant Breast Tumors”

Journal of Magnetic Resonance Imaging, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Language: Английский

---

Cluster Analysis of VERDICT MRI for Cancer Tissue Characterization in Neuroendocrine Tumors

NMR in Biomedicine, Journal Year: 2025, Volume and Issue: 38(6)

Published: April 28, 2025

ABSTRACT Diffusion MRI models accounting for varying diffusion times and high b‐values, such as VERDICT, hold potential non‐invasively characterizing tumor tissue types, potentially enabling improved grading, treatment evaluation. Furthermore, cluster analysis can aid in identifying multidimensional patterns the (dMRI) data that are not apparent when analyzing individual parameters isolation. The aim of this study was to evaluate how well VERDICT be used intratumor characterization compared ADC a mouse model human small intestine neuroendocrine (GOT1), validate method by histological analysis. Mice implanted with GOT1 were irradiated subsequently imaged using dMRI protocol designed estimation values. Histological hematoxylin eosin (H&E), Masson's trichrome, Ki67 staining identified three distinct types: necrotic, fibrotic, viable tissue. ROIs drawn on regions low ADC, which spatially matched necrosis or fibrosis, tissue, respectively. Among parameters, cell radius index ( R ) most effective distinguishing between necrotic fibrotic whereas intracellular fraction f IC differentiating from non‐viable A Gaussian mixture (GMM) clusters, representing each type, fitted all voxel data. maps corresponded histology classification overall. Fibrotic best , intermediate . In conclusion, GMM shows tumors.

Language: Английский

---

A Systematic Review of Diffusion Microstructure Imaging (DMI): Current and Future Applications in Neurology Research

Brain Disorders, Journal Year: 2025, Volume and Issue: unknown, P. 100238 - 100238

Published: May 1, 2025

Language: Английский

---

Time-dependent diffusion magnetic resonance imaging: measurement, modeling, and applications

Journal of Zhejiang University. Science A, Journal Year: 2024, Volume and Issue: 25(10), P. 765 - 787

Published: Aug. 22, 2024

Language: Английский

---

Advanced breast diffusion-weighted imaging: what are the next steps? A proposal from the EUSOBI International Breast Diffusion-weighted Imaging working group

European Radiology, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 8, 2024

Abstract Objectives This study by the EUSOBI International Breast Diffusion-weighted Imaging (DWI) working group aimed to evaluate current and future applications of advanced DWI in breast imaging. Methods A literature search a comprehensive survey members explore clinical use potential techniques were involved. Advanced approaches such as intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), tensor (DTI) assessed for their status challenges implementation. Results Although revealed an increasing number publications growing academic interest DWI, limited adoption among members, with 32% using IVIM models, 17% non-Gaussian analysis, only 8% DTI. variety are used, being most popular, but less than half it, suggesting that identified gap between benefits its actual practice. Conclusion The findings highlight need further research, standardization simplification transition from research tool regular practice concludes guidelines recommendations directions implementation, emphasizing importance interdisciplinary collaboration this field improve cancer diagnosis treatment. Clinical relevance statement imaging, while currently use, offers promising improvements diagnosis, staging, treatment monitoring, highlighting standardized protocols, accessible software, collaborative promote broader integration into routine Key Points Increasing on over last decade indicates . shows is used primarily not extensively More needed integrate

Language: Английский

---

Histology-informed liver diffusion MRI: relevance in cancer immunotherapy

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: April 29, 2024

Abstract Innovative diffusion Magnetic Resonance Imaging (dMRI) models enable the non-invasive measurement of cancer biological properties in vivo . However, while cancers frequently spread to liver, tailored for liver application and easy deploy clinic are still sought. We fill this gap by delivering a practical, clinically-viable dMRI framework tumour imaging, informing its design through histology. By comparing histological data from mice patients, we select signal model restricted intra-cellular with negligible extra-cellular contributions, maximising radiological-histological correlations. The enables phenotyping, providing cell size density estimates that i) correlate their histopathology counterparts, ii) associated proliferation volume, iii) distinguish types. metrics biologically meaningful, our approach may complement standard-of-care radiology, become new tool enhanced characterisation precision oncology.

Language: Английский

---