[1] |
Gillies RJ, Balagurunathan Y. Perfusion MR imaging of breast cancer: insights using "habitat imaging". Radiology 2018; 288:36-37.
doi: 10.1148/radiol.2018180271
pmid: 29714676
|
[2] |
Wu J, Cao G, Sun X, Lee J, Rubin DL, Napel S, et al. Intratumoral spatial heterogeneity at perfusion MR imaging predicts recurrence-free survival in locally advanced breast cancer treated with neoadjuvant chemotherapy. Radiology 2018; 288:26-35.
doi: 10.1148/radiol.2018172462
pmid: 29714680
|
[3] |
Juan-Albarracin J, Fuster-Garcia E, Perez-Girbes A, Aparici-Robles F, Alberich-Bayarri A, Revert-Ventura A, et al. Glioblastoma: vascular habitats detected at preoperative dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging predict survival. Radiology 2018; 287:944-954.
doi: 10.1148/radiol.2017170845
pmid: 29357274
|
[4] |
Gatenby RA, Grove O, Gillies RJ. Quantitative imaging in cancer evolution and ecology. Radiology 2013; 269:8-15.
doi: 10.1148/radiol.13122697
pmid: 24062559
|
[5] |
Kazerouni AS, Hormuth DA, Davis T, Bloom MJ, Mounho S, Rahman G, et al. Quantifying tumor heterogeneity via MRI habitats to characterize microenvironmental alterations in HER2+ breast cancer. Cancers (Basel) 2022;14.
|
[6] |
Sala E, Mema E, Himoto Y, Veeraraghavan H, Brenton JD, Snyder A, et al. Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging. Clin Radiol 2017; 72:3-10.
doi: S0009-9260(16)30373-7
pmid: 27742105
|
[7] |
Cho HH, Kim H, Nam SY, Lee JE, Han BK, Ko EY, et al. Measurement of perfusion heterogeneity within tumor habitats on magnetic resonance imaging and its association with prognosis in breast cancer patients. Cancers (Basel) 2022;14.
|
[8] |
Bailo M, Pecco N, Callea M, Scifo P, Gagliardi F, Presotto L, et al. Decoding the heterogeneity of malignant gliomas by PET and MRI for spatial habitat analysis of hypoxia, perfusion, and diffusion imaging: a preliminary study. Front Neurosci 2022;16:885291.
|
[9] |
Carvalho ED, da Silva Neto OP, Mathew MJ, de Carvalho Filho AO. An approach to the prediction of breast cancer response to neoadjuvant chemotherapy based on tumor habitats in DCE-MRI images. Expert Systems with Applications 2023;234:121081.
|
[10] |
Sujit SJ, Aminu M, Karpinets TV, Chen P, Saad MB, Salehjahromi M, et al. Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights. Nat Commun 2024; 15:3152.
doi: 10.1038/s41467-024-47512-0
pmid: 38605064
|
[11] |
Errico C, Pierre J, Pezet S, Desailly Y, Lenkei Z, Couture O, et al. Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging. Nature 2015; 527:499-502.
|
[12] |
Sloun RJGv, Solomon O, Bruce M, Khaing ZZ, Eldar YC, Mischi M. Deep learning for super-resolution vascular ultrasound imaging. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2019; p1055-1059.
|
[13] |
Sloun RJGv, Solomon O, Eldar YC, Wijkstra H, Mischi M. Sparsity-driven super-resolution in clinical contrast-enhanced ultrasound. 2017 IEEE International Ultrasonics Symposium (IUS) 2017; p1-4.
|
[14] |
Zheng Y, Zhou J. Deep learning in ultrasound localization microscopy. Advanced Ultrasound in Diagnosis and Therapy 2024; 8:86-92.
|
[15] |
Shi Z, Huang X, Cheng Z, Xu Z, Lin H, Liu C, et al. MRI-based quantification of intratumoral heterogeneity for predicting treatment response to neoadjuvant chemotherapy in breast cancer. Radiology 2023; 308:e222830.
|
[16] |
Bernatowicz K, Grussu F, Ligero M, Garcia A, Delgado E, Perez-Lopez R. Robust imaging habitat computation using voxel-wise radiomics features. Sci Rep 2021; 11:20133.
doi: 10.1038/s41598-021-99701-2
pmid: 34635786
|
[17] |
Wu Y, Xu W. Habitat imaging with radiomics for predicting lung cancer invasiveness on CT: deeper biologic insight needed. AJR Am J Roentgenol 2025. doi: 10.2214/AJR.24.32500.
|
[18] |
Chen L, Liu K, Zhao X, Shen H, Zhao K, Zhu W. Habitat imaging-based (18)F-FDG PET/CT radiomics for the preoperative discrimination of non-small cell lung cancer and benign inflammatory diseases. Front Oncol 2021; 11:759897.
|
[19] |
Rauch GM. Precision imaging: one step closer to pretreatment prediction of breast cancer response to neoadjuvant systemic therapy. Radiology 2023; 308:e231482.
|
[20] |
da Silva Neto OP, Araujo JDL, Caldas Oliveira AG, Cutrim M, Silva AC, Paiva AC, et al. Pathophysiological mapping of tumor habitats in the breast in DCE-MRI using molecular texture descriptor. Comput Biol Med 2019; 106:114-125.
doi: S0010-4825(19)30015-0
pmid: 30711799
|
[21] |
Du T, Zhao H. Habitat analysis of breast cancer-enhanced MRI reflects BRCA1 mutation determined by immunohistochemistry. Biomed Res Int 2022; 2022:9623173.
|
[22] |
Wu H, Tong H, Du X, Guo H, Ma Q, Zhang Y, et al. Vascular habitat analysis based on dynamic susceptibility contrast perfusion MRI predicts IDH mutation status and prognosis in high-grade gliomas. Eur Radiol 2020; 30:3254-3265.
doi: 10.1007/s00330-020-06702-2
pmid: 32078014
|
[23] |
Zhang Y, Chen J, Yang C, Dai Y, Zeng M. Preoperative prediction of microvascular invasion in hepatocellular carcinoma using diffusion-weighted imaging-based habitat imaging. Eur Radiol 2024; 34:3215-3225.
|
[24] |
Xia S, Zheng Y, Hua Q, Wen J, Luo X, Yan J, et al. Super-resolution ultrasound and microvasculomics: a consensus statement. Eur Radiol 2024; 34:7503-7513.
|
[25] |
Opacic T, Dencks S, Theek B, Piepenbrock M, Ackermann D, Rix A, et al. Motion model ultrasound localization microscopy for preclinical and clinical multiparametric tumor characterization. Nat Commun 2018; 9:1527.
doi: 10.1038/s41467-018-03973-8
pmid: 29670096
|
[26] |
Song P, Rubin JM, Lowerison MR. Super-resolution ultrasound microvascular imaging: is it ready for clinical use? Z Med Phys 2023; 33:309-323.
doi: 10.1016/j.zemedi.2023.04.001
pmid: 37211457
|
[27] |
Zhang G, Lei YM, Li N, Yu J, Jiang XY, Yu MH, et al. Ultrasound super-resolution imaging for differential diagnosis of breast masses. Front Oncol 2022; 12:1049991.
|
[28] |
Li J, Chen L, Wang R, Zhu J, Li A, Li J, et al. Ultrasound localization microscopy in the diagnosis of breast tumors and prediction of relevant histologic biomarkers associated with prognosis in humans: the protocol for a prospective, multicenter study. BMC Med Imaging 2025; 25:13.
doi: 10.1186/s12880-024-01535-7
pmid: 39780089
|
[29] |
Zeng QQ, An SZ, Chen CN, Wang Z, Liu JC, Wan MX, et al. Focal liver lesions: multiparametric microvasculature characterization via super-resolution ultrasound imaging. Eur Radiol Exp 2024; 8:138.
|
[30] |
Zhu J, Zhang C, Christensen-Jeffries K, Zhang G, Harput S, Dunsby C, et al. Super-resolution ultrasound localization microscopy of microvascular structure and flow for distinguishing metastatic lymph nodes - an initial human study. Ultraschall Med 2022; 43:592-598.
doi: 10.1055/a-1917-0016
pmid: 36206774
|
[31] |
Andersen SB, Taghavi I, Hoyos CAV, Sogaard SB, Gran F, Lonn L, et al. Super-resolution imaging with ultrasound for visualization of the renal microvasculature in rats before and after renal ischemia: a pilot study. Diagnostics (Basel) 2020;10.
|
[32] |
Zhao S, Hartanto J, Joseph R, Wu CH, Zhao Y, Chen YS. Hybrid photoacoustic and fast super-resolution ultrasound imaging. Nat Commun 2023; 14:2191.
doi: 10.1038/s41467-023-37680-w
pmid: 37072402
|