Citations

Abstract Non-invasive detection of microvascular alterations in deep tissues in vivo provides critical information for clinical diagnosis and evaluation of a broad-spectrum of pathologies. Recently, the emergence of super-resolution ultrasound localization microscopy (ULM) offers new possibilities for clinical imaging of microvasculature at capillary level. Currently, the clinical utility of ULM on clinical ultrasound scanners is hindered by the technical limitations, such as long data acquisition time, high microbubble (MB) concentration, and compromised tracking performance associated with low imaging frame-rate. Here we present a robust in-human ULM on a high frame-rate (HFR) clinical ultrasound scanner to achieve super-resolution microvessel imaging using a short acquisition time (<10 s). Ultrasound MB data were acquired from different human tissues, including a healthy liver and a diseased liver with acute-on-chronic liver failure, a kidney, a pancreatic tumor, and a breast mass using an HFR clinical scanner. By leveraging the HFR and advanced processing techniques including sub-pixel motion registration, MB signal separation, and Kalman filter-based tracking, MBs can be robustly localized and tracked for ULM under the circumstances of relatively high MB concentration associated with standard clinical MB administration and limited data acquisition time in humans. Subtle morphological and hemodynamic information in microvasculature were shown based on data acquired with single breath-hold and free-hand scanning. Compared with contrast-enhanced power Doppler generated based on the same MB dataset, ULM showed a 5.7-fold resolution improvement in a vessel based on a linear transducer, and provided a wide-range blood flow speed measurement that is Doppler angle-independent. Microvasculatures with complex hemodynamics can be well-differentiated at super-resolution in both normal and pathological tissues. This preliminary study implemented the ultrafast in-human ULM in various human tissues based on a clinical scanner that supports HFR imaging, indicating the potentials of the technique for various clinical applications. However, rigorous validation of the technique in imaging human microvasculature (especially for those tiny vessel structure), preferably with a gold standard, is still required.

Fast super-resolution ultrasound microvessel imaging using spatiotemporal data with deep fully convolutional neural network

Lok, U‐Wai , Tang, Shanshan , Zhang, Wei , Korfiatis, Panagiotis , Blezek, Daniel J. , Zheng, Rongqin , Trzasko, Joshua D. , Chen, Shigao , Gong, Ping , Yang, Lulu, Zhang, Wei , Lok, U-Wai , Huang, Chengwu , Gong, Ping , Yang, Lulu , Kim, Yohan , Lucien, Fabrice

Mayo Clinic

Physics in Medicine & Biology | March 2, 2021 | Volume: 66 | Issue: 7 | Pages: 075005

10.1088/1361-6560/abeb31 | PMID 33652418

Abstract Ultrasound localization microscopy (ULM) has been proposed to image microvasculature beyond the ultrasound diffraction limit. Although ULM can attain microvascular images with a sub-diffraction resolution, long data acquisition time and processing time are the critical limitations. Deep learning-based ULM (deep-ULM) has been proposed to mitigate these limitations. However, microbubble (MB) localization used in deep-ULMs is currently based on spatial information without the use of temporal information. The highly spatiotemporally coherent MB signals provide a strong feature that can be used to differentiate MB signals from background artifacts. In this study, a deep neural network was employed and trained with spatiotemporal ultrasound datasets to better identify the MB signals by leveraging both the spatial and temporal information of the MB signals. Training, validation and testing datasets were acquired from MB suspension to mimic the realistic intensity-varying and moving MB signals. The performance of the proposed network was first demonstrated in the chicken embryo chorioallantoic membrane dataset with an optical microscopic image as the reference standard. Substantial improvement in spatial resolution was shown for the reconstructed super-resolved images compared with power Doppler images. The full-width-half-maximum (FWHM) of a microvessel was improved from 133 μ m to 35 μ m, which is smaller than the ultrasound wavelength (73 μ m). The proposed method was further tested in an in vivo human liver data. Results showed the reconstructed super-resolved images could resolve a microvessel of nearly 170 μ m (FWHM). Adjacent microvessels with a distance of 670 μ m, which cannot be resolved with power Doppler imaging, can be well-separated with the proposed method. Improved contrast ratios using the proposed method were shown compared with that of the conventional deep-ULM method. Additionally, the processing time to reconstruct a high-resolution ultrasound frame with an image size of 1024 × 512 pixels was around 16 ms, comparable to state-of-the-art deep-ULMs.

Abstract 873: Molecular mechanisms of non-small cell lung cancer growth and drug resistance

Astone, Matteo , Liu, Ping , Coyle, Abbygail M. , Dankert, Erin N. , Hoffman, Dane K. , Hall, Stephanie R., Kuang, Rui , Roden, Anja C. , Alam, Sk. Kayum , Wang, Li , Zhang, Wei , Mansfield, Aaron S. , Hoeppner, Luke H.

Mayo Clinic

Cancer Research | August 7, 2019 | Volume: 79 | Issue: 13_Supplement | Pages: 873-873

10.1158/1538-7445.am2019-873

Abstract Lung cancer is the deadliest and most frequently diagnosed type of tumor worldwide, with 1.6 million deaths reported annually. Non-small cell lung cancer (NSCLC) represents 85% of all lung cancer cases and carries a poor 5-year survival rate below 15%. Prognoses remain dismal due to the large number of patients diagnosed with advanced stage disease and the development of resistance to current therapies. A better understanding of acquired drug resistance will help to circumvent the progression of lung cancer and make significant strides in improving NSCLC patient treatment. Our recent work demonstrates that dopamine and cAMP-regulated phosphoprotein, Mr 32000 (DARPP-32) and its amino-terminally truncated splice variant (t-DARPP) promote lung tumor growth in orthotopic mouse models. IHC staining of 62 human lung adenocarcinoma tissues showed that t-DARPP expression is elevated with increasing tumor (T) staging score, which represents the size of the primary tumor and whether it has grown into nearby areas, as a metric of tumor progression and growth. Correspondingly, a computational biology analysis of 513 lung adenocarcinoma patients revealed upregulation of t-DARPP isoform expression correlates with advanced T stage and is associated with poor overall survival. We identified a novel physical interaction between DARPP-32 and inhibitory kappa B kinase-α (IKKα) that promotes NSCLC cell migration through activation of non-canonical NF-κB2 signaling. It has been shown that DARPP-32 overexpression inhibits gefitinib-induced apoptosis in gastric cancer and t-DARPP contributes to the trastuzumab resistance phenotype in breast cancer. Our recent findings suggest DARPP-32 and t-DARPP overexpression in NSCLC promotes resistance to specific molecular targeted inhibitors by enabling tumor cells to evade apoptosis via Akt- and Erk-dependent cell survival mechanisms. Current ongoing studies are focused on manipulating expression of DARPP-32 isoforms in lung tumor cells to prevent resistance to targeted therapies in NSCLC patients. Citation Format: SK Kayum Alam, Matteo Astone, Ping Liu, Li Wang, Abbygail M. Coyle, Erin N. Dankert, Dane K. Hoffman, Stephanie R. Hall, Wei Zhang, Rui Kuang, Anja C. Roden, Aaron S. Mansfield, Luke H. Hoeppner. Molecular mechanisms of non-small cell lung cancer growth and drug resistance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 873.

Abstract 5161: DARPP-32 and t-DARPP promote non-small cell lung cancer growth through regulation of IKKα-dependent cell migration and Akt/Erk-mediated cell survival

Alam, Sk. Kayum , Astone, Matteo , Hall, Stephanie R., Coyle, Abbygail M. , Dankert, Erin N. , Hoffman, Dane K. , Zhang, Wei , Kuang, Rui , Roden, Anja C. , Liu, Ping , Mansfield, Aaron S. , Hoeppner, Luke H.

Mayo Clinic

Cancer Research | August 17, 2018 | Volume: 78 | Issue: 13_Supplement | Pages: 5161-5161

10.1158/1538-7445.am2018-5161

Abstract Lung cancer is the leading cause of cancer-related death worldwide. In this study, we demonstrate that elevated expression of dopamine and cyclic adenosine monophosphate-regulated phosphoprotein, Mr 32000 (DARPP-32) and its truncated splice variant t-DARPP promotes lung tumor growth, while abrogation of DARPP-32 expression in human non-small cell lung cancer (NSCLC) cells reduces tumor growth in orthotopic mouse models. We observe a novel physical interaction between DARPP-32 and inhibitory kappa B kinase-α (IKKα) that promotes NSCLC cell migration through non-canonical nuclear factor kappa-light-chain-enhancer of activated B cells 2 (NF-κB2) signaling. Bioinformatics analysis of 513 lung adenocarcinoma patients reveals elevated t-DARPP isoform expression is associated with poor overall survival. Histopathological investigation of 62 human lung adenocarcinoma tissues also showed that t-DARPP expression is elevated with increasing tumor (T) stage. Our data suggest that DARPP-32 is a negative prognostic marker associated with increasing stages of NSCLC and may represent a novel therapeutic target. Citation Format: Sk. Kayum Alam, Matteo Astone, Ping Liu, Stephanie R. Hall, Abbygail M. Coyle, Erin N. Dankert, Dane K. Hoffman, Wei Zhang, Rui Kuang, Anja C. Roden, Aaron S. Mansfield, Luke H. Hoeppner. DARPP-32 and t-DARPP promote non-small cell lung cancer growth through regulation of IKKα-dependent cell migration and Akt/Erk-mediated cell survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5161.

Abstract 223: A meta-analysis of genome-wide association studies of multiple myeloma among African Americans

Du, Zhaohui , Song, Chi , Rand, Kristin A. , Weinhold, Niels , Hwang, Amie E. , Sheng, Xin , Hom, Victor, Pawlish, Karen , Peters, Edward , Mohrbacher, Ann, Stram, Alexander , Berndt, Sonja I. , Blot, William J. , Carpten, John D. , Stroup, Antoinette M. , Zhang, Wei , Mehta, Jayesh, Wolf, Jeffrey L. , Martin, Thomas G. , Terebelo, Howard R. , Janakiraman, Nalini, Kolonel, Laurence N. , Vij, Ravi , Bernal‐Mizrachi, Leon , Zonder, Jeffrey A. , Huff, Carol Ann , Conti, David V. , Haiman, Christopher A. , Conti, David V , Berg, David Van Den , Ailawadhi, Sikander , Nooka, Ajay K. , Singhal, Seema , Bock, Cathryn Hufford , Stram, Alex , Olshan, Andrew F. , Chanock, Stephen Jacob , Colditz, Graham A. , Tomasson, Michael H. , Fiala, Mark A. , Marchand, Loı̈c Le , Ziv, Elad , Stram, Daniel O. , Morgan, Gareth J. , Lonial, Sagar , Orlowski, Robert Z. , Cozen, Wendy

Mayo Clinic

Cancer Research | August 17, 2018 | Volume: 78 | Issue: 13_Supplement | Pages: 223-223

10.1158/1538-7445.am2018-223

Abstract Multiple myeloma (MM) is twice as common in African Americans (AA) compared to European Americans (EA). The reported familial clustering and the elevated MM risk among first-degree relatives of cases implicate genetic susceptibility. Previous genome-wide association studies (GWAS) in EA have identified 16 novel risk loci. In this study, we tested the generalizability of the established risk alleles to AA and conducted a meta-GWAS analysis using two sets of AA to identify additional novel common MM risk variants. In the first study, we genotyped 1,305 incident AA MM cases from the African American Multiple Myeloma Study (AAMMS) using the Illumina HumanCore GWAS array and compared them to 7,078 AA controls from the African Ancestry Prostate Cancer Consortium (AAPC) and African Ancestry Breast Cancer Consortium (AABC) using the Illumina 1M-Duo. In the second study, 95 additional AAMMS cases and 435 AA MM cases from the University of Arkansas for Medical Sciences (UAMS) were genotyped using the Illumina MegaBead Chip and compared to 2,390 AA controls from the Multiethnic Cohort. The Haplotype Reference Consortium (HRC) was used to impute the overlapping typed SNPS from each GWAS case and control set together. Per-allele risk associations were tested for 8,715,278 overlapping genotyped and imputed variants with >1% frequency and >0.8 imputation score using unconditional logistic regression in both sets, and the combined effects were estimated using a fixed-effect meta-analysis. Of the 16 reported risk loci discovered in EA, directional consistency was present for 15 variants; eight of these replicated at nominal significance p<0.05, with the most statistically significant variant being rs4487645 at 7p15.3 (OR=1.38, p=3.56×10-6). AA individuals with polygenic risk scores from these 16 variants (PRS) in the top 10% stratum had a 1.44-fold increased MM risk compared to those with a PRS in the 25th -75th percentiles. Additionally, we identified three suggestive novel loci located at 12q12, 9p24.3 and 9p13.1 at p<1×10-6, with ORs ranging from 1.25-1.55, but none reached genome-wide significance. The variant at 9p24.3 is located in an intron in the KANK1 gene and a correlated SNP in EAs (r2=0.5) is strongly associated with gene expression in neoplastic plasma cells (unpublished, Weinhold and Morgan). Our study replicated most of the reported risk loci discovered among EA, demonstrated that a PRS constructed using the 16 reported risk alleles was associated with MM risk, and provides suggestive evidence for additional loci associated with MM risk in AAs. Citation Format: Zhaohui Du, Chi Song, Kristin Rand, Niels Weinhold, David Van Den Berg, Amie Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward S. Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William Blot, John David Carpten, Antoinette Stroup, Andrew Olshan, Wei Zhang, African Ancestry Breast & Prostate Consortium, Stephen Chanock, Jayesh Mehta, Graham A. Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Loic LeMarchand, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association studies of multiple myeloma among African Americans [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 223.