The Tumor Imaging Metrics Core was approved as a developing core in the last CCSG submission. The Tumor Imaging Metrics Core (TIMC) provides objective assessment of response to treatment for patients enrolled in oncology clinical trials. All major radiological assessment criteria are supported including: RECIST (1.0 and 1.1), WHO, IWRC, Cheson, SUV, Choi, 3D Volume and irRC. For each patient, target and nontarget lesions are selected according to the assessment criteria guidelines and are tracked longitudinally. Scans to be measured are transferred from DF/HCC sites to the central Core lab via DICOM imaging network. Quantitative analysis of CT, MR and PET imaging studies are performed on a variety of modalityspecific workstations. After scans are analyzed, the measurement results are reviewed and finalized by Harvard faculty radiologists and/or nuclear medicine physicians. Measurement results are stored in the TIMC database on a secure website and are viewable online by authorized trial staff. The quantitative measurements are used to determine tumor response to treatment and ultimately guide patient care. Summary statistics for the trial are presented as well as individual patient measurements. Requests for scan analysis can be conveniently ordered on-line by the trial staff. Users are authenticated via their home institution's username and password (single sign-on). Rates for sen/ices are very reasonable compared to other options available from outside DF/HCC. Director(s): Gordon J. Harris, PhD""""""""^""""""""and Annick D. Van den Abbeele, MD Category: 4.03 (Clinical - Radiology and Tumor Imaging) Management: Joint (Cancer Center and Institutional).
The Tumor Imaging Metrics Core (TIMC) provides tumor measurements of radiological scans for oncology clinical trials. Its mission is to provide standardized measurements of CT, MR and PET imaging studies according to protocol for oncology clinical trials.
|Lin, Ruei-Zeng; Lee, Chin Nien; Moreno-Luna, Rafael et al. (2017) Host non-inflammatory neutrophils mediate the engraftment of bioengineered vascular networks. Nat Biomed Eng 1:|
|Wang, Meng; Han, Jing; Marcar, Lynnette et al. (2017) Radiation Resistance in KRAS-Mutated Lung Cancer Is Enabled by Stem-like Properties Mediated by an Osteopontin-EGFR Pathway. Cancer Res 77:2018-2028|
|Ignatius, Myron S; Hayes, Madeline N; Lobbardi, Riadh et al. (2017) The NOTCH1/SNAIL1/MEF2C Pathway Regulates Growth and Self-Renewal in Embryonal Rhabdomyosarcoma. Cell Rep 19:2304-2318|
|Nugent, Alicia A; Park, Jong G; Wei, Yan et al. (2017) Mutant ?2-chimaerin signals via bidirectional ephrin pathways in Duane retraction syndrome. J Clin Invest 127:1664-1682|
|Breitkopf, Susanne B; Taveira, Mateus De Oliveira; Yuan, Min et al. (2017) Serial-omics of P53-/-, Brca1-/- Mouse Breast Tumor and Normal Mammary Gland. Sci Rep 7:14503|
|Bowden, John A; Heckert, Alan; Ulmer, Candice Z et al. (2017) Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma. J Lipid Res 58:2275-2288|
|Lindsley, R Coleman; Saber, Wael; Mar, Brenton G et al. (2017) Prognostic Mutations in Myelodysplastic Syndrome after Stem-Cell Transplantation. N Engl J Med 376:536-547|
|Mita, Monica M; Mita, Alain C; Moseley, Jennifer L et al. (2017) Phase 1 safety, pharmacokinetic and pharmacodynamic study of the cyclin-dependent kinase inhibitor dinaciclib administered every three weeks in patients with advanced malignancies. Br J Cancer 117:1258-1268|
|Hu, Yuebi; Alden, Ryan S; Odegaard, Justin I et al. (2017) Discrimination of Germline EGFR T790M Mutations in Plasma Cell-Free DNA Allows Study of Prevalence Across 31,414 Cancer Patients. Clin Cancer Res 23:7351-7359|
|Lam, Hilaire C; Liu, Heng-Jia; Baglini, Christian V et al. (2017) Rapamycin-induced miR-21 promotes mitochondrial homeostasis and adaptation in mTORC1 activated cells. Oncotarget 8:64714-64727|
Showing the most recent 10 out of 371 publications