A TCP model incorporating setup uncertainty and tumor cell density variation in microscopic extension to guide treatment planning

2010 ◽  
Vol 38 (1) ◽  
pp. 439-448 ◽  
Author(s):  
Jian-Yue Jin ◽  
Feng-Ming Kong ◽  
Dezhi Liu ◽  
Lei Ren ◽  
Haisen Li ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Treatment Planning ◽  
Cell Density ◽  
Density Variation ◽  
Microscopic Extension

scholarly journals P09.13 Optimization of a GMP-grade large-scale expansion protocol for cytokine-induced killer cells using gas-permeable static culture flasks

2020 ◽  
Vol 8 (Suppl 2) ◽  
pp. A58.2-A59
Author(s):  
A Ventura ◽  
P Palmerini ◽  
A Dalla Pietà ◽  
R Sommaggio ◽  
G Astori ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Cell Density ◽  
Large Scale ◽  
Scale Production ◽  
Static Culture ◽  
Cik Cells ◽  
Standard Culture ◽  
Cik Cell ◽  
Scale Expansion ◽  
Cells Cultured

BackgroundCytokine-Induced Killer (CIK) cells are ex vivo expanded T cells with NK cell phenotype. They express both CD3 and CD56 antigens, and exert a potent antitumor activity against a variety of tumors. Several clinical trials demonstrated the safety and the feasibility of CIK cell therapy, with very low side effects and minimal graft-versus-host toxicity. In this study, we developed a GMP-compliant protocol for robust large-scale expansion of CIK cells using G-Rex® gas-permeable static culture flasks.Materials and MethodsCIK cells were obtained by stimulating healthy donor PBMCs with GMP-grade IFN-γ, IL-2 and CD3 mAbs, and were cultured in G-Rex6® or G-Rex®6M well plates. CIK cells in G-Rex6® were split only once at day 7 to reduce cell density, whereas the number of CIK cells culterd in G-Rex®6M was not adjusted. In both culture conditions, fresh IL-2 was provided every 3–4 days. We compared these two culture protocols with the culture in standard flasks. Phenotype was analyzed by flow cytometry and cytotoxicity was assessed against several tumor cell lines by calcein-release assay.ResultsCIK cells cultured in G-Rex6® well plates showed an outstanding cell expansion compared to G-Rex®6M well plates or standard culture flasks, with a 400-fold expansion and a mean of 109 total cells obtained per single well in 14 days, starting from just 2.5 × 106 cells per well. Moreover, the cultures in G-Rex6® were characterized by an higher percentage of CD3+CD56+ cells, as compared to G-Rex®6M or standard culture flasks. Cells cultured in all devices had a comparable expression of NKG2D, NKp30, NKp44, 2B4 receptors. Importantly, CIK cells expanded in G-Rex®6 were as cytotoxic as cells expanded in standard culture flasks. Conversely, CIK cells cultured in G-Rex®6M showed a remarkable reduction of cytotoxicity against tumor cell targets, thus suggesting that cell density during expansion could affect CIK cell activity.ConclusionsWe propose a GMP-compliant protocol for robust large-scale production of CIK cells. G-Rex® system allows to obtain large amounts of CIK cells highly enriched in the CD3+CD56+ subset and endowed with high cytotoxic activity; this can be accomplished with just a single cell culture split at day 7, which dramatically reduces the culture manipulation as compared to the standard culture flasks. Notably, this strategy can be further and easily scalable to produce CIK cells for clinical immunotherapy applications.Disclosure InformationA. Ventura: None. P. Palmerini: None. A. Dalla Pietà: None. R. Sommaggio: None. G. Astori: None. K. Chieregato: None. M. Tisi: None. C. Visco: None. O. Perbellini: None. M. Ruggeri: None. E. Cappuzzello: None. A. Rosato: None.

Hematoporphyrin Derivative Uptake and Tumor Cell Density

1987 ◽  
Vol 514 (1 Mechanisms of) ◽  
pp. 328-329
Author(s):  
GRETA M. GARBO ◽  
RICK W. KECK ◽  
STEVEN H. SELMAN ◽  
MARTHA KREIMER-BIRN BAUM
Keyword(s):  
Tumor Cell ◽  
Cell Density ◽  
Hematoporphyrin Derivative

11C-methionine uptake correlates with tumor cell density rather than with microvessel density in glioma: A stereotactic image-histology comparison

NeuroImage ◽  
2010 ◽  
Vol 49 (4) ◽  
pp. 2977-2982 ◽  
Author(s):  
Yoshiko Okita ◽  
Manabu Kinoshita ◽  
Tetsu Goto ◽  
Naoki Kagawa ◽  
Haruhiko Kishima ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Cell Density ◽  
Microvessel Density ◽  
Methionine Uptake

scholarly journals Evaluating the Histopathology of Pancreatic Ductal Adenocarcinoma by Intravoxel Incoherent Motion-Diffusion Weighted Imaging Comparing With Diffusion-Weighted Imaging

2021 ◽  
Vol 11 ◽  
Author(s):  
Qi Liu ◽  
Jinggang Zhang ◽  
Man Jiang ◽  
Yue Zhang ◽  
Tongbing Chen ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Tumor Cell ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Cell Density ◽  
Diffusion Weighted Imaging ◽  
Intravoxel Incoherent Motion ◽  
Ductal Adenocarcinoma ◽  
Diffusion Weighted ◽  
Adc Values ◽  
D Values

ObjectivesTo explore the differences between intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and diffusion-weighted imaging (DWI) in evaluating the histopathological characters of pancreatic ductal adenocarcinoma (PDAC).MethodsThis retrospective study enrolled 50 patients with PDAC confirmed by pathology from December 2018 to May 2020. All patients underwent DWI and IVIM-DWI before surgeries. Patients were classified into low- and high-fibrosis groups. Apparent diffusion coefficient (ADC), diffusion coefficient (D), false diffusion coefficient (D*), and perfusion fraction (f) were measured by two radiologists, respectively in GE AW 4.7 post-processing station, wherein ADC values were derived by mono-exponential fits and f, D, D* values were derived by biexponential fits. The tumor tissue was stained with Sirius red, CD34, and CK19 to evaluate fibrosis, microvascular density (MVD), and tumor cell density. Furthermore, the correlation between ADC, D, D*, and f values and histopathological results was analyzed.ResultsThe D values were lower in the high-fibrosis group than in the low-fibrosis group, while the f values were opposite. Further, no statistically significant differences were detected in ADC and D* values between the high- and low-fibrosis groups. The AUC of D and f values had higher evaluation efficacy in the high- and low-fibrosis groups than ADC values. A significant negative correlation was established between D values, and fibrosis and a significant positive correlation were observed between f values and fibrosis. No statistical difference was detected between DWI/IVIM parameters values and MVD or tumor cell density except for the positive correlation between D* values and tumor cell density.ConclusionsD and f values derived from the IVIM model had higher sensitivity and diagnostic performance for grading fibrosis in PDAC compared to the conventional DWI model. IVIM-DWI may have the potential as an imaging biomarker for predicting the fibrosis grade of PDAC.

scholarly journals NIMG-30. REPRODUCIBLE RADIOMIC MAPPING OF TUMOR CELL DENSITY BY MACHINE LEARNING AND DOMAIN ADAPTATION

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi167-vi167
Author(s):  
Lujia Wang ◽  
Hyunsoo Yoon ◽  
Andrea Hawkins-Daarud ◽  
Kyle Singleton ◽  
Kamala Clark-Swanson ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Cell Density ◽  
Domain Adaptation ◽  
Texture Features ◽  
Training Model ◽  
Biopsy Sample ◽  
Training Data ◽  
Domain Adaption ◽  
Important Challenge ◽  
Test Patient

Abstract BACKGROUND An important challenge in radiomics research is reproducibility. Images are collected on different image scanners and protocols, which introduces significant variability even for the same type of image across institutions. In the present proof-of-concept study, we address the reproducibility issue by using domain adaptation – an algorithm that transforms the radiomic features of each new patient to align with the distribution of features formed by the patient samples in a training set. METHOD Our dataset included 18 patients in training with a total of 82 biopsy sample. The pathological tumor cell density was available for each sample. Radiomic (statistical + texture) features were extracted from the region of six image contrasts locally matched with each biopsy sample. A Gaussian Process (GP) classifier was built to predict tumor cell density using radiomic features. Another 6 patients were used to test the training model. These patients had a total of 31 biopsy samples. The images of each test patient were purposely normalized using a different approach, i.e., using the CSF instead of the whole brain as the reference. This was to mimic the practical scenario of image source discrepancy between different patients. Domain adaptation was applied to each test patient. RESULTS Among the 18 training patients, the leave-one-patient-out cross validation accuracy is 0.81 AUC, 0.78 sensitivity, and 0.83 specificity. When the trained model was applied to the 6 test patients (purposely normalized using a different approach than that of the training data), the accuracy dramatically reduced to 0.39 AUC, 0.08 sensitivity, and 0.61 specificity. After using domain adaption, the accuracy improved to 0.68 AUC, 0.62 sensitivity, and 0.72 specificity. CONCLUSION We provide candidate enabling tools to address reproducibility in radiomics models by using domain adaption algorithms to account for discrepancy of the images between different patients.

scholarly journals Infiltration of CD8+ T cells into tumor cell clusters in triple-negative breast cancer

2019 ◽  
Vol 116 (9) ◽  
pp. 3678-3687 ◽  
Author(s):  
Xuefei Li ◽  
Tina Gruosso ◽  
Dongmei Zuo ◽  
Atilla Omeroglu ◽  
Sarkis Meterissian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
T Cell ◽  
T Lymphocytes ◽  
Tumor Cell ◽  
Cell Density ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Spatial Profile ◽  
Cell Clusters

Infiltration of CD8+ T lymphocytes into solid tumors is associated with good prognosis in various types of cancer, including triple-negative breast cancer (TNBC). However, the mechanisms underlying different infiltration levels are largely unknown. Here, we have characterized the spatial profile of CD8+ T cells around tumor cell clusters (tightly connected tumor cells) in the core and margin regions in TNBC patient samples. We found that in some patients, the CD8+ T cell density first decreases when moving in from the boundary of the tumor cell clusters and then rises again when approaching the center. To explain various infiltration profiles, we modeled the dynamics of T cell density via partial differential equations. We spatially modulated the diffusion/chemotactic coefficients of T cells (to mimic physical barriers) or introduced the localized secretion of a diffusing T cell chemorepellent. Combining the spatial-profile analysis and the modeling led to support for the second idea; i.e., there exists a possible chemorepellent inside tumor cell clusters, which prevents CD8+ T cells from infiltrating into tumor cell clusters. This conclusion was consistent with an investigation into the properties of collagen fibers which suggested that variations in desmoplastic elements does not limit infiltration of CD8+ T lymphocytes, as we did not observe significant correlations between the level of T cell infiltration and fiber properties. Our work provides evidence that CD8+ T cells can cross typical fibrotic barriers and thus their infiltration into tumor clusters is governed by other mechanisms possibly involving a local repellent.

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