Predicting and monitoring cancer treatment response with diffusion-weighted MRI

An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, nonimage based clinical outcome metrics include morphology, clinical, and laboratory parameters, however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pretreatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response.

Effect of systemic tetracycline on the degradation of tetracycline-impregnated bilayered collagen membranes: an animal study

BACKGROUND: Premature collagen membrane degradation may compromise the outcome of osseous regenerative procedures. Tetracyclines (TTCs) inhibit the catalytic activities of human metalloproteinases. Preprocedural immersion of collagen membranes in TTC and systemic administration of TTC may be possible alternatives to reduce the biodegradation of native collagen membranes. AIM: To evaluate the in vivo degradation of collagen membranes treated by combined TTC immersion and systemic administration. MATERIALS AND METHODS: Seventy-eight bilayered porcine collagen membrane disks were divided into three groups and were immersed in 0, 50, or 100 mg/mL TTC solution. Three disks, one of each of the three groups, were implanted on the calvaria of each of 26 Wistar rats. Thirteen (study group) were administered with systemic TTC (10 mg/kg), while the remaining 13 received saline injections (control group). Calvarial tissues were retrieved after 3 weeks, and histological sections were analyzed by image analysis software. RESULTS: Percentage of remaining collagen area within nonimpregnated membranes was 52.26 ± 20.67% in the study group, and 32.74 ± 13.81% in the control group. Immersion of membranes in 100 mg/mL TTC increased the amount of residual collagen to 63.46 ± 18.19% and 42.82 ± 12.99% (study and control groups, respectively). Immersion in 50 mg/mL TTC yielded maximal residual collagen values: 80.75 ± 14.86% and 59.15 ± 8.01% (study and control groups, respectively). Differences between the TTC concentrations, and between the control and the study groups were statistically significant. CONCLUSIONS: Immersion of collagen membranes in TTC solution prior to their implantation and systemic administration of TTC significantly decreased the membranes' degradation.

Delayed osteoblast differentiation and altered inflammatory response around implants placed in incisor sockets of type 2 diabetic rats

Objective: Central to the process of osseointegration is the recruitment of mesenchymal progenitor cells to the healing site, their proliferation and differentiation to bone synthesising osteoblasts. The process is under the control of pro-inflammatory cytokines and growth factors. The aim of this study was to monitor these key stages of osseointegration and the signalling milieu during bone healing around implants placed in healthy and diabetic bone. Methods: Implants were placed into the sockets of incisors extracted from the mandibles of normal Wistar and diabetic Goto-Kakizaki rats. Mandibles 1-12 weeks post-insertion of the implant were examined by histochemistry and immunocytochemistry to localise the presence of Stro-1- positive mesenchymal progenitor cells, proliferating cellular nuclear antigen proliferative cells, osteopontin and osteocalcin, macrophages, pro-inflammatory cytokines interleukin (IL)-1 , IL-6, tumour necrosis factor (TNF)- and tumour growth factor (TGF)- 1. Image analysis provided a semi-quantification of positively expressing cells. Results: Histological staining identified a delay in the formation of mineralised bone around implants placed in diabetic animals. Within the diabetic bone, the migration of Stro-1 mesenchymal cells in the healing tissue appeared to be unaffected. However, in the diabetic healing bone, the onset of cell proliferation and osteoblast differentiation were delayed and subsequently prolonged compared with normal bone. Similar patterns of change were observed in diabetic bone for the presence of IL-1 , TNF- , macrophages and TGF- 1. Conclusion: The observed alterations in the extracellular presence of pro-inflammatory cytokines, macrophages and growth factors within diabetic tissues that correlate to changes in the signalling milieu, may affect the proliferation and differentiation of mesenchymal progenitor cells in the osseointegration process. To cite this article: Colombo JS, Balani D, Sloan AJ, St Crean J, Okazaki J, Waddington RJ. Delayed osteoblast differentiation and altered inflammatory response around implants placed in incisor sockets of type 2 diabetic rats Clin. Oral Impl. Res22, 2011; 578-586 doi: 10.1111/j.1600-0501.2010.01992.x.

Life stage differences in mammary gland gene expression profile in non-human primates

Breast cancer (BC) is the most common malignancy of women in the developed world. To better understand its pathogenesis, knowledge of normal breast development is crucial, as BC is the result of disregulation of physiologic processes. The aim of this study was to investigate the impact of reproductive life stages on the transcriptional profile of the mammary gland in a primate model. Comparative transcriptomic analyses were carried out using breast tissues from 28 female cynomolgus macaques (Macaca fascicularis) at the following life stages: prepubertal (n = 5), adolescent (n = 4), adult luteal (n = 5), pregnant (n = 6), lactating (n = 3), and postmenopausal (n = 5). Mammary gland RNA was hybridized to Affymetrix GeneChip(®) Rhesus Macaque Genome Arrays. Differential gene expression was analyzed using ANOVA and cluster analysis. Hierarchical cluster analysis revealed distinct separation of life stage groups. More than 2,225 differentially expressed mRNAs were identified. Gene families or pathways that changed across life stages included those related to estrogen and androgen (ESR1, PGR, TFF1, GREB1, AR, 17HSDB2, 17HSDB7, STS, HSD11B1, AKR1C4), prolactin (PRLR, ELF5, STAT5, CSN1S1), insulin-like growth factor signaling (IGF1, IGFBP1, IGFBP5), extracellular matrix (POSTN, TGFB1, COL5A2, COL12A1, FOXC1, LAMC1, PDGFRA, TGFB2), and differentiation (CD24, CD29, CD44, CD61, ALDH1, BRCA1, FOXA1, POSTN, DICER1, LIG4, KLF4, NOTCH2, RIF1, BMPR1A, TGFB2). Pregnancy and lactation displayed distinct patterns of gene expression. ESR1 and IGF1 were significantly higher in the adolescent compared to the adult animals, whereas differentiation pathways were overrepresented in adult animals and pregnancy-associated life stages. Few individual genes were distinctly different in postmenopausal animals. Our data demonstrate characteristic patterns of gene expression during breast development. Several of the pathways activated during pubertal development have been implicated in cancer development and metastasis, supporting the idea that other developmental markers may have application as biomarkers for BC.

MicroRNA Expression Array Identifies Novel Diagnostic Markers for Conventional and Oncocytic Follicular Thyroid Carcinomas

Objective:The most difficult thyroid tumors to be diagnosed by cytology and histology are conventional follicular carcinomas (cFTCs) and oncocytic follicular carcinomas (oFTCs). Several microRNAs (miRNAs) have been previously found to be consistently deregulated in papillary thyroid carcinomas; however, very limited information is available for cFTC and oFTC. The aim of this study was to explore miRNA deregulation and find candidate miRNA markers for follicular carcinomas that can be used diagnostically.Design:Thirty-eight follicular thyroid carcinomas (21 cFTCs, 17 oFTCs) and 10 normal thyroid tissue samples were studied for expression of 381 miRNAs using human microarray assays. Expression of deregulated miRNAs was confirmed by individual RT-PCR assays in all samples. In addition, 11 follicular adenomas, two hyperplastic nodules (HNs), and 19 fine-needle aspiration samples were studied for expression of novel miRNA markers detected in this study.Results:The unsupervised hierarchical clustering analysis demonstrated individual clusters for cFTC and oFTC, indicating the difference in miRNA expression between these tumor types. Both cFTCs and oFTCs showed an up-regulation of miR-182/-183/-221/-222/-125a-3p and a down-regulation of miR-542-5p/-574-3p/-455/-199a. Novel miRNA (miR-885-5p) was found to be strongly up-regulated (>40-fold) in oFTCs but not in cFTCs, follicular adenomas, and HNs. The classification and regression tree algorithm applied to fine-needle aspiration samples demonstrated that three dysregulated miRNAs (miR-885-5p/-221/-574-3p) allowed distinguishing follicular thyroid carcinomas from benign HNs with high accuracy.Conclusions:In this study we demonstrate that different histopathological types of follicular thyroid carcinomas have distinct miRNA expression profiles. MiR-885-5p is highly up-regulated in oncocytic follicular carcinomas and may serve as a diagnostic marker for these tumors. A small set of deregulated miRNAs allows for an accurate discrimination between follicular carcinomas and hyperplastic nodules and can be used diagnostically in fine-needle aspiration biopsies.

A MICROFLUIDIC METHOD TO MEASURE DIFFUSION IN HYDROGELS

A novel microfluidic method is proposed for studying diffusion of small molecules in a hydrogel. Microfluidic devices were prepared with semi-permeable microchannels defined by crosslinked poly(ethylene glycol) (PEG). Uptake of dye molecules from aqueous solutions flowing through the microchannels was observedoptically and diffusion of the dye into the hydrogel was quantified. To complement the diffusion measurements from the microfluidic studies, nuclear magnetic resonance(NMR) characterization of the diffusion of dye in the PEG hydrogels was performed. The diffusion of small molecules in a hydrogel is relevant to applications such asdrug delivery and modeling transport for tissue-engineering applications. The diffusion of small molecules in a hydrogel is dependent on the extent of crosslinking within the gel, gel structure, and interactions between the diffusive species and the hydrogel network. These effects were studied in a model environment (semi-infinite slab) at the hydrogelfluid boundary in a microfluidic device. The microfluidic devices containing PEG microchannels were fabricated using photolithography. The unsteady diffusion of small molecules (dyes) within the microfluidic device was monitored and recorded using a digital microscope. The information was analyzed with techniques drawn from digital microscopy and image analysis to obtain concentration profiles with time. Using a diffusion model to fit this concentration vs. position data, a diffusion coefficient was obtained. This diffusion coefficient was compared to those from complementary NMR analysis. A pulsed field gradient (PFG) method was used to investigate and quantify small molecule diffusion in gradient (PFG) method was used to investigate and quantify small molecule diffusion in hydrogels. There is good agreement between the diffusion coefficients obtained from the microfluidic methods and those found from the NMR studies. The microfluidic approachused in this research enables the study of diffusion at length scales that approach those of vasculature, facilitating models for studying drug elution from hydrogels in blood-contacting applications.

Development of a biocrystallisation assay for examining effects of homeopathic preparations ursing cress seedlings

A major challenge in basic research into homeopathic potentisation is to develop bioassays that yield consistent results. We evaluated the potential of a seedling-biocrystallisation method. Cress seeds (Lepidium sativum L.) germinated and grew for 4 days in vitro in Stannum metallicum 30x or water 30x in blinded and randomized assignment. 15 experiments were performed at two laboratories. CuCl2-biocrystallisation of seedlings extracted in the homeopathic preparations was performed on circular glass plates. Resulting biocrystallograms were analysed by computerized textural image analysis. All texture analysis variables analysed yielded significant results for the homeopathic treatment; thus the texture of the biocrystallograms of homeopathically treated cress exhibited specific characteristics. Two texture analysis variables yielded differences between the internal replicates, most probably due to a processing order effect. There were only minor differences between the results of the two laboratories. The biocrystallisation method seems to be a promising complementary outcome measure for plant bioassays investigating effects of homeopathic preparations.

Gene expression profiling reveals consistent differences between clinical samples of human leukaemias and their model cell lines

Microarray gene expression profiles of fresh clinical samples of chronic myeloid leukaemia in chronic phase, acute promyelocytic leukaemia and acute monocytic leukaemia were compared with profiles from cell lines representing the corresponding types of leukaemia (K562, NB4, HL60). In a hierarchical clustering analysis, all clinical samples clustered separately from the cell lines, regardless of leukaemic subtype. Gene ontology analysis showed that cell lines chiefly overexpressed genes related to macromolecular metabolism, whereas in clinical samples genes related to the immune response were abundantly expressed. These findings must be taken into consideration when conclusions from cell line-based studies are extrapolated to patients.

Cerebral correlates of muscle tone fluctuations in restless legs syndrome: A pilot study with combined functional magnetic resonance imaging and anterior tibial muscle electromyography

BACKGROUND: The pathology of restless legs syndrome (RLS) is still not understood. To investigate the pathomechanism of the disorder further we recorded a surface electromyogram (EMG) of the anterior tibial muscle during functional magnetic resonance imaging (fMRI) in patients with idiopathic RLS. METHODS: Seven subjects with moderate to severe RLS were investigated in the present pilot study. Patients were lying supine in the scanner for over 50min and were instructed not to move voluntarily. Sensory leg discomfort (SLD) was evaluated on a 10-point Likert scale. For brain image analysis, an algorithm for the calculation of tonic EMG values was developed. RESULTS: We found a negative correlation of tonic EMG and SLD (p <0.01). This finding provides evidence for the clinical experience that RLS-related subjective leg discomfort increases during muscle relaxation at rest. In the fMRI analysis, the tonic EMG was associated with activation in motor and somatosensory pathways and also in some regions that are not primarily related to motor or somatosensory functions. CONCLUSIONS: By using a newly developed algorithm for the investigation of muscle tone-related changes in cerebral activity, we identified structures that are potentially involved in RLS pathology. Our method, with some modification, may also be suitable for the investigation of phasic muscle activity that occurs during periodic leg movements.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity