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1.
Minn Med ; 100(1): 4, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-30506059

RESUMO

To do this job well, we may need to reanalyze our attitudes toward the potpourri of humanity we encounter in the exam room.

2.
Minn Med ; 100(2): 27, 2017 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30428179
3.
Minn Med ; 100(3): 4, 2017 May.
Artigo em Inglês | MEDLINE | ID: mdl-30452128
7.
Minn Med ; 99(8): 4, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-30501161
8.
Minn Med ; 99(6): 4, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-28857536
9.
Minn Med ; 98(8): 4, 2015 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-26455027
11.
Minn Med ; 98(7): 4, 2015 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-26267910
13.
Minn Med ; 98(4): 4, 2015 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-26065193
15.
PLoS One ; 10(4): e0123877, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-25859981

RESUMO

Bone metastasis occurs for men with advanced prostate cancer which promotes osseous growth and destruction driven by alterations in osteoblast and osteoclast homeostasis. Patients can experience pain, spontaneous fractures and morbidity eroding overall quality of life. The complex and dynamic cellular interactions within the bone microenvironment limit current treatment options thus prostate to bone metastases remains incurable. This study uses voxel-based analysis of diffusion-weighted MRI and CT scans to simultaneously evaluate temporal changes in normal bone homeostasis along with prostate bone metatastsis to deliver an improved understanding of the spatiotemporal local microenvironment. Dynamic tumor-stromal interactions were assessed during treatment in mouse models along with a pilot prospective clinical trial with metastatic hormone sensitive and castration resistant prostate cancer patients with bone metastases. Longitudinal changes in tumor and bone imaging metrics during delivery of therapy were quantified. Studies revealed that voxel-based parametric response maps (PRM) of DW-MRI and CT scans could be used to quantify and spatially visualize dynamic changes during prostate tumor growth and in response to treatment thereby distinguishing patients with stable disease from those with progressive disease (p<0.05). These studies suggest that PRM imaging biomarkers are useful for detection of the impact of prostate tumor-stromal responses to therapies thus demonstrating the potential of multi-modal PRM image-based biomarkers as a novel means for assessing dynamic alterations associated with metastatic prostate cancer. These results establish an integrated and clinically translatable approach which can be readily implemented for improving the clinical management of patients with metastatic bone disease.


Assuntos
Neoplasias Ósseas/diagnóstico , Neoplasias Ósseas/secundário , Imagem Multimodal/métodos , Neoplasias da Próstata/patologia , Animais , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêutico , Densidade Óssea , Neoplasias Ósseas/terapia , Imagem de Difusão por Ressonância Magnética , Difosfonatos/farmacologia , Difosfonatos/uso terapêutico , Modelos Animais de Doenças , Docetaxel , Humanos , Masculino , Camundongos , Osteoblastos/efeitos dos fármacos , Osteoblastos/metabolismo , Osteólise/diagnóstico , Taxoides/farmacologia , Taxoides/uso terapêutico , Resultado do Tratamento , Carga Tumoral/efeitos dos fármacos , Carga Tumoral/efeitos da radiação
16.
PLoS One ; 10(3): e0122151, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-25816249

RESUMO

PURPOSE: To evaluate diffusion weighted MRI (DW-MR) as a response metric for assessment of neoadjuvant chemotherapy (NAC) in patients with primary breast cancer using prospective multi-center trials which provided MR scans along with clinical outcome information. MATERIALS AND METHODS: A total of 39 patients with locally advanced breast cancer accrued from three different prospective clinical trials underwent DW-MR examination prior to and at 3-7 days (Hull University), 8-11 days (University of Michigan) and 35 days (NeoCOMICE) post-treatment initiation. Thirteen patients, 12 of which participated in treatment response study, from UM underwent short interval (<1hr) MRI examinations, referred to as "test-retest" for examination of repeatability. To further evaluate stability in ADC measurements, a thermally controlled diffusion phantom was used to assess repeatability of diffusion measurements. MRI sequences included contrast-enhanced T1-weighted, when appropriate, and DW images acquired at b-values of 0 and 800 s/mm2. Histogram analysis and a voxel-based analytical technique, the Parametric Response Map (PRM), were used to derive diffusion response metrics for assessment of treatment response prediction. RESULTS: Mean tumor apparent diffusion coefficient (ADC) values generated from patient test-retest examinations were found to be very reproducible (|ΔADC|<0.1x10-3mm2/s). This data was used to calculate the 95% CI from the linear fit of tumor voxel ADC pairs of co-registered examinations (±0.45x10-3mm2/s) for PRM analysis of treatment response. Receiver operating characteristic analysis identified the PRM metric to be predictive of outcome at the 8-11 (AUC = 0.964, p = 0.01) and 35 day (AUC = 0.770, p = 0.05) time points (p<.05) while whole-tumor ADC changes where significant at the later 35 day time interval (AUC = 0.825, p = 0.02). CONCLUSION: This study demonstrates the feasibility of performing a prospective analysis of DW-MRI as a predictive biomarker of NAC in breast cancer patients. In addition, we provide experimental evidence supporting the use of sensitive analytical tools, such as PRM, for evaluating ADC measurements.


Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica/administração & dosagem , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/patologia , Imagem de Difusão por Ressonância Magnética/métodos , Adulto , Idoso , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Quimioterapia Adjuvante , Estudos de Viabilidade , Feminino , Humanos , Pessoa de Meia-Idade , Estudos Prospectivos , Resultado do Tratamento
18.
Minn Med ; 98(11-12): 4, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26720930
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