Background
Assessment tools for early cystic fibrosis (CF) lung disease are limited. Detecting early pulmonary disease is crucial to increasing life expectancy by starting interventions to slow the ...progression of the pulmonary disease with the many treatment options available.
Objective
To compare the utility of lung T1-mapping MRI with ultrashort echo time (UTE) MRI in children with cystic fibrosis in detecting early stage lung disease and monitoring pulmonary exacerbations.
Materials and methods
We performed a prospective study in 16 children between September 2017 and January 2018. In Phase 1, we compared five CF patients with normal spirometry (mean 11.2 years) to five age- and gender-matched healthy volunteers. In Phase 2, we longitudinally evaluated six CF patients (median 11 years) in acute pulmonary exacerbation. All children had non-contrast lung T1-mapping and UTE MRI and spirometry testing. We compared the mean normalized T1 value and percentage lung volume without T1 value in CF patients and healthy subjects in Phase 1 and during treatment in Phase 2. We also performed cystic fibrosis MRI scoring. We evaluated differences in continuous variables using standard statistical tests.
Results
In Phase 1, mean normalized T1 values of the lung were significantly lower in CF patients in comparison to healthy controls (
P
=0.02) except in the right lower lobe (
P
=0.29). The percentage lung volume without T1 value was also significantly higher in CF patients (
P
=0.006). UTE MRI showed no significant differences between CF patients and healthy volunteers (
P
=0.11). In Phase 2, excluding one outlier case who developed systemic disease in the course of treatment, the whole-lung T1 value increased (
P
=0.001) and perfusion scoring improved (
P
=0.02) following therapy. We observed no other significant changes in the MRI scoring.
Conclusion
Lung T1-mapping MRI can detect early regional pulmonary CF disease in children and might be helpful in the assessment of acute pulmonary exacerbations.
Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard ...techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy for monitoring disease progression.
To investigate the effectiveness of a convolutional neural network (CNN) model for quantifying and monitoring AT, and to compare it with other quantitative AT measures obtained from threshold-based techniques.
Paired volumetric whole lung inspiratory and expiratory CT scans were obtained at four time points (0, 3, 12 and 24 months) on 36 subjects with mild CF lung disease. A densely connected CNN (DN) was trained using AT segmentation maps generated from a personalized threshold-based method (PTM). Quantitative AT (QAT) values, presented as the relative volume of AT over the lungs, from the DN approach were compared to QAT values from the PTM method. Radiographic assessment, spirometric measures, and clinical scores were correlated to the DN QAT values using a linear mixed effects model.
QAT values from the DN were found to increase from 8.65% ± 1.38% to 21.38% ± 1.82%, respectively, over a two-year period. Comparison of CNN model results to intensity-based measures demonstrated a systematic drop in the Dice coefficient over time (decreased from 0.86 ± 0.03 to 0.45 ± 0.04). The trends observed in DN QAT values were consistent with clinical scores for AT, bronchiectasis, and mucus plugging. In addition, the DN approach was found to be less susceptible to variations in expiratory deflation levels than the threshold-based approach.
The CNN model effectively delineated AT on expiratory CT scans, which provides an automated and objective approach for assessing and monitoring AT in CF patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Ovarian cancer is the fifth leading cause of cancer-related deaths among American women. Platinum-based chemotherapy, such as cisplatin, represents the standard-of-care for ovarian cancer. However, ...toxicity and acquired resistance to cisplatin have proven challenging in the treatment of patients with ovarian cancer.
Using a genetically engineered mouse model of ovarian endometrioid adenocarcinoma (OEA) in combination with molecular-imaging technologies, we studied the activation of the AKT serine/threonine kinase in response to long-term cisplatin therapy.
Treatment of cells in culture and tumor-bearing animals with cisplatin resulted in activation of AKT, a key mediator of cell survival. On the basis of these results, we investigated the therapeutic use of AKT inhibition in combination with cisplatin, which resulted in enhanced and prolonged induction of apoptosis and in significantly improved tumor control as compared with either agent alone.
These results provide an impetus for clinical trials using combination therapy. To facilitate these trials, we also show the use of diffusion-weighted MRI as an imaging biomarker for evaluation of therapeutic efficacy in OEA.
The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former ...smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.
The aim of this study was to assess variability in quantitative air trapping (QAT) measurements derived from spatially aligned expiration CT scans.
Sixty-four paired CT examinations, from 16 ...school-age cystic fibrosis subjects examined at four separate time intervals, were used in this study. For each pair, visually inspected lobe segmentation maps were generated and expiration CT data were registered to the inspiration CT frame. Measurements of QAT, the percentage of voxels on the expiration CT scan below a set threshold were calculated for each lobe and whole-lung from the registered expiration CT and compared to the true values from the unregistered data.
A mathematical model, which simulates the effect of variable regions of lung deformation on QAT values calculated from aligned to those from unaligned data, showed the potential for large bias. Assessment of experimental QAT measurements using Bland-Altman plots corroborated the model simulations, demonstrating biases greater than 5% when QAT was approximately 40% of lung volume. These biases were removed when calculating QAT from aligned expiration CT data using the determinant of the Jacobian matrix. We found, by Dice coefficient analysis, good agreement between aligned expiration and inspiration segmentation maps for the whole-lung and all but one lobe (Dice coefficient > 0.9), with only the lingula generating a value below 0.9 (mean and standard deviation of 0.85 ± 0.06).
The subtle and predictable variability in corrected QAT observed in this study suggests that image registration is reliable in preserving the accuracy of the quantitative metrics.
The parametric response map (PRM) was evaluated as an early surrogate biomarker for monitoring treatment-induced tissue alterations in patients with head and neck squamous cell carcinoma (HNSCC). ...Diffusion-weighted magnetic resonance imaging (DW-MRI) was performed on 15 patients with HNSCC at baseline and 3 weeks after treatment initiation of a nonsurgical organ preservation therapy (NSOPT) using concurrent radiation and chemotherapy. PRM was applied on serial apparent diffusion coefficient (ADC) maps that were spatially aligned using a deformable image registration algorithm to measure the tumor volume exhibiting significant changes in ADC (PRMADC). Pretherapy and midtherapy ADC maps, quantified from the DWIs, were analyzed by monitoring the percent change in whole-tumor mean ADC and the PRM metric. The prognostic values of percentage change in tumor volume and mean ADC and PRMADC as a treatment response biomarker were assessed by correlating with tumor control at 6 months. Pixel-wise differences as part of PRMADC analysis revealed regions where water mobility increased. Analysis of the tumor ADC histograms also showed increases in mean ADC as early as 3 weeks into therapy in patients with a favorable outcome. Nevertheless, the percentage change in mean ADC was found to not correlate with tumor control at 6 months. In contrast, significant differences in PRMADC and percentage change in tumor volume were observed between patients with pathologically different outcomes. Observations from this study have found that diffusion MRI, when assessed by PRMADC, has the potential to provide both prognostic and spatial information during NSOPT of head and neck cancer.
Recent clinical practice for the management for cancer patients has begun to change from a statistical "one-size fits all" approach to medicine to more individualized care. Pre-treatment biomarkers ...(i.e. genetically and histologically based) have a growing role in providing guidance related to the appropriate therapy and likelihood of response; they do not take into account heterogeneity within the tumor mass. Thus, a biomarker which could be utilized to measure actual tumor response early following treatment initiation would provide an important opportunity to evaluate treatment effects on an individual patient basis. Diffusion weighted magnetic resonance imaging (DW-MRI) offers the opportunity to monitor treatment-associated alterations in tumor microenvironment using quantification of changes in tumor water diffusion values as a surrogate imaging biomarker. Results obtained thus far using DW-MRI have shown that changes in tumor diffusion values can be detected early following treatment initiation which correlate with traditional outcome measures. Sensitive imaging biomarkers are providing for the first time a means of assessing 3 dimensional tumor response early in the treatment cycle. This review highlights the development of DW-MRI and its proposed usefulness in the clinical management of cancer patients. The utility of DW-MRI for assessing therapeutic-induced response is further evaluated on tumors residing in the brain, head and neck and bone.
Noninvasive imaging methods are sought to objectively predict early response to therapy for high-grade glioma tumors. Quantitative metrics derived from diffusion-weighted imaging, such as apparent ...diffusion coefficient (ADC), have previously shown promise when used in combination with voxel-based analysis reflecting regional changes. The functional diffusion mapping (fDM) metric is hypothesized to be associated with volume of tumor exhibiting an increasing ADC owing to effective therapeutic action. In this work, the reference fDM-predicted survival (from previous study) for 3 weeks from treatment initiation (midtreatment) is compared to multiple histogram-based metrics using Kaplan-Meier estimator for 80 glioma patients stratified to responders and nonresponders based on the population median value for the given metric. The ADC histogram metric reflecting reduction in midtreatment volume of solid tumor (ADC < 1.25 × 10
mm
/s) by >8% population-median with respect to pretreatment is found to have the same predictive power as the reference fDM of increasing midtreatment ADC volume above 4%. This study establishes the level of correlation between fDM increase and low-ADC tumor volume shrinkage for prediction of early response to radiation therapy in patients with glioma malignancies.
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