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There has been an explosion of use for quantitative image analysis in the setting of lung disease due to advances in acquisition protocols and postprocessing technology, including machine and deep learning. Despite the plethora of published papers, it is important to understand which approach has clinical validation and can be used in clinical practice. This paper provides an introduction to quantitative image analysis techniques being used in the investigation of lung disease and focusses on the techniques that have a reasonable clinical validation for being used in clinical trials and patient care. [ABSTRACT FROM AUTHOR]

Penile squamous cell carcinoma (PSCC) with a poor prognosis lacks reliable biomarkers for stratifying patients. Fas-associated death domain (FADD) could regulate cell proliferation and has shown promising diagnostic and prognostic significance in multiple cancers. However, researchers have not determined how FADD exerts its effect on PSCC. In this study, we set out to investigate the clinical features of FADD and the prognostic impact of PSCC. Additionally, we also assessed the role of affecting the immune environment in PSCC. Immunohistochemistry was carried out to evaluate the protein expression of FADD. The difference between FADD high and FADD low was explored by RNA sequencing from available cases. The immune environment evaluation of CD4, CD8, and Foxp3 was performed by immunohistochemical. In this study, we found that FADD was overexpressed in 19.6 (39/199) patients, and the overexpression of FADD was associated with phimosis (p=0.007), N stage (p<0.001), clinical stage (p=0.001), and histologic grade (p=0.005). The overexpression of FADD was an independent prognostic factor for both PFS (HR 3.976, 95% CI 2.413-6.553, p<0.001) and OS (HR 4.134, 95% CI 2.358-7.247, p<0.001). In addition, overexpression of FADD was mainly linked to T cell activation and PD-L1 expression combined with PD-L1 checkpoint in cancer. Further validation demonstrated that overexpression of FADD was positively correlated with the infiltration of Foxp3 in PSCC (p=0.0142). It is the first time to show that overexpression of FADD is an adjunct biomarker with poor prognosis in PSCC and could also serve as a tumor immune environment regulator., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

MRI is the standard modality to assess anatomy and response to treatment in brain and spine tumors given its superb anatomic soft tissue contrast (e.g., T1 and T2) and numerous additional intrinsic contrast mechanisms that can be used to investigate physiology (e.g., diffusion, perfusion, spectroscopy). As such, hybrid MRI and radiotherapy (RT) devices hold unique promise for Magnetic Resonance guided Radiation Therapy (MRgRT). In the brain, MRgRT provides daily visualizations of evolving tumors that are not seen with cone beam CT guidance and cannot be fully characterized with occasional standalone MRI scans. Significant evolving anatomic changes during radiotherapy can be observed in patients with glioblastoma during the 6-week fractionated MRIgRT course. In this review, a case of rapidly changing symptomatic tumor is demonstrated for possible therapy adaptation. For stereotactic body RT of the spine, MRgRT acquires clear isotropic images of tumor in relation to spinal cord, cerebral spinal fluid, and nearby moving organs at risk such as bowel. This visualization allows for setup reassurance and the possibility of adaptive radiotherapy based on anatomy in difficult cases. A review of the literature for MR relaxometry, diffusion, perfusion, and spectroscopy during RT is also presented. These techniques are known to correlate with physiologic changes in the tumor such as cellularity, necrosis, and metabolism, and serve as early biomarkers of chemotherapy and RT response correlating with patient survival. While physiologic tumor investigations during RT have been limited by the feasibility and cost of obtaining frequent standalone MRIs, MRIgRT systems have enabled daily and widespread physiologic measurements. We demonstrate an example case of a poorly responding tumor on the 0.35 T MRIgRT system with relaxometry and diffusion measured several times per week. Future studies must elucidate which changes in MR-based physiologic metrics and at which timepoints best predict patient outcomes. This will lead to early treatment intensification for tumors identified to have the worst physiologic responses during RT in efforts to improve glioblastoma survival. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and the traditional variables extracted from computed tomography (CT) images may not be sufficient to describe all the topological features of lung tissues in COPD patients. We employed an unsupervised three-dimensional (3D) convolutional autoencoder (CAE)-feature constructor (FC) deep learning network to learn from CT data and derive tissue pattern-clusters jointly. We then applied exploratory factor analysis (EFA) to discover the unobserved latent traits (factors) among pattern-clusters. CT images at total lung capacity (TLC) and residual volume (RV) of 541 former smokers and 59 healthy non-smokers from the cohort of the SubPopulations and Intermediate Outcome Measures in the COPD Study (SPIROMICS) were analyzed. TLC and RV images were registered to calculate the Jacobian (determinant) values for all the voxels in TLC images. 3D Regions of interest (ROIs) with two data channels of CT intensity and Jacobian value were randomly extracted from training images and were fed to the 3D CAE-FC model. 80 pattern-clusters and 7 factors were identified. Factor scores computed for individual subjects were able to predict spirometry-measured pulmonary functions. Two factors which correlated with various emphysema subtypes, parametric response mapping (PRM) metrics, airway variants, and airway tree to lung volume ratio were discriminants of patients across all severity stages. Our findings suggest the potential of developing factor-based surrogate markers for new COPD phenotypes. [ABSTRACT FROM AUTHOR]

COPD and idiopathic pulmonary fibrosis (IPF) together represent a considerable unmet medical need, and advances in their treatment lag well behind those of other chronic conditions. Both diseases involve maladaptive repair mechanisms leading to progressive and irreversible damage. However, our understanding of the complex underlying disease mechanisms is incomplete; with current diagnostic approaches, COPD and IPF are often discovered at an advanced stage and existing definitions of COPD and IPF can be misleading. To halt or reverse disease progression and achieve lung regeneration, there is a need for earlier identification and treatment of these diseases. A precision medicine approach to treatment is also important, involving the recognition of disease subtypes, or endotypes, according to underlying disease mechanisms, rather than the current “one-size-fits-all” approach. This review is based on discussions at a meeting involving 38 leading global experts in chronic lung disease mechanisms, and describes advances in the understanding of the pathology and molecular mechanisms of COPD and IPF to identify potential targets for reversing disease degeneration and promoting tissue repair and lung regeneration. We also discuss limitations of existing disease measures, technical advances in understanding disease pathology, and novel methods for targeted drug delivery. [ABSTRACT FROM AUTHOR]

MRI-guided radiotherapy systems have the potential to bring two important concepts in modern radiotherapy together: adaptive radiotherapy and biological targeting. Based on frequent anatomical and functional imaging, monitoring the changes that occur in volume, shape as well as biological characteristics, a treatment plan can be updated regularly to accommodate the observed treatment response. For this purpose, quantitative imaging biomarkers need to be identified that show changes early during treatment and predict treatment outcome. This review provides an overview of the current evidence on quantitative MRI measurements during radiotherapy and their potential as an imaging biomarker on MRI-guided radiotherapy systems. [ABSTRACT FROM AUTHOR]

Purpose: Lung biomechanical models are important for understanding and characterizing lung anatomy and physiology. A key parameter of biomechanical modeling is the underlying tissue elasticity distribution. While human lung elasticity estimations do not have ground truths, model consistency checks can and should be employed to gauge the stability of the estimation techniques. This work proposes such a consistency check using a set of 10 subjects. Methods: We hypothesize that lung dynamics will be stable over a 2–3 min time period and that this stability can be employed to check biomechanical estimation stability. For this purpose, two sets of 12 fast helical free breathing computed tomography scans (FHFBCT) were acquired back‐to‐back for each of the subjects. A published breathing motion model [five‐dimensional CT (5DCT)] was generated from each set. Both of the models were used to generate two biomechanical modeling input sets: (a) The lung geometry at the end‐exhalation, and (b) the voxel displacement map that mapped the end‐exhalation lung geometry with the end‐inhalation lung geometry. Finite element biomechanical lung models were instantiated using the end‐exhalation lung geometries. The models included voxel‐specific lung tissue elasticity values and were optimized using a gradient search approach until the biomechanical model‐generated displacement maps matched those of the 5DCT voxel displacement maps. Finally, the two elasticity distributions associated with each of the patient 5DCTs were quantitatively compared. Because the end‐exhalation geometries differed slightly between the two scan datasets, the elasticity distributions were deformably mapped to one of the exhalation datasets. Results: For the 10 patients, on average, 90% of parenchymal voxels had <2 kPa Young's modulus difference between the two estimations, with a mean voxel difference of only 0.6 kPa. Similarly, 97% of the parenchymal voxels had <2 mm displacement difference between the two models with a mean difference of 0.48 mm. Furthermore, overlapping elasticity histograms for voxels between −600 and −900 HU (parenchymal tissues) showed that the histograms were consistent between the two estimations. Conclusion: In this paper, we demonstrated that biomechanical lung models can be consistently estimated when using motion‐model based imaging datasets, even though the models were created from scans acquired at different breaths. [ABSTRACT FROM AUTHOR]

Background: The purpose of this review is to summarize our own experimental studies carried out over a 13-year period of time using the F98 rat glioma as model for high grade gliomas. We evaluated a binary chemo-radiotherapeutic modality that combines either cisplatin (CDDP) or carboplatin, administered intracerebrally (i.c.) by means of convection-enhanced delivery (CED) or osmotic pumps, in combination with either synchrotron or conventional X-irradiation. Methods: F98 glioma cells were implanted stereotactically into the brains of syngeneic Fischer rats. Approximately 14 days later, either CDDP or carboplatin was administered i.c. by CED, followed 24 h later by radiotherapy using either a synchrotron or, subsequently, megavoltage linear accelerators (LINAC). Results: CDDP was administered at a dose of 3 µg in 5 µL, followed 24 h later with an irradiation dose of 15 Gy or carboplatin at a dose of 20 µg in 10 µL, followed 24 h later with 3 fractions of 8 Gy each, at the source at the European Synchrotron Radiation Facility (ESRF). This resulted in a median survival time (MeST) > 180 days with 33% long term survivors (LTS) for CDDP and a MeST > 60 days with 8 to 22% LTS, for carboplatin. Subsequently it became apparent that comparable survival data could be obtained with megavoltage X-irradiation using a LINAC source. The best survival data were obtained with a dose of 72 µg of carboplatin administered by means of Alzet® osmotic pumps over 7 days. This resulted in a MeST of > 180 days, with 55% LTS. Histopathologic examination of all the brains of the surviving rats revealed no residual tumor cells or evidence of significant radiation related effects. Conclusions: The results obtained using this combination therapy has, to the best of our knowledge, yielded the most promising survival data ever reported using the F98 glioma model. [ABSTRACT FROM AUTHOR]

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Background: Microstructure analyses are gaining interest in cancer MRI as an alternative to the conventional apparent diffusion coefficient (ADC), of which the determinants remain unclear.Purpose: To assess the sensitivity of parameters calculated from a double diffusion encoding (DDE) sequence to changes in a tumor's microstructure early after radiotherapy and to compare them with ADC and histology.Study Type: Cohort study on experimental tumors.Animal Model: Sixteen WAG/Rij rats grafted with one rhabdomyosarcoma fragment in each thigh. Thirty-one were imaged at days 1 and 4, of which 17 tumors received a 20 Gy radiation dose after the first imagery.Field Strength/sequence: 3T. Diffusion-weighted imaging, DDE with flow compensated, and noncompensated measurements.Assessments: 1) To compare, after irradiation, DDE-derived parameters (intracellular fraction, cell size, and cell density) to their histological counterparts (fraction of stained area, minimal Feret diameter, and nuclei count, respectively). 2) To compare percentage changes in DDE-derived parameters and ADC. 3) To evaluate the evolution of DDE-derived parameters describing perfusion.Statistical Tests: Wilcoxon rank sum test.Results: 1) Intracellular fraction, cell size, and cell density were respectively lower (-24%, P < 0.001), higher (+7.5%, P < 0.001) and lower (-38%, P < 0.001) in treated tumors as compared to controls. Fraction of stained area, minimal Feret diameter, and nuclei count were respectively lower (-20%, P < 0.001), higher (+28%, P < 0.001), and lower (-34%, P < 0.001) in treated tumors. 2) The magnitude of ADC's percentage change due to irradiation (16.4%) was superior to the one of cell size (8.4%, P < 0.01) but inferior to those of intracellular fraction (35.5%, P < 0.001) and cell density (42%, P < 0.001). 3) After treatment, the magnitude of the vascular fraction's decrease was higher than the increase of flow velocity (33.3%, vs. 13.3%, P < 0.001).Data Conclusion: The DDE sequence allows quantitatively monitoring the effects of radiotherapy on a tumor's microstructure, whereas ADC only reveals global changes.Evidence Level: 2.Technical Efficacy: Stage 4. J. Magn. Reson. Imaging 2020;52:941-951. [ABSTRACT FROM AUTHOR]

Rationale: Measuring disease extent and progression of systemic sclerosis-associated interstitial lung disease (SSc-ILD) is challenging, with recent studies suggesting potential utility of quantitative measurements from computed tomography (CT) scans.Objectives: To determine the associations of quantitative computed tomography (qCT) density-based measures with physiological parameters, visual CT scores, and survival in patients with SSc-ILD.Methods: Patients with SSc-ILD and volumetric high-resolution CT images with ≤1.25-mm slice thickness were retrospectively identified. Cardiothoracic radiologists produced visual CT scores of ground glass, reticulation, and honeycombing, with visual fibrosis score equaling the sum of reticulation and honeycombing. qCT measurements included high-attenuation areas (HAA), skewness, kurtosis, and mean lung attenuation (MLA). Associations of qCT measures with pulmonary physiology, visual CT scores, and mortality were analyzed using Spearman's rank correlation and Cox regression.Results: A total of 503 CT scans from 170 patients with SSc-ILD were included. qCT HAA, skewness, kurtosis, and MLA were associated with lung function and visual fibrosis scores, independent of age, sex, and pack-years, using both baseline and change data. Baseline and changes in qCT measures (except ∆skewness) were associated with mortality on unadjusted analysis. Changes in all qCT variables remained associated with survival after adjustment for baseline age, sex, pack-years, and lung function, but not when adjusting for changes in lung function. ∆HAA and ∆MLA were associated with survival after adjustment for age, sex, pack-years, and change in visual CT scores.Conclusions: CT density measurements correlate with physiologic impairment and visual CT scores in patients with SSc-ILD; however, they were not associated with survival independent of changes in pulmonary physiology. The clinical utility of more sophisticated qCT measures should be explored. [ABSTRACT FROM AUTHOR]

Cancer cells differ in size from those of their host tissue and are known to change in size during the processes of cell death. A noninvasive method for monitoring cell size would be highly advantageous as a potential biomarker of malignancy and early therapeutic response. This need is particularly acute in brain tumours where biopsy is a highly invasive procedure. Here, diffusion MRI data were acquired in a GL261 glioma mouse model before and during treatment with Temozolomide. The biophysical model VERDICT (Vascular Extracellular and Restricted Diffusion for Cytometry in Tumours) was applied to the MRI data to quantify multi-compartmental parameters connected to the underlying tissue microstructure, which could potentially be useful clinical biomarkers. These parameters were compared to ADC and kurtosis diffusion models, and, measures from histology and optical projection tomography. MRI data was also acquired in patients to assess the feasibility of applying VERDICT in a range of different glioma subtypes. In the GL261 gliomas, cellular changes were detected according to the VERDICT model in advance of gross tumour volume changes as well as ADC and kurtosis models. VERDICT parameters in glioblastoma patients were most consistent with the GL261 mouse model, whilst displaying additional regions of localised tissue heterogeneity. The present VERDICT model was less appropriate for modelling more diffuse astrocytomas and oligodendrogliomas, but could be tuned to improve the representation of these tumour types. Biophysical modelling of the diffusion MRI signal permits monitoring of brain tumours without invasive intervention. VERDICT responds to microstructural changes induced by chemotherapy, is feasible within clinical scan times and could provide useful biomarkers of treatment response. [ABSTRACT FROM AUTHOR]

Background: Mitochondrial dynamics underlies malignant transformation, cancer progression, and response to treatment. Current research presents conflicting evidence for functions of mitochondrial fission and fusion in tumor progression. Here, we investigated how mitochondrial fission and fusion states regulate underlying processes of cancer progression and metastasis in triple-negative breast cancer (TNBC).Methods: We enforced mitochondrial fission and fusion states through chemical or genetic approaches and measured migration and invasion of TNBC cells in 2D and 3D in vitro models. We also utilized kinase translocation reporters (KTRs) to identify single cell effects of mitochondrial state on signaling cascades, PI3K/Akt/mTOR and Ras/Raf/MEK/ERK, commonly activated in TNBC. Furthermore, we determined effects of fission and fusion states on metastasis, bone destruction, and signaling in mouse models of breast cancer.Results: Enforcing mitochondrial fission through chemical or genetic approaches inhibited migration, invasion, and metastasis in TNBC. Breast cancer cells with predominantly fissioned mitochondria exhibited reduced activation of Akt and ERK both in vitro and in mouse models of breast cancer. Treatment with leflunomide, a potent activator of mitochondrial fusion proteins, overcame inhibitory effects of fission on migration, signaling, and metastasis. Mining existing datasets for breast cancer revealed that increased expression of genes associated with mitochondrial fission correlated with improved survival in human breast cancer.Conclusions: In TNBC, mitochondrial fission inhibits cellular processes and signaling pathways associated with cancer progression and metastasis. These data suggest that therapies driving mitochondrial fission may benefit patients with breast cancer. [ABSTRACT FROM AUTHOR]

We have previously characterized the reproducibility of brain tumor relative cerebral blood volume (rCBV) using a dynamic susceptibility contrast magnetic resonance imaging digital reference object across 12 sites using a range of imaging protocols and software platforms. As expected, reproducibility was highest when imaging protocols and software were consistent, but decreased when they were variable. Our goal in this study was to determine the impact of rCBV reproducibility for tumor grade and treatment response classification. We found that varying imaging protocols and software platforms produced a range of optimal thresholds for both tumor grading and treatment response, but the performance of these thresholds was similar. These findings further underscore the importance of standardizing acquisition and analysis protocols across sites and software benchmarking. [ABSTRACT FROM AUTHOR]

Parametric response mapping (PRM) is a computed tomography (CT)-based method to phenotype patients with chronic obstructive pulmonary disease (COPD). It is capable of differentiating emphysema-related air trapping with nonemphysematous air trapping (small airway disease), which helps to identify the extent and localization of the disease. Most studies evaluating the gene expression in smokers and COPD patients related this to spirometric measurements, but none have investigated the relationship with CT-based measurements of lung structure. The current study aimed to examine gene expression profiles of brushed bronchial epithelial cells in association with the PRM-defined CT-based measurements of emphysema (PRMEmph) and small airway disease (PRMfSAD). Using the Top Institute Pharma (TIP) study cohort (COPD = 12 and asymptomatic smokers = 32), we identified a gene expression signature of bronchial brushings, which was associated with PRMEmph in the lungs. One hundred thirty-three genes were identified to be associated with PRMEmph. Among the most significantly associated genes, CXCL11 is a potent chemokine involved with CD8+ T cell activation during inflammation in COPD, indicating that it may play an essential role in the development of emphysema. The PRMEmph signature was then replicated in two independent data sets. Pathway analysis showed that the PRMEmph signature is associated with proinflammatory and notch signaling pathways. Together these findings indicate that airway epithelium may play a role in the development of emphysema and/or may act as a biomarker for the presence of emphysema. In contrast, its role in relation to functional small airways disease is less clear. [ABSTRACT FROM AUTHOR]

Metastatic breast, prostate, lung, and other cancers often affect bone, causing pain, increasing fracture risk, and decreasing function. Management of metastatic bone disease (MBD) is clinically challenging when there is potential but uncertain risk of pathological fracture. Management of MBD has become a major focus within orthopedic oncology with respect to fracture and impending fracture care. If impending skeletal‐related events (SREs), particularly pathologic fracture, could be predicted, increasing evidence suggests that prophylactic surgical treatment improves patient outcomes. However, current fracture risk assessment and radiographic metrics do not have high accuracy and have not been combined with relevant patient survival tools. This review first explores the prevalence, incidence, and morbidity of MBD and associated SREs for different cancer types. Strengths and limitations of current fracture risk scoring systems for spinal stability and long bone fracture are highlighted. More recent computed tomography (CT)‐based structural rigidity analysis (CTRA) and finite element (FE) analysis methods offer advantages of increased specificity (true negative rate), but are limited in availability. Other fracture prediction approaches including parametric response mapping and positron emission tomography/computed tomography measures show early promise. Substantial new information to inform clinical decision‐making includes measures of survival, clinical benefits, and economic analysis of prophylactic treatment compared to after‐fracture stabilization. Areas of future research include use of big data and machine learning to predict SREs, greater access and refinement of CTRA/FE approaches, combination of clinical survival prediction tools with radiographically based fracture risk assessment, and net benefit analysis for fracture risk assessment and prophylactic treatment. [ABSTRACT FROM AUTHOR]

OBJECTIVES Maximal aortic diameter is commonly used to assess aortic risk but poorly predicts the timing and location of dissection events in patients with connective tissue disease who undergo regular imaging surveillance. Hence, we aimed to use available surveillance computed tomography angiography (CTA) scans to investigate the correlation between 3-dimensional (3D) growth and cyclic transmural wall stress with the location of intimal tear formation. METHODS Three type B aortic dissection patients with 2 available electrocardiogram (ECG)-gated pre-dissection CTA scans and without surgical repair during the pre-dissection interval were retrospectively identified at our institution. Vascular deformation mapping was used to measure 3D aortic growth between 2 pre-dissection clinical CTA studies. In addition, we performed a computational analysis to estimate cyclic transmural wall stress in patient-specific baseline CTA geometries. RESULTS In all 3 connective tissue disease patients, the site of type B aortic intimal tear co-localized with areas of peak 3D aortic wall growth. Aortic growth was detected by clinical radiological assessment in only 1 case. Co-localization of peak transmural stress and the site of intimal tear formation were found in all cases. CONCLUSIONS Focal areas of growth and transmural wall stress co-localized with the site of intimal tear formation. These hypothesis-generating results suggest a possible new analytic pathway for a more sophisticated assessment of the factors leading to the initiation of dissection in patients with connective tissue disease. These methods could improve on current risk-stratification techniques. [ABSTRACT FROM AUTHOR]

The integration of magnetic resonance imaging (MRI) for guidance in external beam radiotherapy has faced significant research and development efforts in recent years. The current availability of linear accelerators with an embedded MRI unit, providing volumetric imaging at excellent soft tissue contrast, is expected to provide novel possibilities in the implementation of image-guided adaptive radiotherapy (IGART) protocols. This study reviews open medical physics issues in MR-guided radiotherapy (MRgRT) implementation, with a focus on current approaches and on the potential for innovation in IGART.Daily imaging in MRgRT provides the ability to visualize the static anatomy, to capture internal tumor motion and to extract quantitative image features for treatment verification and monitoring. Those capabilities enable the use of treatment adaptation, with potential benefits in terms of personalized medicine. The use of online MRI requires dedicated efforts to perform accurate dose measurements and calculations, due to the presence of magnetic fields. Likewise, MRgRT requires dedicated quality assurance (QA) protocols for safe clinical implementation.Reaction to anatomical changes in MRgRT, as visualized on daily images, demands for treatment adaptation concepts, with stringent requirements in terms of fast and accurate validation before the treatment fraction can be delivered. This entails specific challenges in terms of treatment workflow optimization, QA, and verification of the expected delivered dose while the patient is in treatment position. Those challenges require specialized medical physics developments towards the aim of fully exploiting MRI capabilities. Conversely, the use of MRgRT allows for higher confidence in tumor targeting and organs-at-risk (OAR) sparing.The systematic use of MRgRT brings the possibility of leveraging IGART methods for the optimization of tumor targeting and quantitative treatment verification. Although several challenges exist, the intrinsic benefits of MRgRT will provide a deeper understanding of dose delivery effects on an individual basis, with the potential for further treatment personalization. [ABSTRACT FROM AUTHOR]

Objectives: Chronic obstructive pulmonary disease (COPD) is characterized by variable contributions of emphysema and airway disease on computed tomography (CT), and still little is known on their temporal evolution. We hypothesized that quantitative CT (QCT) is able to detect short-time changes in a cohort of patients with very severe COPD.Methods: Two paired in- and expiratory CT each from 70 patients with avg. GOLD stage of 3.6 (mean age = 66 ± 7.5, mean FEV1/FVC = 35.28 ± 7.75) were taken 3 months apart and analyzed by fully automatic software computing emphysema (emphysema index (EI), mean lung density (MLD)), air-trapping (ratio expiration to inspiration of mean lung attenuation (E/I MLA), relative volume change between - 856 HU and - 950 HU (RVC856-950)), and parametric response mapping (PRM) parameters for each lobe separately and the whole lung. Airway metrics measured were wall thickness (WT) and lumen area (LA) for each airway generation and the whole lung.Results: The average of the emphysema parameters (EI, MLD) increased significantly by 1.5% (p < 0.001) for the whole lung, whereas air-trapping parameters (E/I MLA, RVC856-950) were stable. PRMEmph increased from 34.3 to 35.7% (p < 0.001), whereas PRMNormal decrased from 23.6% to 22.8% (p = 0.012). WT decreased significantly from 1.17 ± 0.18 to 1.14 ± 0.19 mm (p = 0.036) and LA increased significantly from 25.08 ± 4.49 to 25.84 ± 4.87 mm2 (p = 0.041) for the whole lung. The generation-based analysis showed heterogeneous results.Conclusion: QCT detects short-time progression of emphysema in severe COPD. The changes were partly different among lung lobes and airway generations, indicating that QCT is useful to address the heterogeneity of COPD progression.Key Points: • QCT detects short-time progression of emphysema in severe COPD in a 3-month period. • QCT is able to quantify even slight parenchymal changes, which were not detected by spirometry. • QCT is able to address the heterogeneity of COPD, revealing inconsistent changes individual lung lobes and airway generations. [ABSTRACT FROM AUTHOR]

Background: Early prediction of nonresponse is essential in order to avoid inefficient treatments.Purpose: To evaluate if parametrical response mapping (PRM)-derived biomarkers could predict early morphological response (EMR) and pathological complete response (pCR) 24-72 hours after initiation of chemotherapy treatment and whether concentric analysis of nonresponding PRM regions could better predict response.Study Type: This was a retrospective analysis of prospectively acquired cohort, nonrandomized, monocentric, diagnostic study.Population: Sixty patients were initially recruited, with 39 women participating in the final cohort.Field Strength/sequence: A 1.5T scanner was used for MRI examinations.Assessment: Dynamic contrast-enhanced (DCE)-MR images were acquired at baseline (timepoint 1, TP1), 24-72 hours after the first chemotherapy (TP2), and after the end of anthracycline treatment (TP3). PRM was performed after fusion of T1 subtraction images from TP1 and TP2 using an affine registration algorithm. Pixels with an increase of more than 10% of their value (PRMdce+) were corresponding nonresponding regions of the tumor. Patients with a decrease of maximum diameter (%dDmax) between TP1 and TP3 of more than 30% were defined as EMR responders. pCR patients achieved a residual cancer burden score of 0.Statistical Tests: T-test, receiver operating characteristic (ROC) curves, and logistic regression were used for the analysis.Results: PRM showed a statistical difference between pCR response groups (P < 0.01) and AUC of 0.88 for the prediction of non-pCR. Logistic regression analysis demonstrated that PRMdce+ and Grade II were significant (P < 0.01) for non-pCR prediction (AUC = 0.94). Peripheral tumor region demonstrated higher performance for the prediction of non-pCR (AUC = 0.85) than intermediate and central zones; however, statistical comparison showed no significant difference.Data Conclusion: PRM could be predictive of non-pCR 24-72 hours after initiation of chemotherapy treatment. Moreover, the peripheral region showed increased AUC for non-pCR prediction and increased signal intensity during treatment for non-pCR tumors, information that could be used for optimal tissue sampling.Level Of Evidence: 1 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2020;51:1403-1411. [ABSTRACT FROM AUTHOR]

The microstructure changes associated with degeneration of spinal axons in amyotrophic lateral sclerosis (ALS) may be reflected in altered water diffusion properties, potentially detectable with diffusion-weighted (DW) MRI. Prior work revealed the classical mono-exponential model fails to precisely depict decay in DW signal at high b-values. In this study, we aim to investigate signal decay behaviors at ultra-high b-values for non-invasive assessment of spinal cord alterations in the transgenic SOD1G93A mouse model of ALS. A multiexponential diffusion analysis using regularized non-negative least squares (rNNLS) algorithm was applied to a series of thirty DW MR images with b-values ranging from 0 to 858,022 s/mm2 on ex vivo spinal cords of transgenic SOD1G93A and age-matched control mice. We compared the distributions of measured diffusion coefficient fractions between the groups. The measured diffusion weighted signals in log-scale showed non-linear decay behaviors with increased b-values. Faster signal decays were observed with diffusion gradients applied parallel to the long axis of the spinal cord compared to when oriented in the transverse direction. Multiexponential analysis at the lumbar level in the spinal cord identified ten subintervals. A significant decrease of diffusion coefficient fractions was found in the ranges of [1.63×10−8,3.70×10−6] mm2/s (P = 0.0002) and of [6.01×10−6,4.20×10−5] mm2/s (P = 0.0388) in SOD1G93A mice. Anisotropic diffusion signals persisted at ultra-high b-value DWIs of the mouse spinal cord and multiexponential diffusion analysis offers the potential to evaluate microstructural alterations of ALS-affected spinal cord non-invasively. [ABSTRACT FROM AUTHOR]

Chronic obstructive pulmonary disease (COPD) is a devastating lung disease with a high personal and societal burden. Exposure to toxic particles and gases, including cigarette smoke, is the main risk factor for COPD. Together with smoking cessation, current treatment strategies of COPD aim to improve symptoms and prevent exacerbations, but there is no disease-modifying treatment. The biggest drawback of today's COPD treatment regimen is the 'one size fits all' pharmacological intervention, mainly based on disease severity and symptoms and not the individual's disease pathology. To halt the worrying increase in the burden of COPD, disease management needs to be advanced with a focus on personalized treatment. The main pathological feature of COPD includes a chronic and abnormal inflammatory response within the lungs, which results in airway and alveolar changes in the lung as reflected by (small) airways disease and emphysema. Here we discuss recent developments related to the abnormal inflammatory response, ECM and age-related changes, structural changes in the small airways and the role of sex-related differences, which are all relevant to explain the individual differences in the disease pathology of COPD and improve disease endotyping. Furthermore, we will discuss the most recent developments of new treatment strategies using biologicals to target specific pathological features or disease endotypes of COPD. [ABSTRACT FROM AUTHOR]

Objective: This study was conducted in order to determine the optimal timing of diffusion-weighted magnetic resonance imaging (DW-MRI) for prediction of pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) for esophageal cancer.Methods: Patients with esophageal adenocarcinoma or squamous cell carcinoma who planned to undergo nCRT followed by surgery were enrolled in this prospective study. Patients underwent six DW-MRI scans: one baseline scan before the start of nCRT and weekly scans during 5 weeks of nCRT. Relative changes in mean apparent diffusion coefficient (ADC) values between the baseline scans and the scans during nCRT (ΔADC(%)) were compared between pathologic complete responders (pCR) and non-pCR (tumor regression grades 2-5). The discriminative ability of ΔADC(%) was determined based on the c-statistic.Results: A total of 24 patients with 142 DW-MRI scans were included. pCR was observed in seven patients (29%). ΔADC(%) from baseline to week 2 was significantly higher in patients with pCR versus non-pCR (median [IQR], 36% [30%, 41%] for pCR versus 16% [14%, 29%] for non-pCR, p = 0.004). The ΔADC(%) of the second week in combination with histology resulted in the highest c-statistic for the prediction of pCR versus non-pCR (0.87). The c-statistic of this model increased to 0.97 after additional exclusion of patients with a small tumor volume (< 7 mL, n = 3) and tumor histology of the resection specimen other than adenocarcinoma or squamous cell carcinoma (n = 1).Conclusion: The relative change in tumor ADC (ΔADC(%)) during the first 2 weeks of nCRT is the most predictive for pathologic complete response to nCRT in esophageal cancer patients.Key Points: • DW-MRI during the second week of neoadjuvant chemoradiotherapy is most predictive for pathologic complete response in esophageal cancer. • A model including ΔADCweek 2was able to discriminate between pathologic complete responders and non-pathologic complete responders in 87%. • Improvements in future MRI studies for esophageal cancer may be obtained by incorporating motion management techniques. [ABSTRACT FROM AUTHOR]

Introduction: To identify patients with aneurysmal degeneration of the native aorta following type A aortic dissection (TAAD), reproducible serial measurements of aortic dimensions are critical. We used a systematic workflow for measuring aortic geometry following TAAD, using computed tomography angiography data, and test its reproducibility.Methods: The workflow for aortic measurements included centerline generation, luminal diameter, and area measurement at six anatomically defined locations along the aorta and luminal volumetric measurements in the descending aorta. Two independent observers measured the aortic geometry in 20 surgically repaired TAAD patients, preoperatively and at 3 months follow-up. To test reproducibility, intraobserver and interobserver agreement scores were analyzed using a concordance correlation coefficient (CCC).Results: The interobserver agreement scores of the diameter, area, and volumetric measurements in the descending aorta were acceptable. The agreement scores of the area measurements were highest, with CCCs ranging from 0.909 to 0.984. Luminal diameter measurements scored lower than luminal area measurements and were least reproducible at the mid aortic arch (CCC < 0.886). Overall, intraobserver agreement scores were better than interobserver agreement scores (SD of mean difference was 1.89 vs 1.94 for intraobserver vs interobserver diameter measurements, and 0.61 vs 0.66 for area measurements).Conclusion: Although overall reproducibility was acceptable in descending aortic measurements, our results show that it remains challenging to reliably measure luminal diameters, compared with areas. To aid identification of early adverse remodeling following acute TAAD, novel two- and three-dimensional measurement techniques are needed that capture locoregional changes in the false lumen and true lumen morphology more accurately. [ABSTRACT FROM AUTHOR]

Contract Grant Sponsor: Health Research Fund of Central Denmark Region.Background: Diffusion gradient nonlinearity (DGNL) bias causes apparent diffusion coefficient (ADC) values to drop with increasing superior-inferior (SI) isocenter offset. This is a concern when performing quantitative diffusion-weighted imaging (DWI).Purpose/hypothesis: To investigate if DGNL ADC bias can be corrected in breast cancer bone metastases using a clinical DWI protocol and an online correction algorithm.Study Type: Prospective.Subjects/phantom: A diffusion phantom (Model 128, High Precision Devices, Boulder, CO) was used for in vitro validation. Twenty-three women with bone-metastasizing breast cancer were enrolled to assess DGNL correction in vivo.Field Strength/sequence: DWI was performed on a 1.5T MRI system as single-shot, spin-echo, echo-planar imaging with short-tau inversion recovery (STIR) fat-saturation. ADC maps with and without DGNL correction were created from the b50 and b800 images.Assessment: Uncorrected and DGNL-corrected ADC values were measured in phantom and bone metastases by placing regions of interest on b800 images and copying them to the ADC map. The SI offset was recorded.Statistical Tests: In all, 79 bone metastases were assessed. ADC values with and without DGNL correction were compared at 14 cm SI offset using a two-tailed t-test.Results: In the diffusion phantom, DGNL correction increased SI offset, where ADC bias was lower than 5%, from 7.3-13.8 cm. Of the 23 patients examined, six had no metastases in the covered regions. In the remaining patients, bias of uncorrected bone metastasis ADC values was 19.1% (95% confidence interval [CI]: 15.4-22.9%) at 14 cm SI offset. After DGNL correction, ADC bias was significantly reduced to 3.5% (95% CI: 0.7-6.3%, P < 0.001), thus reducing bias due to DGNL by 82%.Data Conclusion: Online DGNL correction corrects DGNL ADC value bias and allows increased station lengths in the SI direction.Level Of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:904-911. [ABSTRACT FROM AUTHOR]

Background: Diffusion weighted magnetic resonance imaging (DW-MRI) holds great potential for monitoring treatment response in cancer patients shortly after initiation of radiotherapy. It is hypothesized that a decrease in cellular density of irradiated cancerous tissue will lead to an increase in quantitative apparent diffusion coefficient (ADC) values. DW-MRI can therefore serve as a non-invasive marker of cell death and apoptosis in response to treatment. In the present study, we aimed to investigate the applicability of DW-MRI in preclinical models to monitor radiation-induced treatment response. In addition, we compared DW-MRI with ex vivo measures of cell density, cell death and apoptosis.Methods: DW-MRI was tested in two different syngeneic mouse models, a colorectal cancer (CT26) and a breast cancer (4 T1). ADC values were compared with quantitative determinations of apoptosis and cell death by flow cytometry. Furthermore, ADC-values were also compared to histological measurement of cell density on tumor sections.Results: We found a significant correlation between ADC-values and apoptotic state in the CT26 model (P = 0.0031). A strong correlation between the two measurements of ADC-value and apoptotic state was found in both models, which were also present when comparing ADC-values to cell densities.Conclusions: Our findings demonstrate that DW-MRI can be used for non-invasive monitoring of radiation-induced changes in cell state during cancer therapy. ADC values reflect ex vivo cell density and correlates well with apoptotic state, and can hereby be described as a marker for the cell state after therapy and used as a non-invasive response marker. [ABSTRACT FROM AUTHOR]

Background: The values that have been received from apparent diffusion coefficient (ADC) maps of diffusion-weighted magnetic resonance imaging (DW-MRI) might play a vital role in evaluating tumors and their grading scale. Purpose: To investigate the predictive role of this heterogeneity in brain tumor pathologies and its correlation with Ki-67. Material and Methods: A total of 124 patients with brain tumors underwent brain MRI with gadolinium injection. ADC and standard deviation of each lesion have been obtained from manual localization of the region of interest on the ADC map. A receiver operating characteristic analysis was conducted to determine the minimum cut-off values of the mean ADC and mean standard deviation of ADC maps having the highest sensitivity and specificity to differentiate high-grade and low-grade tumors. Results: Mean ADC values in the region of interest were significantly lower for malignant tumors (grade IV and metastasis) than grade I brain tumors, while a higher mean standard deviation was observed. In a more detailed comparison of tumor groups, the mean standard deviation of the ADC for glioblastoma multiform was significantly higher than meningioma grade I (P < 0.001) and metastasis was significantly higher than grade III and IV astrocytic tumors (P = 0.004). The analysis of Ki-67 proliferation index and mean ADC values in gliomas showed a significant inverse correlation between the parameters (r = –0.0429, P < 0.001) and direct correlation between Ki-67 and mean standard deviation of the ADC (r = 0.551, P < 0.001). As an index for the ADC to differentiate high-grade and low-grade tumors, the cut-off values of 1.40*10−3 mm2/s for mean ADC and 45*10−3 mm2/s for mean standard deviation have the highest combination of sensitivity, specificity, and area under the curve. Conclusion: The mean value and standard deviation of the ADC could be considered for differentiating between low-grade and high-grade brain tumors, as two available non-invasive methods. [ABSTRACT FROM AUTHOR]

Target lung tissue selection remains a challenging task to perform for treating severe emphysema with lung volume reduction (LVR). In order to target the treatment candidate, the percentage of low attenuation volume (LAV%) representing the proportion of emphysema volume to whole lung volume is measured using computed tomography (CT) images. Although LAV% have shown to have a correlation with lung function in patients with chronic obstructive pulmonary disease (COPD), similar measurements of LAV% in whole lung or lobes may have large variations in lung function due to emphysema heterogeneity. The functional information of regional emphysema destruction is required for supporting the choice of optimal target. The purpose of this study is to develop an emphysema heterogeneity descriptor for the three-dimensional emphysematous bullae according to the size variations of emphysematous density (ED) and their spatial distribution. The second purpose is to derive a predictive model of airflow limitation based on the regional emphysema heterogeneity. Deriving the bullous representation and grouping them into four scales in the upper and lower lobes, a predictive model is computed using the linear model fitting to estimate the severity of lung function. A total of 99 subjects, 87 patients with mild to very severe COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage I~IV) and 12 control participants with normal lung functions (forced expiratory volume in one second (FEV1)/forced vital capacity (FVC) > 0.7) were evaluated. The final model was trained with stratified cross-validation on randomly selected 75% of the dataset (n = 76) and tested on the remaining dataset (n = 23). The dispersed cases of LAV% inconsistent with their lung function outcome were evaluated, and the correlation study suggests that comparing to LAV of larger bullae, the widely spread smaller bullae with equivalent LAV has a larger impact on lung function. The testing dataset has the correlation of r = −0.76 (p < 0.01) between the whole lung LAV% and FEV1/FVC, whereas using two ED % of scales and location-dependent variables to predict the emphysema-associated FEV1/FVC, the results shows their correlation of 0.82 (p < 0.001) with clinical FEV1/FVC. [ABSTRACT FROM AUTHOR]

Background: Pulmonary and systemic inflammation are central features of chronic obstructive pulmonary disease (COPD). Previous studies have demonstrated relationships between biologically active extracellular matrix components, or matrikines, and COPD pathogenesis. We studied the relationships between the matrikine acetyl-proline-glycine-proline (AcPGP) in sputum and plasma and clinical features of COPD.Methods: Sputum and plasma samples were obtained from COPD participants in the SPIROMICS cohort at enrollment. AcPGP was isolated using solid phase extraction and measured by mass spectrometry. Demographics, spirometry, quality of life questionnaires, and quantitative computed tomography (CT) imaging with parametric response mapping (PRM) were obtained at baseline. Severe COPD exacerbations were recorded at 1-year of prospective follow-up. We used linear and logistic regression models to measure associations between AcPGP and features of COPD, and Kaplan-Meier analyses to measure time-to-first severe exacerbation.Results: The 182 COPD participants in the analysis were 66 ± 8 years old, 62% male, 84% White race, and 39% were current smokers. AcPGP concentrations were 0.61 ± 1.89 ng/mL (mean ± SD) in sputum and 0.60 ± 1.13 ng/mL in plasma. In adjusted linear regression models, sputum AcPGP was associated with FEV1/FVC, spirometric GOLD stage, PRM-small airways disease, and PRM-emphysema. Sputum AcPGP also correlated with severe AECOPD, and elevated sputum AcPGP was associated with shorter time-to-first severe COPD exacerbation. In contrast, plasma AcPGP was not associated with symptoms, pulmonary function, or severe exacerbation risk.Conclusions: In COPD, sputum but not plasma AcPGP concentrations are associated with the severity of airflow limitation, small airways disease, emphysema, and risk for severe AECOPD at 1-year of follow-up.Trial Registration: ClinicalTrials.gov: NCT01969344 (SPIROMICS). [ABSTRACT FROM AUTHOR]

Rationale: Chronic obstructive pulmonary disease (COPD) has been associated with numerous genetic variants, yet the extent to which its genetic risk is mediated by variation in lung structure remains unknown.Objectives: To characterize associations between a genetic risk score (GRS) associated with COPD susceptibility and lung structure on computed tomography (CT).Methods: We analyzed data from MESA Lung (Multi-Ethnic Study of Atherosclerosis Lung Study), a U.S. general population-based cohort, and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study). A weighted GRS was calculated from 83 SNPs that were previously associated with lung function. Lung density, spatially matched airway dimensions, and airway counts were assessed on full-lung CT. Generalized linear models were adjusted for age, age squared, sex, height, principal components of genetic ancestry, smoking status, pack-years, CT model, milliamperes, and total lung volume.Measurements and Main Results: MESA Lung and SPIROMICS contributed 2,517 and 2,339 participants, respectively. Higher GRS was associated with lower lung function and increased COPD risk, as well as lower lung density, smaller airway lumens, and fewer small airways, without effect modification by smoking. Adjustment for CT lung structure, particularly small airway measures, attenuated associations between the GRS and FEV1/FVC by 100% and 60% in MESA and SPIROMICS, respectively. Lung structure (P < 0.0001), but not the GRS (P > 0.10), improved discrimination of moderate-to-severe COPD cases relative to clinical factors alone.Conclusions: A GRS associated with COPD susceptibility was associated with CT lung structure. Lung structure may be an important mediator of heritability and determinant of personalized COPD risk. [ABSTRACT FROM AUTHOR]

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions. [ABSTRACT FROM AUTHOR]

Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic resonance imaging. Although these techniques have been used for more than two decades to study tumor diffusion, perfusion, and/or permeability, the methods and studies on how to reduce measurement error and bias in the derived imaging metrics is still lacking in the literature. This is of paramount importance because the objective is to translate these quantitative imaging biomarkers (QIBs) into clinical trials, and ultimately in clinical practice. Standardization of the image acquisition using appropriate phantoms is the first step from a technical performance standpoint. The next step is to assess whether the imaging metrics have clinical value and meet the requirements for being a QIB as defined by the Radiological Society of North America's Quantitative Imaging Biomarkers Alliance (QIBA). The goal and mission of QIBA and the National Cancer Institute Quantitative Imaging Network (QIN) initiatives are to provide technical performance standards (QIBA profiles) and QIN tools for producing reliable QIBs for use in the clinical imaging community. Some of QIBA's development of quantitative diffusion‐weighted imaging and dynamic contrast‐enhanced QIB profiles has been hampered by the lack of literature for repeatability and reproducibility of the derived QIBs. The available research on this topic is scant and is not in sync with improvements or upgrades in MRI technology over the years. This review focuses on the need for QIBs in oncology applications and emphasizes the importance of the assessment of their reproducibility and repeatability. Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2019;49:e101–e121. [ABSTRACT FROM AUTHOR]

Exhaled breath temperature (EBT) is a biomarker of inflammation and vascularity of the airways already shown to predict incident COPD. This cross-sectional study was aimed to assess the potential of EBT in identifying "healthy" smokers susceptible to cigarette smoke toxicity of the airways and to the risk of developing COPD by analysing the dynamics of EBT after smoking a cigarette and its associations with their demographics (age, smoking burden) and lung function. The study included 55 current smokers of both sexes, 29–62 years of age, with median smoking exposure of 15 (10–71.8) pack-years. EBT was measured at baseline and 5, 15, 30, 45, and 60 min after smoking a single cigarette. Lung function was measured with spirometry followed by a bronchodilator test. To compare changes in EBT between repeated measurements we used the analysis of variance and the area under the curve (EBTAUC) as a dependent variable. Multivariate regression analysis was used to look for associations with patient characteristics and lung function in particular. The average (±SD) baseline EBT was 33.42±1.50 °C. The highest significant increase to 33.84 (1.25) °C was recorded 5 min after the cigarette was smoked (p=0.003), and it took one hour for it to return to the baseline. EBTAUC showed significant repeatability (ICC=0.85, p<0.001) and was significantly associated with age, body mass index, number of cigarettes smoked a day, baseline EBT, and baseline FEF75 (R2=0.39, p<0.001 for the model). Our results suggest that EBT after smoking a single cigarette could be used as early risk predictor of changes associated with chronic cigarette smoke exposure. [ABSTRACT FROM AUTHOR]

Purpose of Review: Accurate prediction of early treatment response in patients receiving neoadjuvant chemotherapy for breast cancer is essential to provide patients with the best care. Diffusion-weighted magnetic resonance imaging (DWI) provides a novel approach to distinguishing responders from non-responders. This article aims to review the literature regarding the accuracy of DWI in predicting patients who will respond to neoadjuvant chemotherapy at an early stage within their treatment pathway. Recent Findings: The initial search yielded 11,171 articles. After careful review, 19 of these articles were found to adhere to the inclusion criteria. Despite the varied research methods and data analysis across the studies, 16 out of 19 of these studies (84%) demonstrated DWI to be an accurate predictor of neoadjuvant chemotherapy response. Summary: These results are promising; however, further multi-centre studies with larger sample sizes, homogenous imaging and treatment parameters and formal assessment of pathological response are required to accurately evaluate the use of DWI as an early predictor of neoadjuvant chemotherapy response in patients with breast cancer. [ABSTRACT FROM AUTHOR]

Background: In the study, the value of pre-treatment dynamic contrast-enhanced (DCE) and diffusion weighted (DW) MRI-derived parameters as well as their changes early during treatment was evaluated for predicting disease-free survival (DFS) and overall survival (OS) in patients with locoregionally advanced head and neck squamous carcinoma (HNSCC) treated with concomitant chemoradiotherapy (cCRT) with cisplatin. Patients and methods: MRI scans were performed in 20 patients with locoregionally advanced HNSCC at baseline and after 10 Grays (Gy) of cCRT. Tumour apparent diffusion coefficient (ADC) and DCE parameters (volume transfer constant [Ktrans], extracellular extravascular volume fraction [ve], and plasma volume fraction [Vp]) were measured. Relative changes in parameters from baseline to 10 Gy were calculated. Univariate and multivariate Cox regression analysis were conducted. Receiver operating characteristic (ROC) curve analysis was employed to identify parameters with the best diagnostic performance. Results: None of the parameters was identified to predict for DFS. On univariate analysis of OS, lower pre-treatment ADC (p = 0.012), higher pre-treatment Ktrans (p = 0.026), and higher reduction in Ktrans (p = 0.014) from baseline to 10 Gy were identified as significant predictors. Multivariate analysis identified only higher pre-treatment Ktrans (p = 0.026; 95% CI: 0.000–0.132) as an independent predictor of OS. At ROC curve analysis, pre-treatment Ktrans yielded an excellent diagnostic accuracy (area under curve [AUC] = 0.95, sensitivity 93.3%; specificity 80 %). Conclusions: In our group of HNSCC patients treated with cisplatin-based cCRT, pre-treatment Ktrans was found to be a good predictor of OS. [ABSTRACT FROM AUTHOR]

Background and Objectives: Fee for service (FFS), the dominant payment model for primary care in the United States, compensates physicians based on volume. There are many initiatives exploring alternative payment models that prioritize value over volume. The Family Medicine for America's Health (FMAHealth) Payment Team has developed a comprehensive primary care payment (CPCP) model to support the move from activity- and volume-based payment to performance-based payment for value.Methods: In 2016-2017, the FMAHealth Payment Team performed a comprehensive study of the current state of primary care payment models in the United States. This study explored the features, motivations, successes, and failures of a wide variety of payment arrangements.Results: The results of this work have informed a definition of comprehensive primary care payment (CPCP) as well as a CPCP calculator. This quantitative methodology calculates a base rate and includes modifiers that recognize the importance of infrastructure and resources that have been found to be successful in innovative models. The modifiers also incorporate adjustments for chronic disease burden, social determinants of health, quality, and utilization.Conclusions: The calculator and CPCP methodology offer a potential roadmap for transitioning from volume to value and details how to calculate such an adjustable comprehensive payment. This has impact and interest for all levels of the health care system and is intended for use by practices of all types as well as health systems, employers, and payers. [ABSTRACT FROM AUTHOR]

The article concerns the obtainment of liposomal doxorubicin (Dox) in which liposomes are externally modified with a targeting peptide able to drive the formulation in a selective way on membrane receptors overexpressed in tumors. We developed a kit composed by three different vials: (A) a vial containing a sterile, translucent, red dispersion of the liposomal doxorubicin drug (Doxil®), (B) a vial filled with a lyophilized powder of a modified phospholipid with a reactive function (DSPE-Peg-maleimide), and (C) a vial containing a 1-9 bombesin peptide analogue (Cys-BN-AA1) chemically modified to react in stoichiometric ratio respect to DSPE-Peg-maleimide. The chosen peptide is a stable analogue antagonist of the wild-type 1-9 bombesin peptide; it is very stable in serum; maintains high specificity, with nanomolar affinity, towards gastrin release peptide receptors (GRPRs indicated also as BB2); and is overexpressed in some cancer cells. Results on animal studies clearly indicate that in mice treated with the kit product (i.e., pegylated liposomal Dox modified with the bombesin analogue, Doxil-BN-AA1), tumor growth is reduced, with an improved efficacy respect to mice treated with non-modified pegylated liposomal Dox or with saline solution. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate correlations between tumour response to definitive chemoradiotherapy (CRT) in oesophageal squamous cell carcinoma (SCC) and histogram-derived apparent diffusion coefficient (ADC) parameters on diffusion-weighted MR images.Methods: Forty patients with clinical T3-4 oesophageal SCC underwent concurrent CRT. MR examination at 3 T was performed 1-3 days prior to CRT. Readout-segmented echo-planar diffusion imaging was used to acquire ADC maps. Pre- and post-treatment CT examinations were performed. Histogram parameters (mean, 10th, 25th, 50th, 75th, 90th percentiles, skewness and kurtosis) of the ADC values were compared with post-treatment disease status based on RECIST and the tumour regression ratio.Results: None of the ADC parameters showed significant correlation with post-treatment status (range of Spearman's ρ values - 0.19 to 0.14, range of p values 0.22-0.47) or tumour regression ratio (range of Spearman's ρ values - 0.045 to 0.18, range of p values 0.26-0.96). Neither progression-free survival (PFS) (p = 0.17) nor overall survival (OS) (p = 0.15) was significantly different between the two groups corresponding to the lower (< median) and upper arms (≥ median) of the mean ADC values.Conclusions: Histogram-derived pretreatment ADC parameters were not predictive imaging biomarkers for tumour response to CRT in patients with oesophageal SCC.Key Points: • Apparent diffusion coefficient (ADC) values are derived from diffusion-weighted MR imaging. • High-resolution diffusion-weighted images are generated by readout-segmented echo-planar diffusion imaging. • Readout-segmented echo-planar diffusion-weighted imaging enabled evaluation of ADC parameters. • Pretreatment ADC parameters do not predict chemoradiotherapy response in patients with oesophageal carcinoma. [ABSTRACT FROM AUTHOR]

There have been various reports in the literature of an in vivo model for giant cell tumor of bone (GCTB). However, few suitable animal models of GCTB have been established, due to the fact that GCTB contains three histologically different cell types. To the best of our knowledge, injection of patient‑derived GCTB cells into bone environment has not been reported until now. In the present study, the biological behavior of GCTB cells in nude mice was investigated through intratibial injection of patient‑derived GCTB cells. Patient‑derived GCTB cells were obtained from 5 patients who had not undergone chemo‑ and radiotherapy. Once isolated, the cell suspension was injected into the tibias of nude mice. The growth process was monitored by weekly observation and photographic documentation using X‑ray. Four months after injection, nude mice were sacrificed and the injected tibial samples were fixed, and further analyzed using micro‑computed tomography (micro‑CT), standard histology, tartrate‑resistant acid phosphatase (TRAP) staining and mitochondrial immunofluorescence staining. X‑ray, micro‑CT and standard histology revealed osteolytic destruction in the proximal end of the tibia. TRAP staining identified TRAP‑positive, osteoclast‑like cells distributed in the bone marrow interface of the lesion area. Anti‑human mitochondrial immunofluorescence staining confirmed that the surviving cells in the osteolytic destruction were of human GCTB cell origin. These findings indicate that intratibial injection of patient‑derived GCTB cells may elicit osteolytic destruction in nude mice. The results of the current study present a novel animal model for GCTB, opening new perspectives to investigate this disease and develop therapeutic agents. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to provide and optimize a performing algorithm for predicting the breast cancer response rate to the first round of chemotherapy using Magnetic Resonance Imaging (MRI). This provides an early recognition of breast tumor reaction to chemotherapy by using the Parametric Response Map (PRM) method.Methods: PRM may predict the breast cancer response to chemotherapy by analyzing voxel-by-voxel temporal intra-tumor changes during one round of chemotherapy. Indeed, the tumor recognizes intra-tumor changes concerning its vascularity, which is an important criterion in the present study. This method is mainly based on spatial image affine registration between the breast tumor MRI volumes, acquired before and after the first cycle of chemotherapy, and region growing segmentation of the tumor volume. To evaluate our method, we used a retrospective study of 40 patients provided by a collaborating institute.Results: PRM allows a color map to be created with the percentages of positive, negative and stable breast tumor response during the first round of chemotherapy, identifying each region with its response rate. We assessed the accuracy of the proposed method using technical and medical validation methods. The technical validation was based on landmarks-based registration and fully manual segmentation. The medical evaluation was based on the accuracy calculation of the standard reference of anatomic pathology. The p-values and the Area Under the Curve (AUC) of the Receiver Operating Characteristics were calculated to evaluate the proposed PRM method.Conclusion: We performed and evaluated the proposed PRM method to study and analyze the behavior of a tumor during the first round of chemotherapy, based on the intra-tumor changes of MR breast tumor images. The AUC obtained for the PRM method is considered as relevant in the early prediction of breast tumor response. [ABSTRACT FROM AUTHOR]

Objective To assess the optimal timing and predictive value of early intra-treatment changes in multimodality functional and molecular imaging (FMI) parameters as biomarkers for clinical remission in patients receiving chemoradiation for head and neck squamous cell carcinoma (HNSCC). Methods Thirty-five patients with stage III-IVb (AJCC 7th edition) HNSCC prospectively underwent 18F-FDG-PET/CT, and diffusion-weighted (DW), dynamic contrast-enhanced (DCE) and susceptibility-weighted MRI at baseline, week 1 and week 2 of chemoradiation. Patients with evidence of persistent or recurrent disease during follow-up were classed as non-responders. Changes in FMI parameters at week 1 and week 2 were compared between responders and non-responders with the Mann-Whitney U test. The significance threshold was set at a p value of <0.05. Results There were 27 responders and 8 non-responders. Responders showed a greater reduction in PET-derived tumor total lesion glycolysis (TLG40%; p = 0.007) and maximum standardized uptake value (SUVmax; p = 0.034) after week 1 than nonresponders but these differences were absent by week 2. In contrast, it was not until week 2 that MRI-derived parameters were able to discriminate between the two groups: larger fractional increases in primary tumor apparent diffusion coefficient (ADC; p < 0.001), volume transfer constant (Ktrans; p = 0.012) and interstitial space volume fraction (Ve; p = 0.047) were observed in responders versus non-responders. ADC was the most powerful predictor (Δ >17%, AUC 0.937). Conclusion Early intra-treatment changes in FDG-PET, DW and DCE MRI-derived parameters are predictive of ultimate response to chemoradiation in HNSCC. However, the optimal timing for assessment with FDG-PET parameters (week 1) differed from MRI parameters (week 2). This highlighted the importance of scanning time points for the design of FMI risk-stratified interventional studies. [ABSTRACT FROM AUTHOR]