Prophylactic Antibiotic Choice and Deep Infection in Lower Extremity Endoprosthetic Reconstruction: Comparison of Cefazolin, Cefazolin-Vancomycin, and Alternative Regimens.

INTRODUCTION: Infection is a common mode of failure in lower extremity endoprostheses. The Prophylactic Antibiotic Regimens in Tumor Surgery trial reported that 5 days of cefazolin had no difference in surgical site infection compared with 24 hours of cefazolin. Our purpose was to evaluate infection rates of patients receiving perioperative cefazolin monotherapy, cefazolin-vancomycin dual therapy, or alternative antibiotic regimens. METHODS: A single-center retrospective review was conducted on patients who received lower extremity endoprostheses from 2008 to 2021 with minimum 1-year follow-up. Three prophylactic antibiotic regimen groups were compared: cefazolin monotherapy, cefazolin-vancomycin dual therapy, and alternative regimens. The primary outcome was deep infection, defined by a sinus tract, positive culture, or clinical diagnosis. Secondary outcomes were revision surgery, microorganisms isolated, and superficial wound issues. RESULTS: The overall deep infection rate was 10% (30/294) at the median final follow-up of 3.0 years (IQR 1.7 to 5.4). The deep infection rates in the cefazolin, cefazolin-vancomycin, and alternative regimen groups were 8% (6/72), 10% (18/179), and 14% (6/43), respectively (P = 0.625). Patients not receiving cefazolin had an 18% deep infection rate (6/34) and 21% revision surgery rate (7/34) compared with a 9% deep infection rate (24/260) (P = 0.13) and 12% revision surgery rate (31/260) (P = 0.17) in patients receiving cefazolin. In those not receiving cefazolin, 88% (30/34) were due to a documented penicillin allergy, only two being anaphylaxis. All six patients in the alternative regimen group who developed deep infections did not receive cefazolin secondary to nonanaphylactic penicillin allergy. CONCLUSION: The addition of perioperative vancomycin to cefazolin in lower extremity endoprosthetic reconstructions was not associated with a lower deep infection rate. Patients who did not receive cefazolin trended toward higher rates of deep infection and revision surgery, although not statistically significant. The most common reason for not receiving cefazolin was a nonanaphylactic penicillin allergy, highlighting the continued practice of foregoing cefazolin unnecessarily.

A Review of Machine Learning Approaches for Brain Positron Emission Tomography Data Analysis.

Positron emission tomography (PET) imaging has moved forward the development of medical diagnostics and research across various domains, including cardiology, neurology, infection detection, and oncology. The integration of machine learning (ML) algorithms into PET data analysis has further enhanced their capabilities of including disease diagnosis and classification, image segmentation, and quantitative analysis. ML algorithms empower researchers and clinicians to extract valuable insights from complex big PET datasets, which enabling automated pattern recognition, predictive health outcome modeling, and more efficient data analysis. This review explains the basic knowledge of PET imaging, statistical methods for PET image analysis, and challenges of PET data analysis. We also discussed the improvement of analysis capabilities by combining PET data with machine learning algorithms and the application of this combination in various aspects of PET image research. This review also highlights current trends and future directions in PET imaging, emphasizing the driving and critical role of machine learning and big PET image data analytics in improving diagnostic accuracy and personalized medical approaches. Integration between PET imaging will shape the future of medical diagnosis and research.

Polyethylene Glycol-Mediated Axonal Fusion Promotes Early Sensory Recovery After Digital Nerve Injury: A Randomized Clinical Trial.

BACKGROUND: Peripheral nerve repair is limited by Wallerian degeneration coupled with the slow and inconsistent rates of nerve regrowth. In more proximal injuries, delayed nerve regeneration can cause debilitating muscle atrophy. Topical application of polyethylene glycol (PEG) during neurorrhaphy facilitates the fusion of severed axonal membranes, immediately restoring action potentials across the coaptation site. In preclinical animal models, PEG-fusion resulted in remarkable early functional recovery. METHODS: This is the first randomized clinical trial comparing functional outcomes between PEG-fusion and standard neurorrhaphy. Participants with digital nerve transections were followed up at 2 weeks, 1 month, and 3 months postoperatively. The primary outcome was assessed using the Medical Research Council Classification (MRCC) rating for sensory recovery at each timepoint. Semmes-Weinstein monofilaments and static two-point discrimination determined MRCC ratings. Postoperative quality of life was measured using the Michigan Hand Questionnaire (MHQ). RESULTS: Forty-eight transected digital nerves (25 control, 23 PEG) across twenty-two patients were analyzed. PEG-fused nerves demonstrated significantly higher MRCC scores at 2 weeks (OR 16.95, 95% CI: 1.79 - 160.38, p = 0.008) and 1 month (OR 13.40, 95% CI: 1.64 - 109.77, p = 0.009). Participants in the PEG cohort also had significantly higher average MHQ scores at 2 weeks (Hodge's g 1.28, 95% CI: 0.23 - 2.30, p = 0.0163) and 1 month (Hodge's g 1.02, 95% CI: 0.04 - 1.99, p = 0.049). No participants had adverse events related to the study drug. CONCLUSION: PEG-fusion promotes early sensory recovery and improved patient well-being following peripheral nerve repair of digital nerves.

Exocrine pancreas in type 1 and type 2 diabetes: different patterns of fibrosis, metaplasia, angiopathy, and adiposity.

The endocrine and exocrine compartments of the pancreas are spatially related but functionally distinct. Multiple diseases affect both compartments, including type 1 diabetes (T1D), pancreatitis, cystic fibrosis, and pancreatic cancer. To better understand how the exocrine pancreas changes with age, obesity, and diabetes, we performed systematic analysis of wellpreserved tissue sections from the pancreatic head, body, and tail of organ donors with T1D (n = 20), type 2 diabetes (T2D, n = 25), and donors with no diabetes (ND, n = 74). Among ND donors, we found that acinar-to-ductal metaplasia (ADM), angiopathy, and pancreatic adiposity increased with age, while ADM and adiposity also increased with BMI. Compared to age- and sex-matched ND organs, T1D pancreata had greater acinar atrophy and angiopathy with fewer intralobular adipocytes. T2D pancreata had greater ADM, angiopathy, and total T lymphocytes, but no difference in adipocyte number, compared to ND organs. While total pancreatic fibrosis was increased in both T1D and T2D, the pattern was different with T1D pancreata having greater periductal and perivascular fibrosis, whereas T2D pancreata had greater lobular and parenchymal fibrosis. Thus, the exocrine pancreas undergoes distinct changes as individuals age or develop T1D or T2D.

Structural brain differences in essential tremor and Parkinson's disease deep brain stimulation patients.

BACKGROUND: Essential tremor (ET) and Parkinson's disease (PD) are the most common tremor disorders and are common indications for deep brain stimulation (DBS). In some patients, PD and ET symptoms overlap and diagnosis can be challenging based on clinical criteria alone. The objective of this study was to identify structural brain differences between PD and ET DBS patients to help differentiate these disorders and improve our understanding of the different brain regions involved in these pathologic processes. METHODS: We included ET and PD patients scheduled to undergo DBS surgery in this observational study. Patients underwent 3T brain MRI while under general anesthesia as part of their procedure. Cortical thicknesses and subcortical volumes were quantified from T1-weighted images using automated multi-atlas segmentation. We used logistic regression analysis to identify brain regions associated with diagnosis of ET or PD. RESULTS: 149 ET and 265 PD patients were included. Smaller volumes in the pallidum and thalamus and reduced thickness in the anterior orbital gyrus, lateral orbital gyrus, and medial precentral gyrus were associated with greater odds of ET diagnosis. Conversely, reduced volumes in the caudate, amygdala, putamen, and basal forebrain, and reduced thickness in the orbital part of the inferior frontal gyrus, supramarginal gyrus, and posterior cingulate were associated with greater odds of PD diagnosis. CONCLUSIONS: These findings identify structural brain differences between PD and ET patients. These results expand our understanding of the different brain regions involved in these disorders and suggest that structural MRI may help to differentiate patients with these two disorders.

Corticostriatal beta oscillation changes associated with cognitive function in Parkinson's disease.

Cognitive impairment is the most frequent non-motor symptom in Parkinson's disease and is associated with deficits in a number of cognitive functions including working memory. However, the pathophysiology of Parkinson's disease cognitive impairment is poorly understood. Beta oscillations have previously been shown to play an important role in cognitive functions including working memory encoding. Decreased dopamine in motor cortico-striato-thalamo-cortical (CSTC) circuits increases the spectral power of beta oscillations and results in Parkinson's disease motor symptoms. Analogous changes in parallel cognitive CSTC circuits involving the caudate and dorsolateral prefrontal cortex (DLPFC) may contribute to Parkinson's disease cognitive impairment. The objective of our study is to evaluate whether changes in beta oscillations in the caudate and DLPFC contribute to cognitive impairment in Parkinson's disease patients. To investigate this, we used local field potential recordings during deep brain stimulation surgery in 15 patients with Parkinson's disease. Local field potentials were recorded from DLPFC and caudate at rest and during a working memory task. We examined changes in beta oscillatory power during the working memory task as well as the relationship of beta oscillatory activity to preoperative cognitive status, as determined from neuropsychological testing results. We additionally conducted exploratory analyses on the relationship between cognitive impairment and task-based changes in spectral power in additional frequency bands. Spectral power of beta oscillations decreased in both DLPFC and caudate during working memory encoding and increased in these structures during feedback. Subjects with cognitive impairment had smaller decreases in caudate and DLPFC beta oscillatory power during encoding. In our exploratory analysis, we found that similar differences occurred in alpha frequencies in caudate and theta and alpha in DLPFC. Our findings suggest that oscillatory power changes in cognitive CSTC circuits may contribute to cognitive symptoms in patients with Parkinson's disease. These findings may inform the future development of novel neuromodulatory treatments for cognitive impairment in Parkinson's disease.

Is the Number of National Database Research Studies in Musculoskeletal Sarcoma Increasing, and Are These Studies Reliable?

BACKGROUND: Large national databases have become a common source of information on patterns of cancer care in the United States, particularly for low-incidence diseases such as sarcoma. Although aggregating information from many hospitals can achieve statistical power, this may come at a cost when complex variables must be abstracted from the medical record. There is a current lack of understanding of the frequency of use of the Surveillance, Epidemiology, and End Results (SEER) database and the National Cancer Database (NCDB) over the last two decades in musculoskeletal sarcoma research and whether their use tends to produce papers with conflicting findings. QUESTIONS/PURPOSES: (1) Is the number of published studies using the SEER and NCDB databases in musculoskeletal sarcoma research increasing over time? (2) What are the author, journal, and content characteristics of these studies? (3) Do studies using the SEER and the NCDB databases for similar diagnoses and study questions report concordant or discordant key findings? (4) Are the administrative data reported by our institution to the SEER and the NCDB databases concordant with the data in our longitudinally maintained, physician-run orthopaedic oncology dataset? METHODS: To answer our first three questions, PubMed was searched from 2001 through 2020 for all studies using the SEER or the NCDB databases to evaluate sarcoma. Studies were excluded from the review if they did not use these databases or studied anatomic locations other than the extremities, nonretroperitoneal pelvis, trunk, chest wall, or spine. To answer our first question, the number of SEER and NCDB studies were counted by year. The publication rate over the 20-year span was assessed with simple linear regression modeling. The difference in the mean number of studies between 5-year intervals (2001-2005, 2006-2010, 2011-2015, 2016-2020) was also assessed with Student t-tests. To answer our second question, we recorded and summarized descriptive data regarding author, journal, and content for these studies. To answer our third question, we grouped all studies by diagnosis, and then identified studies that shared the same diagnosis and a similar major study question with at least one other study. We then categorized study questions (and their associated studies) as having concordant findings, discordant findings, or mixed findings. Proportions of studies with concordant, discordant, or mixed findings were compared. To answer our fourth question, a coding audit was performed assessing the concordance of nationally reported administrative data from our institution with data from our longitudinally maintained, physician-run orthopaedic oncology dataset in a series of patients during the past 3 years. Our orthopaedic oncology dataset is maintained on a weekly basis by the senior author who manually records data directly from the medical record and sarcoma tumor board consensus notes; this dataset served as the gold standard for data comparison. We compared date of birth, surgery date, margin status, tumor size, clinical stage, and adjuvant treatment. RESULTS: The number of musculoskeletal sarcoma studies using the SEER and the NCDB databases has steadily increased over time in a linear regression model (ß = 2.51; p < 0.001). The mean number of studies per year more than tripled during 2016-2020 compared with 2011-2015 (39 versus 13 studies; mean difference 26 ± 11; p = 0.03). Of the 299 studies in total, 56% (168 of 299) have been published since 2018. Nineteen institutions published more than five studies, and the most studies from one institution was 13. Orthopaedic surgeons authored 35% (104 of 299) of studies, and medical oncology journals published 44% (130 of 299). Of the 94 studies (31% of total [94 of 299]) that shared a major study question with at least one other study, 35% (33 of 94) reported discordant key findings, 29% (27 of 94) reported mixed key findings, and 44% (41 of 94) reported concordant key findings. Both concordant and discordant groups included papers on prognostic factors, demographic factors, and treatment strategies. When we compared nationally reported administrative data from our institution with our orthopaedic oncology dataset, we found clinically important discrepancies in adjuvant treatment (19% [15 of 77]), tumor size (21% [16 of 77]), surgery date (23% [18 of 77]), surgical margins (38% [29 of 77]), and clinical stage (77% [59 of 77]). CONCLUSION: Appropriate use of databases in musculoskeletal cancer research is essential to promote clear interpretation of findings, as almost two-thirds of studies we evaluated that asked similar study questions produced discordant or mixed key findings. Readers should be mindful of the differences in what each database seeks to convey because asking the same questions of different databases may result in different answers depending on what information each database captures. Likewise, differences in how studies determine which patients to include or exclude, how they handle missing data, and what they choose to emphasize may result in different messages getting drawn from large-database studies. Still, given the rarity and heterogeneity of sarcomas, these databases remain particularly useful in musculoskeletal cancer research for nationwide incidence estimations, risk factor/prognostic factor assessment, patient demographic and hospital-level variable assessment, patterns of care over time, and hypothesis generation for future prospective studies. LEVEL OF EVIDENCE: Level III, therapeutic study.

Influences of resting-state intrinsic functional brain connectivity on the antidepressant treatment response in late-life depression.

BACKGROUND: Late-life depression (LLD) is characterized by differences in resting state functional connectivity within and between intrinsic functional networks. This study examined whether clinical improvement to antidepressant medications is associated with pre-randomization functional connectivity in intrinsic brain networks. METHODS: Participants were 95 elders aged 60 years or older with major depressive disorder. After clinical assessments and baseline MRI, participants were randomized to escitalopram or placebo with a two-to-one allocation for 8 weeks. Non-remitting participants subsequently entered an 8-week trial of open-label bupropion. The main clinical outcome was depression severity measured by MADRS. Resting state functional connectivity was measured between a priori key seeds in the default mode (DMN), cognitive control, and limbic networks. RESULTS: In primary analyses of blinded data, lower post-treatment MADRS score was associated with higher resting connectivity between: (a) posterior cingulate cortex (PCC) and left medial prefrontal cortex; (b) PCC and subgenual anterior cingulate cortex (ACC); (c) right medial PFC and subgenual ACC; (d) right orbitofrontal cortex and left hippocampus. Lower post-treatment MADRS was further associated with lower connectivity between: (e) the right orbitofrontal cortex and left amygdala; and (f) left dorsolateral PFC and left dorsal ACC. Secondary analyses associated mood improvement on escitalopram with anterior DMN hub connectivity. Exploratory analyses of the bupropion open-label trial associated improvement with subgenual ACC, frontal, and amygdala connectivity. CONCLUSIONS: Response to antidepressants in LLD is related to connectivity in the DMN, cognitive control and limbic networks. Future work should focus on clinical markers of network connectivity informing prognosis. REGISTRATION: ClinicalTrials.gov NCT02332291.

Towards differentiation of brain tumor from radiation necrosis using multi-parametric MRI: Preliminary results at 4.7 T using rodent models.

BACKGROUND: It remains a clinical challenge to differentiate brain tumors from radiation-induced necrosis in the brain. Despite significant improvements, no single MRI method has been validated adequately in the clinical setting. METHODS: Multi-parametric MRI (mpMRI) was performed to differentiate 9L gliosarcoma from radiation necrosis in animal models. Five types of MRI methods probed complementary information on different scales i.e., T2 (relaxation), CEST based APT (probing mobile proteins/peptides) and rNOE (mobile macromolecules), qMT (macromolecules), diffusion based ADC (cell density) and SSIFT iAUC (cell size), and perfusion based DSC (blood volume and flow). RESULTS: For single MRI parameters, iAUC and ADC provide the best discrimination of radiation necrosis and brain tumor. For mpMRI, a combination of iAUC, ADC, and APT shows the best classification performance based on a two-step analysis with the Lasso and Ridge regressions. CONCLUSION: A general mpMRI approach is introduced to choosing candidate multiple MRI methods, identifying the most effective parameters from all the mpMRI parameters, and finding the appropriate combination of chosen parameters to maximize the classification performance to differentiate tumors from radiation necrosis.

Structural MRI-Based Measures of Accelerated Brain Aging do not Moderate the Acute Antidepressant Response in Late-Life Depression.

OBJECTIVE: Late-life depression (LLD) is characterized by accelerated biological aging. Accelerated brain aging, estimated from structural magnetic resonance imaging (sMRI) data by a machine learning algorithm, is associated with LLD diagnosis, poorer cognitive performance, and disability. We hypothesized that accelerated brain aging moderates the antidepressant response. DESIGN AND INTERVENTIONS: Following MRI, participants entered an 8-week randomized, controlled trial of escitalopram. Nonremitting participants then entered an open-label 8-week trial of bupropion. PARTICIPANTS: Ninety-five individuals with LLD. MEASUREMENTS: A machine learning algorithm estimated each participant's brain age from sMRI data. This was used to calculate the brain-age gap (BAG), or how estimated age differed from chronological age. Secondary sMRI measures of aging pathology included white matter hyperintensity (WMH) volumes and hippocampal volumes. Mixed models examined the relationship between sMRI measures and change in depression severity. Initial analyses tested for a moderating effect of MRI measures on change in depression severity with escitalopram. Subsequent analyses tested for the effect of MRI measures on change in depression severity over time across trials. RESULTS: In the blinded initial phase, BAG was not significantly associated with a differential response to escitalopram over time. BAG was also not associated with a change in depression severity over time across both arms in the blinded phase or in the subsequent open-label bupropion phase. We similarly did not observe effects of WMH volume or hippocampal volume on change in depression severity over time. CONCLUSION: sMRI markers of accelerated brain aging were not associated with treatment response in this sequential antidepressant trial.

Elevated cerebral blood flow in patients with pure autonomic failure.

PURPOSE: Pure autonomic failure (PAF) results from an impaired peripheral autonomic nervous system, and clinical symptoms present with orthostatic hypotension. While the impact on cardiovascular indices of orthostatic intolerance are well-characterized, more limited information is available regarding cerebral hemodynamic dysfunction in PAF. The objective of this study was to test the hypothesis that cerebral blood flow (CBF) is reduced in PAF, and to quantify the relationship between CBF and clinical indicators of disease severity, including peripheral supine arterial blood pressure. METHODS: Participants with PAF (n = 17) and age- and sex-matched normotensive healthy controls (n = 17) were examined using established clinical rating scales, cardiovascular autonomic function tests, and 3T MRI measurements of CBF. CBF-weighted images were also used to determine the prevalence of venous hyperintensities from the major dural sinuses as evidence of abnormal capillary flow. Nonparametric tests and general linear models were used to evaluate differences and correlations between study variables. RESULTS: Gray matter CBF was higher in PAF (51.1 ± 13.4 mL/100 g/min) compared to controls (42.9 ± 6.5 mL/100 g/min, p = 0.007). Venous hyperintensities were more prevalent in PAF relative to controls, and the presence and degree of venous hyperintensities was associated with higher mean CBF (p = 0.027). In PAF participants, CBF and supine systolic blood pressure were inversely related (Spearman's rho = -0.545, p = 0.024). CONCLUSIONS: Findings suggest that PAF patients may exhibit elevated CBF and provide evidence that this condition exerts a hemodynamic impact in the central nervous system.

Texture Analysis of F-18 Fluciclovine PET/CT to Predict Biochemically Recurrent Prostate Cancer: Initial Results.

Predicting biochemical recurrence of prostate cancer is imperative for initiating early treatment, which can improve the outcome of cancer treatment. However, because of inter- and intrareader variability in interpretation of F-18 fluciclovine positron emission tomography/computed tomography (PET/CT), it is difficult to reliably discern between necrotic tissue owing to radiation therapy and tumor tissue. Our goal is to develop a computational methodology using Haralick texture analysis that can be used as an adjunct tool to improve and standardize the interpretation of F-18 fluciclovine PET/CT to identify biochemical recurrence of prostate cancer. Four main textural features were chosen by variable selection procedure using least absolute shrinkage and selection operator logistic regression and bootstrapping, and then included as predictors in subsequent logistic ridge regression model for prediction (n = 28). Age at prostatectomy, prostate-specific antigen (PSA) level before the PET/CT imaging, and number of days between the prostate-specific antigen measurement and PET/CT imaging were also included in the prediction model. The overfitting-corrected area under the curve and Brier score of the proposed model were 0.94 (95% CI: 0.81, 1.00) and 0.12 (95% CI: 0.03, 0.23), respectively. Compared with a model with textural features (TI model) and that with only clinical information (CI model), the proposed model achieved 2% and 32% increase in AUC and 8% and 48% reduction in Brier score, respectively. Combining Haralick textural features based on the PET/CT imaging data with clinical information shows a high potential of enhanced prediction of the biochemical recurrence of prostate cancer.

Quantitative Comparison of Prone and Supine PERCIST Measurements in Breast Cancer.

Positron emission tomography (PET) is typically performed in the supine position. However, breast magnetic resonance imaging (MRI) is performed in prone, as this improves visibility of deep breast tissues. With the emergence of hybrid scanners that integrate molecular information from PET and functional information from MRI, it is of great interest to determine if the prognostic utility of prone PET is equivalent to supine. We compared PERCIST (PET Response Criteria in Solid Tumors) measurements between prone and supine FDG-PET in patients with breast cancer and the effect of orientation on predicting pathologic complete response (pCR). In total, 47 patients were enrolled and received up to 6 cycles of neoadjuvant therapy. Prone and supine FDG-PET were performed at baseline (t0 ; n = 46), after cycle 1 (t1 ; n = 1) or 2 (t2 ; n = 10), or after all neoadjuvant therapy (t3 ; n = 19). FDG uptake was quantified by maximum and peak standardized uptake value (SUV) with and without normalization to lean body mass; that is, SUVmax , SUVpeak , SULmax , and SULpeak . PERCIST measurements were performed for each paired baseline and post-treatment scan. Receiver operating characteristic analysis for the prediction of pCR was performed using logistic regression that included age and tumor size as covariates. SUV and SUL metrics were significantly different between orientation (P < .001), but were highly correlated (P > .98). Importantly, no differences were observed with the PERCIST measurements (P > .6). Overlapping 95% confidence intervals for the receiver operating characteristic analysis suggested no difference at predicting pCR. Therefore, prone and supine PERCIST in this data set were not statistically different.

Machine learning methods are comparable to logistic regression techniques in predicting severe walking limitation following total knee arthroplasty.

PURPOSE: Machine-learning methods are flexible prediction algorithms with potential advantages over conventional regression. This study aimed to use machine learning methods to predict post-total knee arthroplasty (TKA) walking limitation, and to compare their performance with that of logistic regression. METHODS: From the department's clinical registry, a cohort of 4026 patients who underwent elective, primary TKA between July 2013 and July 2017 was identified. Candidate predictors included demographics and preoperative clinical, psychosocial, and outcome measures. The primary outcome was severe walking limitation at 6 months post-TKA, defined as a maximum walk time ≤ 15 min. Eight common regression (logistic, penalized logistic, and ordinal logistic with natural splines) and ensemble machine learning (random forest, extreme gradient boosting, and SuperLearner) methods were implemented to predict the probability of severe walking limitation. Models were compared on discrimination and calibration metrics. RESULTS: At 6 months post-TKA, 13% of patients had severe walking limitation. Machine learning and logistic regression models performed moderately [mean area under the ROC curves (AUC) 0.73-0.75]. Overall, the ordinal logistic regression model performed best while the SuperLearner performed best among machine learning methods, with negligible differences between them (Brier score difference, < 0.001; 95% CI [- 0.0025, 0.002]). CONCLUSIONS: When predicting post-TKA physical function, several machine learning methods did not outperform logistic regression-in particular, ordinal logistic regression that does not assume linearity in its predictors. LEVEL OF EVIDENCE: Prognostic level II.

Magnetic resonance imaging of mean cell size in human breast tumors.

PURPOSE: Cell size is a fundamental characteristic of all tissues, and changes in cell size in cancer reflect tumor status and response to treatments, such as apoptosis and cell-cycle arrest. Unfortunately, cell size can currently be obtained only by pathological evaluation of tumor tissue samples obtained invasively. Previous imaging approaches are limited to preclinical MRI scanners or require relatively long acquisition times that are impractical for clinical imaging. There is a need to develop cell-size imaging for clinical applications. METHODS: We propose a clinically feasible IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) approach that can characterize mean cell sizes in solid tumors. We report the use of a combination of pulse sequences, using different gradient waveforms implemented on clinical MRI scanners and analytical equations based on these waveforms to analyze diffusion-weighted MRI signals and derive specific microstructural parameters such as cell size. We also describe comprehensive validations of this approach using computer simulations, cell experiments in vitro, and animal experiments in vivo and demonstrate applications in preoperative breast cancer patients. RESULTS: With fast acquisitions (~7 minutes), IMPULSED can provide high-resolution (1.3 mm in-plane) mapping of mean cell size of human tumors in vivo on clinical 3T MRI scanners. All validations suggest that IMPULSED provides accurate and reliable measurements of mean cell size. CONCLUSION: The proposed IMPULSED method can assess cell-size variations in tumors of breast cancer patients, which may have the potential to assess early response to neoadjuvant therapy.

Probabilistic Assessment of Nerve Regeneration with Diffusion MRI in Rat Models of Peripheral Nerve Trauma.

Nerve regeneration after injury must occur in a timely fashion to restore function. Unfortunately, current methods (e.g., electrophysiology) provide limited information following trauma, resulting in delayed management and suboptimal outcomes. Herein, we evaluated the ability of diffusion MRI to monitor nerve regeneration after injury/repair. Sprague-Dawley rats were divided into three treatment groups (sham = 21, crush = 23, cut/repair = 19) and ex vivo diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) was performed 1-12 weeks post-surgery. Behavioral data showed a distinction between crush and cut/repair nerves at 4 weeks. This was consistent with DTI, which found that thresholds based on the ratio of radial and axial diffusivities (RD/AD = 0.40 ± 0.02) and fractional anisotropy (FA = 0.53 ± 0.01) differentiated crush from cut/repair injuries. By the 12th week, cut/repair nerves whose behavioral data indicated a partial recovery were below the RD/AD threshold (and above the FA threshold), while nerves that did not recover were on the opposite side of each threshold. Additional morphometric analysis indicated that DTI-derived normalized scalar indices report on axon density (RD/AD: r = -0.54, p < 1e-3; FA: r = 0.56, p < 1e-3). Interestingly, higher-order DKI analyses did not improve our ability classify recovery. These findings suggest that DTI may provide promising biomarkers for distinguishing successful/unsuccessful nerve repairs and potentially identify cases that require reoperation.

Transdermal Nicotine for the Treatment of Mood and Cognitive Symptoms in Nonsmokers With Late-Life Depression.

OBJECTIVE: Late-life depression (LLD) is characterized by poor antidepressant response and cognitive dysfunction. This study examined whether transdermal nicotine benefits mood symptoms and cognitive performance in LLD. METHODS: In a 12-week open-label outpatient study conducted between November 2016 and August 2017, transdermal nicotine was given to 15 nonsmoking older adults (≥ 60 years of age). Eligible participants met DSM-IV-TR criteria for major depressive disorder with ≥ 15 on the Montgomery-Asberg Depression Rating scale (MADRS) and endorsed subjective cognitive impairment. Transdermal nicotine patches were applied daily and titrated in a rigid dose escalation strategy to a maximum dose of 21.0 mg/d, allowing dose reductions for tolerability. The primary mood outcome was MADRS change measured every 3 weeks, with response defined as ≥ 50% improvement from baseline and remission as MADRS score ≤ 8. The primary cognitive outcome was the Conners Continuous Performance Test (CPT), a test of attention. RESULTS: Robust rates of response (86.7%; 13/15 subjects) and remission (53.3%; 8/15 subjects) were observed. There was a significant decrease in MADRS scores over the study (ß = -1.51, P < .001), with improvement seen as early as 3 weeks (Bonferroni-adjusted P value = .004). We also observed improvement in apathy and rumination. We did not observe improvement on the CPT but did observe improvement in subjective cognitive performance and signals of potential drug effects on secondary cognitive measures of working memory, episodic memory, and self-referential emotional processing. Overall, transdermal nicotine was well tolerated, although 6 participants could not reach the maximum targeted dose. CONCLUSIONS: Nicotine may be a promising therapy for depressed mood and cognitive performance in LLD. A definitive placebo-controlled trial and establishment of longer-term safety are necessary before clinical usage. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02816138​.

Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting.

BACKGROUND: Quantitative diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) have the potential to impact patient care by providing noninvasive biological information in breast cancer. PURPOSE/HYPOTHESIS: To quantify the repeatability, reproducibility, and accuracy of apparent diffusion coefficient (ADC) and T1 -mapping of the breast in community radiology practices. STUDY TYPE: Prospective. SUBJECTS/PHANTOM: Ice-water DW-MRI and T1 gel phantoms were used to assess accuracy. Normal subjects (n = 3) and phantoms across three sites (one academic, two community) were used to assess reproducibility. Test-retest analysis at one site in normal subjects (n = 12) was used to assess repeatability. FIELD STRENGTH/SEQUENCE: 3T Siemens Skyra MRI quantitative DW-MRI and T1 -mapping. ASSESSMENT: Quantitative DW-MRI and T1 -mapping parametric maps of phantoms and fibroglandular and adipose tissue of the breast. STATISTICAL TESTS: Average values of breast tissue were quantified and Bland-Altman analysis was performed to assess the repeatability of the MRI techniques, while the Friedman test assessed reproducibility. RESULTS: ADC measurements were reproducible across sites, with an average difference of 1.6% in an ice-water phantom and 7.0% in breast fibroglandular tissue. T1 measurements in gel phantoms had an average difference of 2.8% across three sites, whereas breast fibroglandular and adipose tissue had 8.4% and 7.5% average differences, respectively. In the repeatability study, we found no bias between first and second scanning sessions (P = 0.1). The difference between repeated measurements was independent of the mean for each MRI metric (P = 0.156, P = 0.862, P = 0.197 for ADC, T1 of fibroglandular tissue, and T1 of adipose tissue, respectively). DATA CONCLUSION: Community radiology practices can perform repeatable, reproducible, and accurate quantitative T1 -mapping and DW-MRI. This has the potential to dramatically expand the number of sites that can participate in multisite clinical trials and increase clinical translation of quantitative MRI techniques for cancer response assessment. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

α5ß1 integrin trafficking and Rac activation are regulated by APPL1 in a Rab5-dependent manner to inhibit cell migration.

Cell migration is a tightly coordinated process that requires the spatiotemporal regulation of many molecular components. Because adaptor proteins can serve as integrators of cellular events, they are being increasingly studied as regulators of cell migration. The adaptor protein containing a pleckstrin-homology (PH) domain, phosphotyrosine binding (PTB) domain, and leucine zipper motif 1 (APPL1) is a 709 amino acid endosomal protein that plays a role in cell proliferation and survival as well as endosomal trafficking and signaling. However, its function in regulating cell migration is poorly understood. Here, we show that APPL1 hinders cell migration by modulating both trafficking and signaling events controlled by Rab5 in cancer cells. APPL1 decreases internalization and increases recycling of α5ß1 integrin, leading to higher levels of α5ß1 integrin at the cell surface that hinder adhesion dynamics. Furthermore, APPL1 decreases the activity of the GTPase Rac and its effector PAK, which in turn regulate cell migration. Thus, we demonstrate a novel role for the interaction between APPL1 and Rab5 in governing crosstalk between signaling and trafficking pathways on endosomes to affect cancer cell migration.This article has an associated First Person interview with the first author of the paper.

Combining multiparametric MRI with receptor information to optimize prediction of pathologic response to neoadjuvant therapy in breast cancer: preliminary results.

Pathologic complete response following neoadjuvant therapy (NAT) is used as a short-term surrogate marker of eventual outcome in patients with breast cancer. Analyzing voxel-level heterogeneity in MRI-derived parametric maps, obtained before and after the first cycle of NAT ([Formula: see text]), in conjunction with receptor status, may improve the predictive accuracy of tumor response to NAT. Toward that end, we incorporated two MRI-derived parameters, the apparent diffusion coefficient and efflux rate constant, with receptor status in a logistic ridge-regression model. The area under the curve (AUC) and Brier score of the model computed via 10-fold cross validation were 0.94 (95% CI: 0.85, 0.99) and 0.11 (95% CI: 0.06, 0.16), respectively. These two statistics strongly support the hypothesis that our proposed model outperforms the other models that we investigated (namely, models without either receptor information or voxel-level information). The contribution of the receptor information was manifested by an 8% to 15% increase in AUC and a 14% to 21% decrease in Brier score. These data indicate that combining multiparametric MRI with hormone receptor status has a high likelihood of improved prediction of pathologic response to NAT in breast cancer.