COVID-19 Pandemic Impact on Decreased Imaging Utilization: A Single Institutional Experience

RATIONALE AND OBJECTIVES: Predictive models and anecdotal articles suggest radiology practices were losing 50-70% of their normal imaging volume during the COVID-19 pandemic. Using actual institutional data, we investigated the change in imaging utilization and revenue during this public health crisis. MATERIALS AND METHODS: Imaging performed within the 8-week span between March 8-April 30, 2020 was categorized into the COVID-19 healthcare crisis timeframe. The first week of this date range and the 10 weeks prior were used to derive the normal practice expected volume. A rolling seven-day total value was used for volume tracking and comparison. Total imaging utilization was derived and organized by patient setting (outpatient, inpatient, emergency) and imaging modality (X-ray, CT, Mammography, MRI, Nuclear Medicine/PET, US). The three highest volume hospitals were analyzed. Revenue information was collected from the hospital billing system. RESULTS: System-wide imaging volume decreased by 55% between April 7-13, 2020. Outpatient exams decreased by 68% relative to normal practice. Emergency exams decreased by 48% and inpatient exams declined by 31%. Mammograms and nuclear medicine scans were the most affected modalities, decreasing by 93% and 61%, respectively. The main campus hospital experienced less relative imaging volume loss compared to the other smaller and outpatient-driven hospitals. At its lowest point, the technical component revenue from main campus imaging services demonstrated a 49% negative variance from normal practice. CONCLUSION; The trends and magnitude of the actual imaging utilization data presented will help inform evidence-based decisions for more accurate volume predictions, policy changes, and institutional preparedness for current and future pandemics

Quantifying the Decrease in Emergency Department Imaging Utilization During the COVID-19 Pandemic at a Multicenter Healthcare System in Ohio

PURPOSE: To illustrate the change in emergency department (ED) imaging utilization at a multicenter health system in the state of Ohio during the COVID-19 pandemic. METHODS: A retrospective observational study was conducted assessing ED imaging volumes between March 1, 2020, and May 11, 2020, during the COVID-19 crisis. A rolling 7-day total value was used for volume tracking and comparison. Total imaging utilization in the ED was compared with new COVID-19 cases in our region. Utilization was first categorized by modality and then by plain films and computed tomography (CT) scans grouped by body part. CT imaging of the chest was specifically investigated by assessing both CT chest only exams and CT chest, abdomen, and pelvis (C/A/P) exams. Ultimately, matching pair-wise statistical analysis of exam volumes was performed to assess significance of volume change. RESULTS: Our multicenter health system experienced a 46% drop in imaging utilization (p \u3c 0.0001) during the pandemic. Matching pair-wise analysis showed a statistically significant volume decrease by each modality and body part. The exceptions were non-contrast chest CT, which increased (p = 0.0053), and non-trauma C/A/P CT, which did not show a statistically significant volume change (p = 0.0633). CONCLUSION: ED imaging utilization trends revealed through actual health system data will help inform evidence-based decisions for more accurate volume predictions and therefore institutional preparedness for current and future pandemics

MR imaging of therapy-induced changes of bone marrow

MR imaging of bone marrow infiltration by hematologic malignancies provides non-invasive assays of bone marrow cellularity and vascularity to supplement the information provided by bone marrow biopsies. This article will review the MR imaging findings of bone marrow infiltration by hematologic malignancies with special focus on treatment effects. MR imaging findings of the bone marrow after radiation therapy and chemotherapy will be described. In addition, changes in bone marrow microcirculation and metabolism after anti-angiogenesis treatment will be reviewed. Finally, new specific imaging techniques for the depiction of regulatory events that control blood vessel growth and cell proliferation will be discussed. Future developments are directed to yield comprehensive information about bone marrow structure, function and microenvironment

Screening for novel bacteria from the bioenergy feedstock switchgrass (Panicum virgatum L.)

Switchgrass is considered as a good candidate for biofuel, especially ethanol production due to its huge biomass output and high cellulose content. In a search for novel microorganisms capable of using and degrading switchgrass to produce sugars and ethanol, enrichment experiments were established to screen for microorganisms from soil samples obtained at the University of Tennessee Agricultural Research Station, Jackson, Tennessee. Three enrichments were prepared and incubated at different pH and temperatures: (1) 30°C, pH 5, (2) 30°C, pH 8 and (3) 60°C, pH5. Bulk community DNA was directly extracted from the enrichments. Microbial community structures were determined by phylogenetic analysis of 16S rRNA gene sequences retrieved from the enrichment cultures containing switchgrass as the carbon source. The mesophilic enrichments were dominated by Sarcina, Anaerobacter, and Clostrium, which were not found in the thermophilic enrichment. The thermophilic enrichment selected for two types of bacteria belonging to the class Bacilli (Geobacillus and Saccharococcus). The thermophilic enrichments were dominated by the Geobacillus spp. (Firmicutes, class Bacilli), and Saccharococcus (Firmicutes, class Bacilli); both containing thermophilic microorganisms with some cellulolytic members. Enzymatic assays detected the presence of enzymes involved in cellulose (β-glucosidase and cellobiohydrolase) and hemicellulose degradations (β-xylosidase); and the activity tends to be higher in the enrichments incubated at 30°C. © 2013 Taylor and Francis.http://deepblue.lib.umich.edu/bitstream/2027.42/191246/2/Plecha et al., 2013.pdfPublished versio

Abstract P2-02-12: Computer derived image features on DCE-MRI appear to distinguish estrogen receptor-positive breast cancers with low and high oncotype DX recurrence scores

Abstract The Oncotype DX (ODX) is a 21 panel gene-expression based assay for identifying which Estrogen Receptor-positive (ER+) breast cancer (BCa) patients are candidates for adjuvant chemotherapy. The objective of this research was to identify whether computerized texture features on a staging DCE-MRI can distinguish ER+ BCa with low and high ODX recurrence scores (RS) (i.e. to distinguish which ER+ BCa patients are more likely to benefit from adjuvant hormonal therapy from those who require chemotherapy). This would provide a non-invasive, imaging based, pre-therapeutic assessment tool for predicting the appropriate treatment regimen. This work, to the best of our knowledge, is the first attempt to quantitatively correlate low versus high risk stratification via computer derived MRI measurements to corresponding risk stratification via the ODX assay. 52 ER+ BCa patient studies with high (&amp;gt;30, N = 28) and low (&amp;lt;18, N = 24) ODX RS were available for this study from two sites; 16 breast MRIs from the Boston Medical Center using a Phillips 1.5T magnet with a 7-channel breast coil, and 36 MRIs from the Case Medical Center using a Siemens 1.5T magnet with a 8-channel breast coil. All datasets included T1w images obtained prior to, during, and after administration of 0.1 mmol/kg of Gd-DTPA and corresponding ODX RS. For each study a radiologist picked a representative slice showing the tumor and then manually segmented the region of interest (ROI) containing the lesion. Computerized image analysis tools developed in-house via the MATLAB© programming platform were applied to the manually segmented lesion ROI for each of the 52 MRI studies to quantitatively characterize the lesion via a set of (a) 6 shape, (b) 3 pharmacokinetic (Ktrans, ve, kep) based on Tofts model (PK), (c) 12 enhancement kinetic (EK), (d) 12 intensity kinetic (IK), (e) 312 textural kinetic (TK), (f) 6 dynamic local binary pattern (DLBP), and (g) 5 dynamic histogram of oriented gradient (DHoG) features. The computer extracted features were evaluated via a linear discriminant analysis (LDA) classifier in terms of their ability to distinguish ER+ BCa as having a low or high ODX RS via a 2-fold randomized cross validation scheme. At each iteration, half of the studies were randomly selected from the 52 cases and used for training the LDA classifier and the remaining 26 studies were used for independent testing. This process was repeated 200 times. Classification performance was evaluated by area under the ROC curve (AUC). Higher AUC values suggest a stronger relationship between risk stratification via MRI attributes and ODX. Table 1Feature classAccuracy (μ±Δ)AUC (μ±Δ)DHoG87.07%±5.66%0.89±0.04DLBP85.86%±7.82%0.83±0.07EK82.36%±8.46%0.80±0.06PK81.14%±7.55%0.78±0.07TK75.93%±6.65%0.76±0.08IK76.43%±7.23%0.75±0.12Shape71.04%±6.81%0.70±0.06 Table 1 illustrates the mean and standard deviation in accuracy and AUC values over 200 runs of randomized cross validation. DHoG, DBLP and EK features yielded the highest classification accuracy and AUC. Although lesion shape has been shown to be important for discriminating benign and malignant lesions on MRI, shape appears to be less useful in distinguishing between ER+ BCa lesions with low and high ODX RS. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P2-02-12.</jats:p