Challenges of COVID-19 Case Forecasting in the US, 2020-2021

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub (https://covid19forecasthub.org). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1-4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

flepiMoP: The evolution of a flexible infectious disease modeling pipeline during the COVID-19 pandemic

The COVID-19 pandemic led to an unprecedented demand for projections of disease burden and healthcare utilization under scenarios ranging from unmitigated spread to strict social distancing policies. In response, members of the Johns Hopkins Infectious Disease Dynamics Group developed flepiMoP (formerly called the COVID Scenario Modeling Pipeline), a comprehensive open-source software pipeline designed for creating and simulating compartmental models of infectious disease transmission and inferring parameters through these models. The framework has been used extensively to produce short-term forecasts and longer-term scenario projections of COVID-19 at the state and county level in the US, for COVID-19 in other countries at various geographic scales, and more recently for seasonal influenza. In this paper, we highlight how the flepiMoP has evolved throughout the COVID-19 pandemic to address changing epidemiological dynamics, new interventions, and shifts in policy-relevant model outputs. As the framework has reached a mature state, we provide a detailed overview of flepiMoP's key features and remaining limitations, thereby distributing flepiMoP and its documentation as a flexible and powerful tool for researchers and public health professionals to rapidly build and deploy large-scale complex infectious disease models for any pathogen and demographic setup.

Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.

Informing pandemic response in the face of uncertainty. An evaluation of the U.S. COVID-19 Scenario Modeling Hub

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make 6-month ahead projections of the number of SARS-CoV-2 cases, hospitalizations and deaths. The SMH released nearly 1.8 million national and state-level projections between February 2021 and November 2022. SMH performance varied widely as a function of both scenario validity and model calibration. Scenario assumptions were periodically invalidated by the arrival of unanticipated SARS-CoV-2 variants, but SMH still provided projections on average 22 weeks before changes in assumptions (such as virus transmissibility) invalidated scenarios and their corresponding projections. During these periods, before emergence of a novel variant, a linear opinion pool ensemble of contributed models was consistently more reliable than any single model, and projection interval coverage was near target levels for the most plausible scenarios (e.g., 79% coverage for 95% projection interval). SMH projections were used operationally to guide planning and policy at different stages of the pandemic, illustrating the value of the hub approach for long-term scenario projections.

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: A multi-model study

Background

The COVID-19 Scenario Modeling Hub convened nine modeling teams to project the impact of expanding SARS-CoV-2 vaccination to children aged 5-11 years on COVID-19 burden and resilience against variant strains.

Methods

Teams contributed state- and national-level weekly projections of cases, hospitalizations, and deaths in the United States from September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of 1) vaccination (or not) of children aged 5-11 years (starting November 1, 2021), and 2) emergence (or not) of a variant more transmissible than the Delta variant (emerging November 15, 2021). Individual team projections were linearly pooled. The effect of childhood vaccination on overall and age-specific outcomes was estimated using meta-analyses.

Findings

Assuming that a new variant would not emerge, all-age COVID-19 outcomes were projected to decrease nationally through mid-March 2022. In this setting, vaccination of children 5-11 years old was associated with reductions in projections for all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios without childhood vaccination. Vaccine benefits increased for scenarios including a hypothesized more transmissible variant, assuming similar vaccine effectiveness. Projected relative reductions in cumulative outcomes were larger for children than for the entire population. State-level variation was observed.

Interpretation

Given the scenario assumptions (defined before the emergence of Omicron), expanding vaccination to children 5-11 years old would provide measurable direct benefits, as well as indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

Funding

Various (see acknowledgments).

Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

In Spring 2021, the highly transmissible SARS-CoV-2 Delta variant began to cause increases in cases, hospitalizations, and deaths in parts of the United States. At the time, with slowed vaccination uptake, this novel variant was expected to increase the risk of pandemic resurgence in the US in summer and fall 2021. As part of the COVID-19 Scenario Modeling Hub, an ensemble of nine mechanistic models produced 6-month scenario projections for July-December 2021 for the United States. These projections estimated substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant, projected to occur across most of the US, coinciding with school and business reopening. The scenarios revealed that reaching higher vaccine coverage in July-December 2021 reduced the size and duration of the projected resurgence substantially, with the expected impacts was largely concentrated in a subset of states with lower vaccination coverage. Despite accurate projection of COVID-19 surges occurring and timing, the magnitude was substantially underestimated 2021 by the models compared with the of the reported cases, hospitalizations, and deaths occurring during July-December, highlighting the continued challenges to predict the evolving COVID-19 pandemic. Vaccination uptake remains critical to limiting transmission and disease, particularly in states with lower vaccination coverage. Higher vaccination goals at the onset of the surge of the new variant were estimated to avert over 1.5 million cases and 21,000 deaths, although may have had even greater impacts, considering the underestimated resurgence magnitude from the model.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

Impact of SARS-CoV-2 vaccination of children ages 5-11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021-March 2022: a multi-model study

Background

SARS-CoV-2 vaccination of persons aged 12 years and older has reduced disease burden in the United States. The COVID-19 Scenario Modeling Hub convened multiple modeling teams in September 2021 to project the impact of expanding vaccine administration to children 5-11 years old on anticipated COVID-19 burden and resilience against variant strains.

Methods

Nine modeling teams contributed state- and national-level projections for weekly counts of cases, hospitalizations, and deaths in the United States for the period September 12, 2021 to March 12, 2022. Four scenarios covered all combinations of: 1) presence vs. absence of vaccination of children ages 5-11 years starting on November 1, 2021; and 2) continued dominance of the Delta variant vs. emergence of a hypothetical more transmissible variant on November 15, 2021. Individual team projections were combined using linear pooling. The effect of childhood vaccination on overall and age-specific outcomes was estimated by meta-analysis approaches.

Findings

Absent a new variant, COVID-19 cases, hospitalizations, and deaths among all ages were projected to decrease nationally through mid-March 2022. Under a set of specific assumptions, models projected that vaccination of children 5-11 years old was associated with reductions in all-age cumulative cases (7.2%, mean incidence ratio [IR] 0.928, 95% confidence interval [CI] 0.880-0.977), hospitalizations (8.7%, mean IR 0.913, 95% CI 0.834-0.992), and deaths (9.2%, mean IR 0.908, 95% CI 0.797-1.020) compared with scenarios where children were not vaccinated. This projected effect of vaccinating children 5-11 years old increased in the presence of a more transmissible variant, assuming no change in vaccine effectiveness by variant. Larger relative reductions in cumulative cases, hospitalizations, and deaths were observed for children than for the entire U.S. population. Substantial state-level variation was projected in epidemic trajectories, vaccine benefits, and variant impacts.

Conclusions

Results from this multi-model aggregation study suggest that, under a specific set of scenario assumptions, expanding vaccination to children 5-11 years old would provide measurable direct benefits to this age group and indirect benefits to the all-age U.S. population, including resilience to more transmissible variants.

Projected resurgence of COVID-19 in the United States in July-December 2021 resulting from the increased transmissibility of the Delta variant and faltering vaccination

WHAT IS ALREADY KNOWN ABOUT THIS TOPIC?

The highly transmissible SARS-CoV-2 Delta variant has begun to cause increases in cases, hospitalizations, and deaths in parts of the United States. With slowed vaccination uptake, this novel variant is expected to increase the risk of pandemic resurgence in the US in July-December 2021.

WHAT IS ADDED BY THIS REPORT?

Data from nine mechanistic models project substantial resurgences of COVID-19 across the US resulting from the more transmissible Delta variant. These resurgences, which have now been observed in most states, were projected to occur across most of the US, coinciding with school and business reopening. Reaching higher vaccine coverage in July-December 2021 reduces the size and duration of the projected resurgence substantially. The expected impact of the outbreak is largely concentrated in a subset of states with lower vaccination coverage.

WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE?

Renewed efforts to increase vaccination uptake are critical to limiting transmission and disease, particularly in states with lower current vaccination coverage. Reaching higher vaccination goals in the coming months can potentially avert 1.5 million cases and 21,000 deaths and improve the ability to safely resume social contacts, and educational and business activities. Continued or renewed non-pharmaceutical interventions, including masking, can also help limit transmission, particularly as schools and businesses reopen.

Modeling of Future COVID-19 Cases, Hospitalizations, and Deaths, by Vaccination Rates and Nonpharmaceutical Intervention Scenarios - United States, April-September 2021

After a period of rapidly declining U.S. COVID-19 incidence during January-March 2021, increases occurred in several jurisdictions (1,2) despite the rapid rollout of a large-scale vaccination program. This increase coincided with the spread of more transmissible variants of SARS-CoV-2, the virus that causes COVID-19, including B.1.1.7 (1,3) and relaxation of COVID-19 prevention strategies such as those for businesses, large-scale gatherings, and educational activities. To provide long-term projections of potential trends in COVID-19 cases, hospitalizations, and deaths, COVID-19 Scenario Modeling Hub teams used a multiple-model approach comprising six models to assess the potential course of COVID-19 in the United States across four scenarios with different vaccination coverage rates and effectiveness estimates and strength and implementation of nonpharmaceutical interventions (NPIs) (public health policies, such as physical distancing and masking) over a 6-month period (April-September 2021) using data available through March 27, 2021 (4). Among the four scenarios, an accelerated decline in NPI adherence (which encapsulates NPI mandates and population behavior) was shown to undermine vaccination-related gains over the subsequent 2-3 months and, in combination with increased transmissibility of new variants, could lead to surges in cases, hospitalizations, and deaths. A sharp decline in cases was projected by July 2021, with a faster decline in the high-vaccination scenarios. High vaccination rates and compliance with public health prevention measures are essential to control the COVID-19 pandemic and to prevent surges in hospitalizations and deaths in the coming months.

A scenario modeling pipeline for COVID-19 emergency planning

Coronavirus disease 2019 (COVID-19) has caused strain on health systems worldwide due to its high mortality rate and the large portion of cases requiring critical care and mechanical ventilation. During these uncertain times, public health decision makers, from city health departments to federal agencies, sought the use of epidemiological models for decision support in allocating resources, developing non-pharmaceutical interventions, and characterizing the dynamics of COVID-19 in their jurisdictions. In response, we developed a flexible scenario modeling pipeline that could quickly tailor models for decision makers seeking to compare projections of epidemic trajectories and healthcare impacts from multiple intervention scenarios in different locations. Here, we present the components and configurable features of the COVID Scenario Pipeline, with a vignette detailing its current use. We also present model limitations and active areas of development to meet ever-changing decision maker needs.

Perfect counterfactuals for epidemic simulations

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervention, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a 'single-world' approach to matching simulations of controlled epidemics to their exact uncontrolled counterfactual. Our method borrows concepts from percolation approaches, prunes out possible epidemic histories and creates potential epidemic graphs (i.e. a mathematical representation of all consistent epidemics) that can be 'realized' to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models (e.g. SIR models), and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids nonsensical inferences. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

What is Machine Learning? A Primer for the Epidemiologist

Machine learning is a branch of computer science that has the potential to transform epidemiologic sciences. Amid a growing focus on "Big Data," it offers epidemiologists new tools to tackle problems for which classical methods are not well-suited. In order to critically evaluate the value of integrating machine learning algorithms and existing methods, however, it is essential to address language and technical barriers between the two fields that can make it difficult for epidemiologists to read and assess machine learning studies. Here, we provide an overview of the concepts and terminology used in machine learning literature, which encompasses a diverse set of tools with goals ranging from prediction to classification to clustering. We provide a brief introduction to 5 common machine learning algorithms and 4 ensemble-based approaches. We then summarize epidemiologic applications of machine learning techniques in the published literature. We recommend approaches to incorporate machine learning in epidemiologic research and discuss opportunities and challenges for integrating machine learning and existing epidemiologic research methods.

The projected impact of geographic targeting of oral cholera vaccination in sub-Saharan Africa: A modeling study

BACKGROUND

Cholera causes an estimated 100,000 deaths annually worldwide, with the majority of burden reported in sub-Saharan Africa. In May 2018, the World Health Assembly committed to reducing worldwide cholera deaths by 90% by 2030. Oral cholera vaccine (OCV) plays a key role in reducing the near-term risk of cholera, although global supplies are limited. Characterizing the potential impact and cost-effectiveness of mass OCV deployment strategies is critical for setting expectations and developing cholera control plans that maximize the chances of success.

METHODS AND FINDINGS

We compared the projected impacts of vaccination campaigns across sub-Saharan Africa from 2018 through 2030 when targeting geographically according to historical cholera burden and risk factors. We assessed the number of averted cases, deaths, and disability-adjusted life years and the cost-effectiveness of these campaigns with models that accounted for direct and indirect vaccine effects and population projections over time. Under current vaccine supply projections, an approach optimized to targeting by historical burden is projected to avert 828,971 (95% CI 803,370-859,980) cases (equivalent to 34.0% of projected cases; 95% CI 33.2%-34.8%). An approach that balances logistical feasibility with targeting historical burden is projected to avert 617,424 (95% CI 599,150-643,891) cases. In contrast, approaches optimized for targeting locations with limited access to water and sanitation are projected to avert 273,939 (95% CI 270,319-277,002) and 109,817 (95% CI 103,735-114,110) cases, respectively. We find that the most logistically feasible targeting strategy costs US$1,843 (95% CI 1,328-14,312) per DALY averted during this period and that effective geographic targeting of OCV campaigns can have a greater impact on cost-effectiveness than improvements to vaccine efficacy and moderate increases in coverage. Although our modeling approach does not project annual changes in baseline cholera risk or directly incorporate immunity from natural cholera infection, our estimates of the relative performance of different vaccination strategies should be robust to these factors.

CONCLUSIONS

Our study suggests that geographic targeting substantially improves the cost-effectiveness and impact of oral cholera vaccination campaigns. Districts with the poorest access to improved water and sanitation are not the same as districts with the greatest historical cholera incidence. While OCV campaigns can improve cholera control in the near term, without rapid progress in developing water and sanitation services or dramatic increases in OCV supply, our results suggest that vaccine use alone is unlikely to allow us to achieve the 2030 goal.

Comparison of US County-Level Public Health Performance Rankings With County Cluster and National Rankings: Assessment Based on Prevalence Rates of Smoking and Obesity and Motor Vehicle Crash Death Rates

IMPORTANCE

Health departments can be grouped together based on sociodemographic characteristics of the population served. Comparisons within these groups can then help with monitoring and improving the health of their populations.

OBJECTIVE

To compare county-level percentile rankings on outcomes of smoking, motor vehicle crash deaths, and obesity within sociodemographic peer clusters vs nationwide rankings.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional, population-based study of demographic and health data from the 2014 Behavioral Risk Factor Surveillance System and the 2016 Robert Wood Johnson Foundation County Health Rankings data set was conducted at 3139 of 3143 US counties and county-equivalents. Four locations were excluded due to incomplete data. Data analysis was conducted between January and August 2017.

EXPOSURES

Random forest algorithms were used to identify sociodemographic characteristics most associated with the outcomes of interest. These characteristics were race and ethnicity, educational attainment, age, marital status, employment status, sex, and health insurance status. k-means clustering was used to cluster counties based on these sociodemographic characteristics and the percentage of the county classified as rural.

MAIN OUTCOMES AND MEASURES

County-level smoking prevalence, motor vehicle crash death rate, and obesity prevalence. County percentile rankings on the outcomes of interest were compared in the national context and the within-cluster context.

RESULTS

A total of 318 856 967 individuals (mean [SD] individuals per county, 101 579.2 [326 315]; 161 911 910 women [50.8%]) were represented by the 3139 counties used in this analysis. Eight distinct sociodemographic clusters throughout the United States were found. Cluster-specific percentile rankings for both smoking prevalence and motor vehicle crash death rates improved more than 70 percentile points for several counties in the rural, American Indian cluster compared with the nationwide percentiles. Conversely, the young, urban, middle to high socioeconomic status cluster included counties with cluster-specific percentile rankings that declined by 60 percentile points or more compared with the nationwide rankings for all 3 outcomes of interest.

CONCLUSIONS AND RELEVANCE

Comparing county health outcomes on a nationwide or statewide basis fails to adequately account for sociodemographic context. Clustering counties by sociodemographic factors related to the outcome of interest allows a better understanding of other factors that may be shaping the prevalence of health outcomes. These groupings may also aid learning exchange.

Piezosurgical lateral suboccipital craniectomy and opening of the internal auditory canal in the rat

AIM

Rotating burs (RB), routinely used in skull base and cerebellopontine angle (CPA) surgery for craniotomy and opening of the internal auditory canal (IAC) carry some risks for neurovascular tissue due to their rotating power. This paper describes the use of piezosurgery (PS), which selectively cuts bone with preservation of soft tissue, in lateral suboccipital craniectomy and opening of the IAC in the rat.

METHODS

A lateral suboccipital craniectomy and opening of the bony IAC were performed with the Mectron® piezosurgical device under microsurgical conditions in the anesthezised rat. The piezosurgical device was evaluated with respect to practicability, safety, preciseness of craniectomy and IAC opening, and preservation of adjacent neurovascular tissue. The operation procedure is described in detail.

RESULTS

The present work shows that PS allows easy, safe and precise bone cutting with no injury to neurovascular tissue, such as dura, transverse or sigmoid sinus, brain, and cranial nerves. No complications were noted during the procedure. Due to the absence of rotating power near neurovascular structures the drilling process was easy and comfortable for the surgeon.

CONCLUSION

PS proved to be a safe, precise and easy to handle tool to perform suboccipital craniectomy and opening of IAC in the rat. Since PS makes the drilling process safer and more comfortable compared to a rotating bur it may be used instead of rotating burs in all scientific applications in animal models where a safe removal of bone near delicate nervous or soft tissue structures is essential.

[Therapy of posterior orbital tumors]

Tumors of the posterior orbit require different therapeutic modalities, depending on the histological entity. In the orbit all structures are in close relationship and the endocranium is in the direct proximity. This requires profound knowledge of topographic anatomy and high therapeutic precision. The surgical approach to the posterior orbit via a ventral intraorbital approach is strongly restricted due to the ocular bulb which consumes most space in the anterior orbit. Therefore if the bulb and vision are to be retained extraorbital surgical corridors are predominantly preferred. These are classified into extracranial and intracranial approaches. In detail, the former are medial transethmoidal orbitotomy, caudal transmaxillar orbitotomy and lateral orbitotomy. Frontolateral and frontotemporal orbitotomy as well as frontal, bifrontal and subfrontal orbitotomy are intracranial approaches. Apart from surgical methods there are several forms of radiotherapy which can be applied to orbital tumors under certain indications. Radiotherapy may be performed with external fractionated photon radiation or as stereotactic radiation, with heavy ions or protons or as brachytherapy. In this article various therapeutic interventions to the posterior orbit and the indications and potential side-effects are described.

[Surgical therapy in Graves' orbitopathy]

Surgical therapy of Graves' orbitopathy comprises orbital decompression as well as strabismus and lid surgery. The former is primarily carried out during active disease, the latter during inactive disease. Orbital decompression abates increased intraorbital pressure and is thus applicable against dysthyroid optic neuropathy and also reduces exophthalmos. The choice of a specific procedure depends mainly on the experience of the respective center. In this article, the pterional transcranial, transnasal transethmoidal, transconjunctival and swinging eyelid approaches are presented. Eye muscle recession relieves the abnormal tension of fibrotic muscles and thus corrects diplopia. Compared to normal strabismus surgery, the dose-response relationship is increased. Lid lengthening surgery is applied to counter upper or lower lid retraction. If several of these operations are necessary the order is chosen in such a way that downstream procedures cannot change specific results of upstream operations.

[Nuchal swelling]

In the unusual case of a 68-year-old woman with one-sided painless lateral neck swelling, the ENT examination showed a firm nuchal mass (4 × 4 cm) on the right side with no other pathological findings. Angio-MRI confirmed a solid, sharply demarcated tumor with arterial hyperperfusion. Core needle aspiration biopsy was performed, revealing well-circumscribed tufts showing the typical "cannonball" aspect. After preoperative embolisation we performed extirpation of the mass. Histological examination showed an acquired tufted angioma. Clinical as well as radiological follow-up examination detected neither local relapse nor metastases.

Minimally invasive removal of an extradural intraradicular lumbar schwannoma

OBJECTIVE

Surgical exposure of peripheral lumbar schwannomas often requires extensive muscle mobilization which results in significant postoperative pain. We describe an alternative minimally invasive surgical technique for the treatment of such lesions.

METHODS

We report the case of a patient with an extradural intraradicular schwannoma of the L4 root that was treated with a minimally invasive transmuscular approach by using tubular retractors.

RESULTS

Muscle trauma and intraoperative blood loss were negligible. The postoperative course was uneventfull. There was no additional morbidity associated with the approach. The patient was discharged 72 h after the procedure.

CONCLUSIONS

In selected cases extradural intraradicular lumbar schwannomas can be treated adequately with a minimally invasive transmuscular approach.

Endoscope-assisted retrosigmoid intradural suprameatal approach to the middle fossa: Anatomical and surgical considerations

INTRODUCTION

Lesions involving the posterior and middle fossa may be reached by several surgical approaches depending mostly on tumors' location and characteristics. The retrosigmoid intradural suprameatal approach has been used to remove tumors of the posterior fossa extending into Meckel's cave and the middle fossa. With large tumors, this approach may allow exposure of the oculomotor and optic nerves, the supraclinoid internal carotid and communicating posterior arteries.

METHODS

Three formaldehyde-fixed specimens have been prepared on both sides using the conventional retrosigmoidal-suprameatal approach. The entire endoscopic preparations have been documented via a digital recording system, using a 5mm endoscope with a 25 degrees perspective. The authors describe the anatomical corridor and technique of the endoscope-assisted retrosigmoid intradural suprameatal approach to lesions that are located predominantly within the posterior fossa and supratentorial extension into Meckel's cave, sellar and parasellar region.

CONCLUSIONS

The endoscope-assisted suprameatal approach provides exposure of the antero-medial middle fossa even in cases of skull base lesions that have not caused significant displacement of neurovascular structures.

Evaluation of surface and volume rendering in 3D-CT of facial fractures

OBJECTIVES

Three-dimensional computed tomography (3D-CT) of facial fractures has been reported as beneficial using surface (SR) and volume rendering (VR). There are controversial statements concerning the preferable algorithm. The purpose of this study was to evaluate and compare SR and VR for clinical 3D-CT in facial fractures on an experimental basis.

METHODS

Multislice CT was obtained in 22 patients with facial fractures using two data acquisition protocols. Five SR and VR post-processing protocols were applied. Five assessors independently evaluated the quality of visualization of the fracture gap and dislocated fragments as well as the overall image quality using a five-point rating scale. The potential benefit of the 3D-images for radiological diagnosis and presentation was evaluated. The influence of the data acquisition protocol was analysed.

RESULTS

SR in general achieved better evaluation scores than VR at corresponding thresholds. Variation of evaluation scores for all criteria was found for SR and VR depending on the segmentation threshold. Apart from the overall image quality no significant influence of the data acquisition technique was found for the evaluated criteria.

CONCLUSIONS

SR provided sufficient and time efficient means for 3D-visualization of facial fractures in this study. No diagnostic benefit of VR over SR was found.

Rosai-Dorfman disease involving the cranial base, paranasal sinuses and spinal cord

Rosai-Dorfman disease is a lymphoproliferative disease that rarely involves the central nervous system. A 32-year-old patient with an extensive process involving the petroclival region, cavernous sinuses, suprasellar region, anterior cranial fossa, paranasal sinuses, nasal cavity and spinal cord is reported. Sinus histiocytosis with massive lymphadenopathy lesions may be dural-based and located in the skull base. As these lesions may clinically and radiologically mimic meningiomas as well as other disorders, Rosai-Dorfman disease should be included in the differential diagnosis of extensive lesions involving the intracranial and spinal compartments along with meningiomatosis and inflammatory diseases. The individual management of Rosai-Dorfman disease may be challenging due to diffuse involvement of neurovascular structures at the skull base.

3D-Darstellung des Mittelohres mittels computergestützter Nachverarbeitung helikaler Mehrschicht-CT-Daten

Post-processing of CT-data allows non-invasive 3D-Visualisation of the middle ear for diagnosis and surgical planning. In this study different post-processing techniques and the clinical application of a 3D-postprocessing algorithm in a large number of patients are presented. 20 normal patients, 6 dissected temporal bones and 213 patients with suspected middle ear pathology were examined using a low-dosage Multi-Slice CT protocol. Virtual endoscopic views of the middle ear and 3D-images of the ossicles were generated using a standardised algorithm. Evaluation of the image quality was performed. The virtual views of the dissected temporal bones were compared to real views. In 32 patients high-quality 3D-models of the individual anatomical structures were generated and displayed using different visualisation techniques. The standardised and evaluated method enabled visualisation of the normal middle ear anatomy. Assessment of different pathologies, especially malformation, trauma, implants and postoperative alterations, was facilitated. The high-quality 3D-models allowed precise imaging of the anatomical structures. 3D-Visualisation of the middle ear using CT-data is beneficial for radiological diagnosis and surgical planning in cases of complex middle ear pathology as a complementary examination technique.

Mehrsegmentale Bildfusion an der Wirbelsäule / Multisegmental Image Fusion of the Spine

Fusion of medical images is a technique that permits the correlation of homologous anatomical structures in different imaging modalities on the basis of a spatial transformation of the data sets. CT and MRI of the spine provide complementary information of possible relevance for diagnostic and therapeutic decisions. Methods enabling a multisegmental CT-MRI fusion of the spine were developed. These solve the problem of altered spatial relationships of the individual anatomical structures due to differing patient positioning in successive data acquisitions. Routine clinical CT and MRI data of a thoracic section of the spine were obtained and transferred to a PC-workstation. Following segmentation of the CT-data, landmarks for each individual vertebra were defined in the CT and MRI data. For each individual vertebra the algorithm we developed then carried out a rigid registration of the CT information to the MR data. The fused data sets were presented as colour-coded images or on the basis of dynamic variation of transparency. To assess registration precision, fiducial registration errors (FRE) and target registration errors (TRE) were calculated. The algorithm permitted multi-segmental image fusion of the spine. The average time required for defining the landmarks was 22 seconds per landmark for CT, and 34 seconds per landmark for MR. The average FRE was 1.53 mm. The TRE for the vertebrae was less than 2 mm. The colour-coded images were particularly suitable for assessing the contours of the anatomical structures, whereas dynamic variation of the transparency of overlapping CT images enabled a better overall assessment of the spatial relationship of the anatomical structures. The algorithm permits precise multi-segmental fusion of CT and MR of the spine, which was not possible using current fusion-algorithms due to variations in the spatial orientation of the anatomical structures caused by different positioning of the axial skeleton in successive examinations.

Entwicklung einer universellen Schnittstellen umgebung zur Übertragung medizinischer Bilddaten mit magnetooptischen Medien / Development of a Universal Interface for the Exchange of Medical Image Data Using Magneto-optical Media

Digital images generated by medical imaging form the basis for radiological diagnosis and surgical planning. Despite the advent of the DICOM 3.0 standard for medical image communication, widespread application of the existing information is often limited by incompatibility of the data formatting used by different equipment generations, and the manufacturer-specific standards employed. An exchange interface based on magneto optical discs has been developed to retrieve and present medical image data regardless of the technological hardware and the specific formats used. Specially adapted routines to retrieve the data first had to be developed. A modular program structure was used to allow flexibility in the implementation of further routines and other exchange media. Over 20,000 CT and MRI images including header information obtained from different General Electric and Siemens scanners were extracted successfully from MO discs. The image data were used for follow up and surgical planning and were transferred to a PAC-server. The interface proved reliable and easy to use. Support for further proprietary formats is currently being developed. The present exchange interface permits reliable retrieval of digital images for diagnostic and surgical planning purposes, regardless of the hardware generation and manufacturer-specific formats.

3-D-Segmentierung der Wirbelsäule mit speziell angepaßten Werkzeugen. 3-D Segmentation of the Spine with Specially Adapted Tools

Segmented 3-D data of the spine form the basis for various modern clinical applications. Among these, multisegmental image fusion, image registration and finite element modeling for biomechanical analysis are promising innovative tools capable of facilitating treatment decisions and optimization of individual therapy in the future. However, the complex anatomy of the spine and the often extensive degenerative deformation presenting in clinical practice, generally limit the application of fully automated segmentation. A newly developed software system is presented that meets the complex requirements for image segmentation of the spine through the use of specially adapted interactive tools that take account of its axial skeletal structure. Furthermore, a standardized protocol is introduced that combines the newly developed interactive tools (rotation transformation, warped dissection plane) and standard segmentation tools to permit rapid and accurate segmentation. To date, the software environment presented herein has been applied with success to the segmentation of cervical, thoracic and lumbar spine.

Navigation-guided opening of the internal auditory canal via the retrosigmoid route for acoustic neuroma surgery: cadaveric, radiological, and preliminary clinical study

OBJECTIVE

We investigated the usefulness of a microscope-based navigational system (Multi Koordinaten Manipulator; Zeiss, Oberkochen, Germany) for removal of the posterior wall of the internal auditory canal (IAC) via the retrosigmoid route.

METHODS

A cadaveric study was performed to assess the navigational localization error for the retrosigmoid approach to the IAC. Computed tomographic findings for 47 acoustic neuroma cases were divided into three groups, on the basis of the relationship between the labyrinth and the sigmoid-fundus line (medial, on the line, or lateral). Furthermore, the shortest distances between the most medial labyrinthine extension and the resection line were measured. In 20 acoustic neuroma operations, the different features and the practicality of the microscope-based navigational system for opening of the IAC were evaluated.

RESULTS

The mean anatomic localization errors were 0.67 +/- 0.2 mm (95th percentile, 1.32 mm) for navigation to the IAC and 0.71 +/- 0.37 mm (95th percentile, 1.68 mm) for navigation to the posterior semicircular canal. The average distances between the most medial labyrinthine extension and the resection line were 3.65, 3.36, and 2.0 mm for the lateral, on-the-line, and medial groups, respectively. Direct contouring of structures at risk does not take into account the localization error, nor does it provide reliable navigational information. A novel indirect contouring concept that takes into account the localization error (the safety corridor method) was therefore introduced.

CONCLUSION

The value of navigational assistance for opening of the IAC is promising but still limited. Further development is required before the clinical effects of this navigational approach can be evaluated.

Universal interface for exchange of medical images via magneto-optical discs

Digital images are the ever-growing basis of modern medical imaging and treatment. Despite the advent of the DICOM 3.0 standard for medical image communication it still requires cumbersome efforts to export images from imaging modalities to other computer systems. This is true especially for smaller institutions, which often have limited resources for standardized image transfer. To gain access even to these data we developed an exchange interface on the basis of magneto-optical discs (MO-discs), as they are usually available in most of the imaging modalities in use today. Unfortunately images on MO-discs are usually stored in formats specific for each manufacturer. Therefore special routines to access the data on MO-discs had to be developed for each company or even each scanner. Over 10,000 CT and MRI images including their header information from different General Electric and Siemens scanners were extracted successfully from MO-discs. The interface proved to be reliable and easy to handle by technicians. Support of additional manufacturers and of the DICOM 3.0 standard are work in progress.

Technical considerations regarding accuracy of the MKM navigation system. An experimental study on impact factors

The purpose of this study was to investigate experimentally, factors determining the navigation accuracy of the MKM navigation system by Zeiss. The MKM consists of an operating microscope mounted to a six-axis motor-driven robot arm and an alpha-workstation. The image-guided surgery device provides navigation information based on calculation of the cartesian coordinates of the robot arm, and coordinates of the focus point assessed by laser assisted measurement. Navigation information (current position, direction and distance to a previously selected target) is optically projected into the microscopic field. Following factors were examined in an experimental setting for their impact on accuracy of the MKM: optical system, mechanical precision of the robot arm, and registration procedure. The robot arm and the optical system of the microscope allow high precision measurements of any focus point (error < 2 mm if the following aspects are considered: the use of auto-focus function instead of manual focusing, positioning of the registration points as a square or a triangle focus point should be selected on a surface that is perpendicular to the optical axis.

An experimental approach to image guided skull base surgery employing a microscope-based neuronavigation system

INTRODUCTION

A cadaveric study was undertaken to investigate the usefulness and reliability of a microscope based navigation system (NS) for skull base surgery.

MATERIAL AND METHODS

CT-scans (1 mm slices) were performed in 10 fixed cadaver heads after implantation of fiducials. There upon, various skull base dissections were undertaken: transethmoidal-transsphenoidal approach to sella and clivus, retrosigmoidal approach to the internal auditory canal (IAC) and to the posterior semicircular canal (PSCC). The navigated dissections were performed with the MKM, a microscope based navigation system of Carl Zeiss (Oberkochen, Germany).

RESULTS

The registration assessment by the NS yielded a mean deviation of 0.23 mm +/- 0.03 mm (mean +/- SD, n = 7, range 0.19 to 0.27 mm). The real anatomical deviation during dissection was 0.67 mm +/- 0.2 mm for navigation to the IAC and 0.71 mm +/- 0.37 mm to the PSCC. This accuracy was achieved with three fiducials (4 x 1 mm titanium screws) arranged as a triangle (side length 4-6 cm) nearby the surgical field. Navigation data on current position, direction and distance to a target structure were helpful in the transethmoidal-transsphenoidal approach to the clivus, as well as for accessing deep seated structures (C1-C2 junction, petrous bone tip). The contouring feature was beneficial for identifying structures embedded in the bone. However, due to inaccurate 3-D modelling this feature has a restricted reliability.

DISCUSSION

Our cadaveric skull base study has shown that the MKM is a reliable tool with high anatomical accuracy and usefulness of most navigation features. However, in order to effectively and reliably use any NS the surgeon must be familiar with its potential features and limitations as is demonstrated in this study.

Comparison of geometry-based and CT voxel-based finite element modelling and experimental validation

The objectives of the paper presented here is the comparison of a geometry-based and voxel-based finite element (FE) method preprocessor of the human femur. The models were experimentally validated by strain gauge measurements (principal stress). The correlation coefficients (r) between the three methods (geometry-based FEM, voxel-based FEM, strain gauge measurements) were found to be in the range 0.91-0.94 (r2: 0.84-0.88). The relationships between the samples are highly significant (P = 0.001), where the strain gauge results are the independent variables. These results suggest that the validity with respect to the principal stress of a voxel-based modelling is similar to the validity of geometry-based modelling. In summary, therefore, we conclude that voxel-based meshing allows a straightforward interfacing with computerized tomography (CT) scans and might contribute to a clinically applicable FEM technology.

Sensitivity of femoral strain pattern analyses to resultant and muscle forces at the hip joint

An automated geometrical preprocessor was developed with the aim of creating three-dimensional finite element models (FEM) of the human femur. On the basis of postprocessed computed tomography data, this preprocessor makes possible rapid, flexible and regular meshing with 'brick' elements. Three different material properties were modelled at the present stage of development. Sensitivity analyses demonstrated that the strain energy density (SED) patterns of the different femoral parts were most sensitive to the implementation of an iliotibial tract force. The variation of the resultant hip force and abductor force direction within the sagittal plane demonstrated a SED minimum at an anterior inclination of 13 degrees; the variation of the resultant force direction within the frontal plane demonstrated a minimum SED at a medial inclination of 21 degrees relative to the mechanical axis of the lower limb. The orientation of the connecting line between the surface-SED-peaks in the horizontal view was found to be most sensitive to the variation of the resultant force within the sagittal plane.

[Automatic generation of 3-D finite element codes of the human femur]

The extremely irregular geometry of bones makes it very difficult to develop and preprocess three-dimensional finite element models (FEM). In the field of biomechanics, the finite element simulation method is a research tool of increasing importance for the prediction of stresses and the stress-compatibility testing of endoprostheses. With this in mind, a FEM preprocessor was developed with the aim of creating three dimensional models of human femurs. On the basis of postprocessed computed tomography data, this preprocessor makes possible rapid, flexible and regular cross-linking. "Brick" elements are used, which are of advantage in terms of computing time, accuracy and computer storage requirements. The software simplifies the generation of models and facilitates the investigation of individual variations, thus providing the basis for utilizing the method in the clinical setting.