Christopher J. Morris

Clinical activity of arsenic trioxide for the treatment of multiple myeloma

Arsenic has been used since ancient times as a therapeutic agent. However, until recently its use in modern medicine has been restricted to the treatment of a limited number of parasitic infections. In the early 1990s, reports from China described impressive results with arsenic trioxide in patients with de novo, relapsed, and refractory acute promyelocytic leukemia (APL). Other investigators subsequently confirmed these results leading to approval of its use for relapsed or refractory APL in the United States. Investigations of this agent have demonstrated that its efficacy in APL and preclinical tumor models is dependent upon a number of mechanisms, including induction of apoptosis, effects on cellular differentiation, cell cycling, and tumor angiogenesis. Subsequent preclinical studies showed significant activity of arsenic trioxide in multiple myeloma (MM). Based on this, in a phase II trial, we have evaluated the activity of arsenic trioxide in 14 patients with relapsed MM, refractory to conventional salvage therapy. With the dose and schedule used, treatment with arsenic trioxide produced responses in three patients and prolonged stable disease in a fourth patient, with the longest response lasting 6 weeks. Although treatment was reasonably well tolerated, in these patients with extensive prior therapy, 11 developed cytopenia, five associated with infectious complications and three developed deep vein thromboses. The results of this small trial support further investigation of this novel drug for the treatment of patients with relapsed or refractory MM.

Non-photorealistic volume rendering using stippling techniques

Simulating hand-drawn illustration techniques can succinctly express information in a manner that is communicative and informative. We present a framework for an interactive direct volume illustration system that simulates traditional stipple drawing. By combining the principles of artistic and scientific illustration, we explore several feature enhancement techniques to create effective, interactive visualizations of scientific and medical datasets. We also introduce a rendering mechanism that generates appropriate point lists at all resolutions during an automatic preprocess, and modifies rendering styles through different combinations of these feature enhancements. The new system is an effective way to interactively preview large, complex volume datasets in a concise, meaningful, and illustrative manner. Volume stippling is effective for many applications and provides a quick and efficient method to investigate volume models.

Illustrative interactive stipple rendering

Simulating hand-drawn illustration can succinctly express information in a manner that is communicative and informative. We present a framework for an interactive direct stipple rendering of volume and surface-based objects. By combining the principles of artistic and scientific illustration, we explore several feature enhancement techniques to create effective, interactive visualizations of scientific and medical data sets. We also introduce a rendering mechanism that generates appropriate point lists at all resolutions during an automatic preprocess and modifies rendering styles through different combinations of these feature enhancements. The new system is an effective way to interactively preview large, complex volume and surface data sets in a concise, meaningful, and illustrative manner. Stippling is effective for many applications and provides a quick and efficient method to investigate both volume and surface models.

Designing effective transfer functions for volume rendering from photographic volumes

Photographic volumes present a unique, interesting challenge for volume rendering. In photographic volumes, the voxel color is pre-determined, making color selection through transfer functions unnecessary. However, photographic data does not contain a clear mapping from the multi-valued color values to a scalar density or opacity, making projection and compositing much more difficult than with traditional volumes. Moreover, because of the nonlinear nature of color spaces, there is no meaningful norm for the multi-valued voxels. Thus, the individual color channels of photographic data must be treated as incomparable data tuples rather than as vector values. Traditional differential geometric tools, such as intensity gradients, density and Laplacians, are distorted by the nonlinear non-orthonormal color spaces that are the domain of the voxel values. We have developed different techniques for managing these issues while directly rendering volumes from photographic data. We present and justify the normalization of color values by mapping RGB values to the CIE L*u*v* color space. We explore and compare different opacity transfer functions that map three-channel color values to opacity. We apply these many-to-one mappings to the original RGB values as well as to the voxels after conversion to L*u*v* space. Direct rendering using transfer functions allows us to explore photographic volumes without having to commit to an a-priori segmentation that might mask fine variations of interest. We empirically compare the combined effects of each of the two color spaces with our opacity transfer functions using source data from the Visible Human project.

ABO mismatch may affect engraftment in multiple myeloma patients receiving nonmyeloablative conditioning.

BACKGROUND: Blood group incompatibility does not appear to affect the overall outcome in patients undergoing myeloablative conditioning before allogeneic BMT. Data on ABO‐mismatched transplantation in the nonmyeloablative setting are limited.

Similar survival with breast conservation therapy or mastectomy in the management of young women with early-stage breast cancer

PURPOSE To evaluate survival outcomes of young women with early-stage breast cancer treated with breast conservation therapy (BCT) or mastectomy, using a large, population-based database. METHODS AND MATERIALS Using the Surveillance, Epidemiology, and End Results (SEER) database, information was obtained for all female patients, ages 20 to 39 years old, diagnosed with T1-2 N0-1 M0 breast cancer between 1990 and 2007, who underwent either BCT (lumpectomy and radiation treatment) or mastectomy. Multivariable and matched pair analyses were performed to compare overall survival (OS) and cause-specific survival (CSS) of patients undergoing BCT and mastectomy. RESULTS A total of 14,764 women were identified, of whom 45% received BCT and 55% received mastectomy. Median follow-up was 5.7 years (range, 0.5-17.9 years). After we accounted for all patient and tumor characteristics, multivariable analysis found that BCT resulted in OS (hazard ratio [HR], 0.93; 95% confidence interval [CI], 0.83-1.04; p = 0.16) and CSS (HR, 0.93; CI, 0.83-1.05; p = 0.26) similar to that of mastectomy. Matched pair analysis, including 4,644 BCT and mastectomy patients, confirmed no difference in OS or CSS: the 5-, 10-, and 15-year OS rates for BCT and mastectomy were 92.5%, 83.5%, and 77.0% and 91.9%, 83.6%, and 79.1%, respectively (p = 0.99), and the 5-, 10-, and 15-year CSS rates for BCT and mastectomy were 93.3%, 85.5%, and 79.9% and 92.5%, 85.5%, and 81.9%, respectively (p = 0.88). CONCLUSIONS Our analysis of this population-based database suggests that young women with early-stage breast cancer have similar survival rates whether treated with BCT or mastectomy. These patients should be counseled appropriately regarding their treatment options and should not choose a mastectomy based on the assumption of improved survival.

Deep view: high-resolution reality

We have designed the Deep View visualization system, which consists of a Linux cluster that performs computations to produce 3D geometry, renders the geometry to produce 2D pixels, and then transfers the pixels to be displayed on the T221 display (or video wall). We accelerate the pixel transfer operations using IBMs Scalable Graphics Engine (SGE). We drive high-resolution displays at interactive frame rates using our cluster and the SGE. The SGE is a network-attached frame buffer capable of double buffering up to 16 million pixels. It routes incoming pixels from multiple sources to the appropriate locations in its frame buffer and then transfers the composited result to the T221 display using digital video interface (DVI) output. In total, the SGE can accept up to 16 input links and can drive as many as eight synchronized DVI outputs. In addition, it can time interleave image pairs from its frame buffer to effect time-division stereo. In the current Deep View configuration, the rendered pixels are sent by each node in the cluster to the SGE over a Gigabit Ethernet link, and we use four of the synchronized DVI outputs to drive the T221 at full resolution.

Volume warping for adaptive isosurface extraction

Polygonal approximations of isosurfaces extracted from uniformly sampled volumes are increasing in size due to the availability of higher resolution imaging techniques. The large number of I primitives represented hinders the interactive exploration of the dataset. Though many solutions have been proposed to this problem, many require the creation of isosurfaces at multiple resolutions or the use of additional data structures, often hierarchical, to represent the volume. We propose a technique for adaptive isosurface extraction that is easy to implement and allows the user to decide the degree of adaptivity as well as the choice of isosurface extraction algorithm. Our method optimizes the extraction of the isosurface by warping the volume. In a warped volume, areas of importance (e.g. containing significant details) are inflated while unimportant ones are contracted. Once the volume is warped, any extraction algorithm can be applied. The extracted mesh is subsequently unwarped such that the warped areas are rescaled to their initial proportions. The resulting isosurface is represented by a mesh that is more densely sampled in regions decided as important.

SPVN: a new application framework for interactive visualization of large datasets

We present SPVN (Scalable Parallel Visual Networking), a new application framework for interactive visualization of large datasets. We designed SPVN with four main goals in mind. First, we wanted to make it easier for developers to write visualization applications that can handle massive datasets and deliver interactive frame rates. SPVN provides developers with efficient implementations of many optimization techniques such as spatialization, simplification, view-frustum culling, occlusion culling, multithreading, and prefetching. Second, we wanted developers to better leverage the performance and scalability of a cluster of inexpensive rendering servers, while insulating them from the complexities of distributed programming. SPVN provides implementations of sort-first rendering with dynamic load balancing, sort-last rendering with depth-order and binary-swap image compositing, and a distributed shared memory mechanism that gives programmers the illusion that all machines have all the data at all times. Third, we wanted to support multiple low-level rendering libraries. SPVN separates modeling from rendering so that the same scene can be rendered by different back-ends (e.g., OpenGL, DirectX, or ray tracing). Finally, we wanted SPVN to be easy to use and extend. SPVN uses the familiar concept of a scene graph, applies many well-established design patterns (e.g., smart pointers, factories, observers, and visitors), and allows for extensions of shape classes, rendering algorithms, and file formats using registry and plug-in mechanisms. We have used SPVN to develop both remote and immersive visualization applications, and found that SPVN reduces the amount of time and money it takes to write such applications.

Direct volume rendering of photographic volumes using multi-dimensional color-based transfer functions

Traditionally, volume rendering of medical data has been comprised of transfer functions that map a scalar value, usually a MRI or CT intensity, to an opacity. Corresponding color maps are either selected regardless of the actual physical color of the volume (i.e. greyscale) or predetermined as in photographic volumes. Rarely has the voxel color been used as a means to define the associated opacity value. By using transfer functions that map multi-channel color values(RGB or CIE L*u*v*) to opacity, we can generate compelling and informative renderings that provide consistent boundary extraction throughout the volume. We present renderings of the Visible Human photographic volume using multi-dimensional color-based transfer functions. These functions were constructed by using gradient boundary enhancement techniques in conjunction with volume illustration techniques and incorporating the first and second directional derivatives along the gradient direction. We empirically compare the effectiveness of using the color-based transfer functions and discuss their applications and potential for future development.