Tailoring Radiation Therapy for Patients With Limited Cutaneous T Cell Lymphoma: Preliminary Clinical Experience With Subtotal Skin Electron Therapy.

BACKGROUND/AIM: Total skin electron beam therapy (TSEBT) is an effective treatment for managing cutaneous T-cell lymphoma (CTCL), but may result in unnecessary toxicity. With the production of a custom rolling shield holding a configurable stack of plastic slats to block uninvolved skin, we implemented a program for subtotal skin electron beam therapy (STSEBT). We report our preliminary experience with STSEBT vs. TSEBT to manage CTCL. PATIENTS AND METHODS: A retrospective review of 32 CTCL patients who were treated at a single institution between February 28th, 2017, and May 25th, 2022, was completed. Of these cases, seven patients received STSEBT and 25 received TSEBT. RESULTS: Thirty-two patients underwent a course of STSEBT or TSEBT. The median follow-up was 465 days and the median age at diagnosis was 70.8 years. Stage distribution was as follows: one (3%) IA, 16 (50%) IB, 6 (19%) IIB, two (6%) IIIA, five (16%) IVA, and two (6%) IVB. The overall response rate was 96%. For patients receiving TSEBT (n=25), three (12%), 10 (40%), and 11 (44%) had a CR, NCR, and PR, respectively. For the patients receiving STSEBT, four (57.1%), three (42.9%), and zero (0%) had a CR, NCR, and PR, respectively. There was one patient (4%) with no response. Cumulative incidence of progressive skin disease requiring additional electron therapy at three months was 21.1% [IQR=8.6, 51.5%], 36.8% [IQR=20, 68%] at six months, and 57.9% [IQR=38.5, 87.1%] at one year. Low rates of toxicities were recorded. CONCLUSION: This analysis demonstrated that treatment of CTCL patients with low disease burden with STSEBT results in similar overall response and time to progression compared to treatment with TSEBT.

Development and Dosimetric Characterization of a Customizable Shield for Subtotal Skin Electron Beam Therapy.

Purpose: Purpose: Subtotal skin electron beam therapy may be an option for patients with cutaneous lymphoma receiving radiation therapy to treat large areas of their skin but may benefit from sparing specific areas that may have had previous radiation therapy, are of specific cosmetic concern, and/or show no evidence of disease. We report here on the design, implementation, and dosimetric characteristics of a reusable and transparent customizable shield for use with the large fields used to deliver total skin electron beam therapy at extended distance with a conventional linear accelerator. Methods and Materials: A shield was designed and manufactured consisting of acrylic blocks that can be mounted on a steel frame to allow patient-specific shielding. The dosimetry of the device was measured using radiochromic film. Results: The shield is easy to use and well-tolerated for patient treatment, providing minimal electron transmission through the shield with a sharp penumbra at the field edge, with no increase in x-ray dose. We report on the dosimetry of a commercial device that has been used to treat more than 30 patients to date. Conclusions: The customizable shield is well suited to providing patient-specific shielding for subtotal skin electron beam therapy.

PARAFAC2×N: Coupled decomposition of multi-modal data with drift in N modes.

Analysis of GC×GC-TOFMS data for large numbers of poorly-resolved peaks, and for large numbers of samples remains an enduring problem that hinders the widespread application of the technique. For multiple samples, GC×GC-TOFMS data for specific chromatographic regions manifests as a 4th order tensor of I mass spectral acquisitions, J mass channels, K modulations, and L samples. Chromatographic drift is common along both the first-dimension (modulations), and along the second-dimension (mass spectral acquisitions), while drift along the mass channel is for all practical purposes nonexistent. A number of solutions to handling GC×GC-TOFMS data have been proposed: these involve reshaping the data to make it amenable to either 2nd order decomposition techniques based on Multivariate Curve Resolution (MCR), or 3rd order decomposition techniques such as Parallel Factor Analysis 2 (PARAFAC2). PARAFAC2 has been utilised to model chromatographic drift along one mode, which has enabled its use for robust decomposition of multiple GC-MS experiments. Although extensible, it is not straightforward to implement a PARAFAC2 model that accounts for drift along multiple modes. In this submission, we demonstrate a new approach and a general theory for modelling data with drift along multiple modes, for applications in multidimensional chromatography with multivariate detection. The proposed model captures over 99.9% of variance for a synthetic data set, presenting an extreme example of peak drift and co-elution across two modes of separation.

Untargeted region of interest selection for gas chromatography - mass spectrometry data using a pseudo F-ratio moving window.

There are many challenges associated with analysing gas chromatography - mass spectrometry (GC-MS) data. Many of these challenges stem from the fact that electron ionization (EI) can make it difficult to recover molecular information due to the high degree of fragmentation with concomitant loss of molecular ion signal. With GC-MS data there are often many common fragment ions shared among closely-eluting peaks, necessitating sophisticated methods for analysis. Some of these methods are fully automated, but make some assumptions about the data which can introduce artifacts during the analysis. Chemometric methods such as Multivariate Curve Resolution (MCR), or Parallel Factor Analysis (PARAFAC/PARAFAC2) are particularly attractive, since they are flexible and make relatively few assumptions about the data - ideally resulting in fewer artifacts. These methods do require expert user intervention to determine the most relevant regions of interest and an appropriate number of components, k, for each region. Automated region of interest selection is needed to permit automated batch processing of chromatographic data with advanced signal deconvolution. Here, we propose a new method for automated, untargeted region of interest selection that accounts for the multivariate information present in GC-MS data to select regions of interest based on the ratio of the squared first, and second singular values from the Singular Value Decomposition (SVD) of a window that moves across the chromatogram. Assuming that the first singular value accounts largely for signal, and that the second singular value accounts largely for noise, it is possible to interpret the relationship between these two values as a probabilistic distribution of Fisher Ratios. The sensitivity of the algorithm was tested by investigating the concentration at which the algorithm can no longer pick out chromatographic regions known to contain signal. The algorithm achieved detection of features in a GC-MS chromatogram at concentrations below 10 pg on-column. The resultant probabilities can be interpreted as regions that contain features of interest.

Global metabolome analysis of Dunaliella tertiolecta, Phaeobacter italicus R11 Co-cultures using thermal desorption - Comprehensive two-dimensional gas chromatography - Time-of-flight mass spectrometry (TD-GC×GC-TOFMS).

Dunaliella tertiolecta is a marine microalgae that has been studied extensively as a potential carbon-neutral biofuel source (Tang et al., 2011). Microalgae oil contains high quantities of energy-rich fatty acids and lipids, but is not yet commercially viable as an alternative fuel. Carefully optimised growth conditions, and more recently, algal-bacterial co-cultures have been explored as a way of improving the yield of D. tertiolecta microalgae oils. The relationship between the host microalgae and bacterial co-cultures is currently poorly understood. Here, a complete workflow is proposed to analyse the global metabolomic profile of co-cultured D. tertiolectra and Phaeobacter italicus R11, which will enable researchers to explore the chemical nature of this relationship in more detail. To the best of the authors' knowledge this study is one of the first of its kind, in which a pipeline for an entirely untargeted analysis of the algal metabolome is proposed using a practical sample preparation, introduction, and data analysis routine.