Mechano-electrical interactions and heterogeneities in wild-type and drug-induced long QT syndrome rabbits.

Electromechanical reciprocity - comprising electro-mechanical (EMC) and mechano-electric coupling (MEC) - provides cardiac adaptation to changing physiological demands. Understanding electromechanical reciprocity and its impact on function and heterogeneity in pathological conditions - such as (drug-induced) acquired long QT syndrome (aLQTS) - might lead to novel insights in arrhythmogenesis. Our aim is to investigate how electrical changes impact on mechanical function (EMC) and vice versa (MEC) under physiological conditions and in aLQTS. To measure regional differences in EMC and MEC in vivo, we used tissue phase mapping cardiac MRI and a 24-lead ECG vest in healthy (control) and IKr -blocker E-4031-induced aLQTS rabbit hearts. MEC was studied in vivo by acutely increasing cardiac preload, and ex vivo by using voltage optical mapping (OM) in beating hearts at different preloads. In aLQTS, electrical repolarization (heart rate corrected RT-interval, RTn370) was prolonged compared to control (P < 0.0001) with increased spatial and temporal RT heterogeneity (P < 0.01). Changing electrical function (in aLQTS) resulted in significantly reduced diastolic mechanical function and prolonged contraction duration (EMC), causing increased apico-basal mechanical heterogeneity. Increased preload acutely prolonged RTn370 in both control and aLQTS hearts (MEC). This effect was more pronounced in aLQTS (P < 0.0001). Additionally, regional RT-dispersion increased in aLQTS. Motion-correction allowed us to determine APD-prolongation in beating aLQTS hearts, but limited motion correction accuracy upon preload-changes prevented a clear analysis of MEC ex vivo. Mechano-induced RT-prolongation and increased heterogeneity were more pronounced in aLQTS than in healthy hearts. Acute MEC effects may play an additional role in LQT-related arrhythmogenesis, warranting further mechanistic investigations. KEY POINTS: Electromechanical reciprocity comprising excitation-contraction coupling (EMC) and mechano-electric feedback loops (MEC) is essential for physiological cardiac function. Alterations in electrical and/or mechanical heterogeneity are known to have potentially pro-arrhythmic effects. In this study, we aimed to investigate how electrical changes impact on the mechanical function (EMC) and vice versa (MEC) both under physiological conditions (control) and in acquired long QT syndrome (aLQTS). We show that changing the electrical function (in aLQTS) results in significantly altered mechanical heterogeneity via EMC and, vice versa, that increasing the preload acutely prolongs repolarization duration and increases electrical heterogeneity, particularly in aLQTS as compared to control. Our results substantiate the hypothesis that LQTS is an ?electro-mechanical', rather than a 'purely electrical', disease and suggest that acute MEC effects may play an additional role in LQT-related arrhythmogenesis.

Acute Medical Ward for better care coordination of patients admitted with infection - evidence from a tertiary hospital in Singapore.

Coordination and consolidation of care provided in acute care hospitals need reconfiguration and reorganization to meet the demand of large number of acute admissions. We report on the effectiveness of an Acute Medical Ward AMW (AMW) receiving cases that were suspected to have infection related diagnosis on admission by Emergency Department (ED), addressing this in a large tertiary hospital in South East Asia. Mean Length of Stay (LOS) was compared using Gamma Generalized Linear Models with Log-link while odds of readmissions and mortality were compared using logistic regression models. The LOS (mean: 5.8 days, SD: 9.1 days) of all patients admitted to AMW was similar to discharge diagnosis-matched general ward (GW) patients admitted before AMW implementation, readmission rates were lower (15-day: 5.3%, 30-day: 8.1%). Bivariate and multivariate models revealed that mean LOS after AMW implementation was not significantly different from before AMW implementation (Ratio: 0.99, p=0.473). Our AMW had reduced readmission rates for patients with infection but has not made an overall impact on the LOS and readmission rates for the department as a whole.

A comparison of single-dose dexmedetomidine or propofol on the incidence of emergence delirium in children undergoing general anaesthesia for magnetic resonance imaging.

Emergence delirium is a significant problem in children regaining consciousness following general anaesthesia. We compared the emergence characteristics of 120 patients randomly assigned to receive a single intravenous dose of dexmedetomidine 0.3 µg.kg(-1) , propofol 1 mg.kg(-1) , or 10 ml saline 0.9% before emerging from general anaesthesia following a magnetic resonance imaging scan. Emergence delirium was diagnosed as a score of 10 or more on the Paediatric Anaesthesia Emergence Delirium scale. The incidence of emergence delirium was 42.5% in the dexmedetomidine group, 33.3% in the propofol group and 41.5% in the saline group (p = 0.671). Three patients in the dexmedetomidine group, none in the propofol group and two in the saline group required pharmacological intervention for emergence delirium (p = 0.202). Administration of neither dexmedetomidine nor propofol significantly reduced the incidence, or severity, of emergence delirium. The only significant predictor for emergence delirium was the time taken to awaken from general anaesthesia, with every minute increase in wake-up time reducing the odds of emergence delirium by 7%.

Quality of Large Language Model Responses to Radiation Oncology Patient Care Questions.

Importance: Artificial intelligence (AI) large language models (LLMs) demonstrate potential in simulating human-like dialogue. Their efficacy in accurate patient-clinician communication within radiation oncology has yet to be explored. Objective: To determine an LLM's quality of responses to radiation oncology patient care questions using both domain-specific expertise and domain-agnostic metrics. Design, Setting, and Participants: This cross-sectional study retrieved questions and answers from websites (accessed February 1 to March 20, 2023) affiliated with the National Cancer Institute and the Radiological Society of North America. These questions were used as queries for an AI LLM, ChatGPT version 3.5 (accessed February 20 to April 20, 2023), to prompt LLM-generated responses. Three radiation oncologists and 3 radiation physicists ranked the LLM-generated responses for relative factual correctness, relative completeness, and relative conciseness compared with online expert answers. Statistical analysis was performed from July to October 2023. Main Outcomes and Measures: The LLM's responses were ranked by experts using domain-specific metrics such as relative correctness, conciseness, completeness, and potential harm compared with online expert answers on a 5-point Likert scale. Domain-agnostic metrics encompassing cosine similarity scores, readability scores, word count, lexicon, and syllable counts were computed as independent quality checks for LLM-generated responses. Results: Of the 115 radiation oncology questions retrieved from 4 professional society websites, the LLM performed the same or better in 108 responses (94%) for relative correctness, 89 responses (77%) for completeness, and 105 responses (91%) for conciseness compared with expert answers. Only 2 LLM responses were ranked as having potential harm. The mean (SD) readability consensus score for expert answers was 10.63 (3.17) vs 13.64 (2.22) for LLM answers (P < .001), indicating 10th grade and college reading levels, respectively. The mean (SD) number of syllables was 327.35 (277.15) for expert vs 376.21 (107.89) for LLM answers (P = .07), the mean (SD) word count was 226.33 (191.92) for expert vs 246.26 (69.36) for LLM answers (P = .27), and the mean (SD) lexicon score was 200.15 (171.28) for expert vs 219.10 (61.59) for LLM answers (P = .24). Conclusions and Relevance: In this cross-sectional study, the LLM generated accurate, comprehensive, and concise responses with minimal risk of harm, using language similar to human experts but at a higher reading level. These findings suggest the LLM's potential, with some retraining, as a valuable resource for patient queries in radiation oncology and other medical fields.

Determining risk and predictors of head and neck cancer treatment-related lymphedema: A clinicopathologic and dosimetric data mining approach using interpretable machine learning and ensemble feature selection.

Background and purpose: The ability to determine the risk and predictors of lymphedema is vital in improving the quality of life for head and neck (HN) cancer patients. However, selecting robust features is challenging due to the multicollinearity and high dimensionality of radiotherapy (RT) data. This study aims to overcome these challenges using an ensemble feature selection technique with machine learning (ML). Materials and methods: Thirty organs-at-risk, including bilateral cervical lymph node levels, were contoured, and dose-volume data were extracted from 76 HN treatment plans. Clinicopathologic data was collected. Ensemble feature selection was used to reduce the number of features. Using the reduced features as input to ML and competing risk models, internal and external lymphedema prediction capability was evaluated with the ML models, and time to lymphedema event and risk stratification were estimated using the risk models. Results: Two ML models, XGBoost and random forest, exhibited robust prediction performance. They achieved average F1-scores and AUCs of 84 ± 3.3 % and 79 ± 11.9 % (external lymphedema), and 64 ± 12 % and 78 ± 7.9 % (internal lymphedema). Predictive ML and risk models identified common predictors, including bulky node involvement, high dose to various lymph node levels, and lymph nodes removed during surgery. At 180 days, removing 0-25, 26-50, and > 50 lymph nodes increased external lymphedema risk to 72.1 %, 95.6 %, and 57.7 % respectively (p = 0.01). Conclusion: Our approach, involving the reduction of HN RT data dimensionality, resulted in effective ML models for HN lymphedema prediction. Predictive dosimetric features emerged from both predictive and competing risk models. Consistency with clinicopathologic features from other studies supports our methodology.

Clinical, Pathologic, and Dosimetric Predictors of Head and Neck Lymphedema Following Definitive or Adjuvant Radiation Therapy for Head and Neck Cancer.

Purpose: Head and neck lymphedema (HNL) following radiation therapy for head and neck cancer (HNC) causes patient morbidity. Predicting individual patients' risk of HNL after treatment is challenging. We aimed to identify the demographic, disease-related, and treatment-related factors associated with external and internal HNL following treatment of HNC with definitive or adjuvant radiation therapy. Methods and Materials: Relevant clinical, pathologic, and dosimetric data for 76 consecutive patients who received definitive or adjuvant radiation ± chemotherapy were retrospectively collected from a single institution. Multivariable models predictive of external and internal lymphedema using clinicopathologic variables alone and in combination with dosimetric variables were constructed and optimized using competing risk regression. Results: After median follow-up of 550 days, the incidence of external and internal HNL at 360 days was 70% and 34%, respectively. When evaluating clinical and treatment-related factors alone, number of lymph nodes removed and advanced adenopathy status were predictive of external lymphedema. With incorporation of dosimetric variables, the optimized model included the percentage volume of the contralateral lymph node level VII receiving 30Gy V30 ≥50%, number of lymph nodes removed, and advanced adenopathy status. For internal lymphedema, our clinicopathologic model identified both adjuvant radiation, as opposed to definitive radiation, and advanced adenopathy status. With inclusion of a dosimetric variable, the optimized model included larynx V45 ≥50% and advanced adenopathy. Conclusions: HNL following HNC treatment is common. For both external and internal lymphedema, nodal disease burden at diagnosis predicts increased risk. For external lymphedema, increasing extent of lymph node dissection prior to adjuvant therapy increases risk. The contralateral level VII lymph node region is also predictive of external lymphedema when radiation dose to V30 is ≥50%, meriting investigation. For internal lymphedema, we confirm that increasing radiation dose to the larynx is the most significant dosimetric predictor of mucosal edema when larynx V45 is ≥50%.

GlioPredictor: a deep learning model for identification of high-risk adult IDH-mutant glioma towards adjuvant treatment planning.

Identification of isocitrate dehydrogenase (IDH)-mutant glioma patients at high risk of early progression is critical for radiotherapy treatment planning. Currently tools to stratify risk of early progression are lacking. We sought to identify a combination of molecular markers that could be used to identify patients who may have a greater need for adjuvant radiation therapy machine learning technology. 507 WHO Grade 2 and 3 glioma cases from The Cancer Genome Atlas, and 1309 cases from AACR GENIE v13.0 datasets were studied for genetic disparities between IDH1-wildtype and IDH1-mutant cohorts, and between different age groups. Genetic features such as mutations and copy number variations (CNVs) correlated with IDH1 mutation status were selected as potential inputs to train artificial neural networks (ANNs) to predict IDH1 mutation status. Grade 2 and 3 glioma cases from the Memorial Sloan Kettering dataset (n = 404) and Grade 3 glioma cases with subtotal resection (STR) from Northwestern University (NU) (n = 21) were used to further evaluate the best performing ANN model as independent datasets. IDH1 mutation is associated with decreased CNVs of EGFR (21% vs. 3%), CDKN2A (20% vs. 6%), PTEN (14% vs. 1.7%), and increased percentage of mutations for TP53 (15% vs. 63%), and ATRX (10% vs. 54%), which were all statistically significant (p < 0.001). Age > 40 was unable to identify high-risk IDH1-mutant with early progression. A glioma early progression risk prediction (GlioPredictor) score generated from the best performing ANN model (6/6/6/6/2/1) with 6 inputs, including CNVs of EGFR, PTEN and CDKN2A, mutation status of TP53 and ATRX, patient's age can predict IDH1 mutation status with over 90% accuracy. The GlioPredictor score identified a subgroup of high-risk IDH1-mutant in TCGA and NU datasets with early disease progression (p = 0.0019, 0.0238, respectively). The GlioPredictor that integrates age at diagnosis, CNVs of EGFR, CDKN2A, PTEN and mutation status of TP53, and ATRX can identify a small cohort of IDH-mutant with high risk of early progression. The current version of GlioPredictor mainly incorporated clinically often tested genetic biomarkers. Considering complexity of clinical and genetic features that correlate with glioma progression, future derivatives of GlioPredictor incorporating more inputs can be a potential supplement for adjuvant radiotherapy patient selection of IDH-mutant glioma patients.

Imaging appearances for recurrent nasopharyngeal carcinoma and post-salvage nasopharyngectomy.

Nasopharyngeal carcinoma (NPC) is a head and neck neoplasm that occurs in endemic numbers among people of southern Chinese descent. External beam radiation to the nasopharyngeal bed and primary draining lymph node echelons is the mainstay of treatment with concurrent cisplatin-based chemotherapy for more advanced disease. Detection of residual and/or recurrent NPC has important clinical implications, as salvage protocols are available. The review aims to increase awareness of the imaging features of NPC recurrences at local and distant sites using computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET). Important changes in imaging seen in patients after nasopharyngectomy are also discussed.

Image-Based Deep Neural Network for Individualizing Radiotherapy Dose Is Transportable Across Health Systems.

PURPOSE: We developed a deep neural network that queries the lung computed tomography-derived feature space to identify radiation sensitivity parameters that can predict treatment failures and hence guide the individualization of radiotherapy dose. In this article, we examine the transportability of this model across health systems. METHODS: This multicenter cohort-based registry included 1,120 patients with cancer in the lung treated with stereotactic body radiotherapy. Pretherapy lung computed tomography images from the internal study cohort (n = 849) were input into a multitask deep neural network to generate an image fingerprint score that predicts time to local failure. Deep learning (DL) scores were input into a regression model to derive iGray, an individualized radiation dose estimate that projects a treatment failure probability of < 5% at 24 months. We validated our findings in an external, holdout cohort (n = 271). RESULTS: There were substantive differences in the baseline patient characteristics of the two study populations, permitting an assessment of model transportability. In the external cohort, radiation treatments in patients with high DL scores failed at a significantly higher rate with 3-year cumulative incidences of local failure of 28.5% (95% CI, 19.8 to 37.8) versus 10.2% (95% CI, 5.9 to 16.2; hazard ratio, 3.3 [95% CI, 1.74 to 6.49]; P < .001). A model that included DL score alone predicted treatment failures with a concordance index of 0.68 (95% CI, 0.59 to 0.77), which had a similar performance to a nested model derived from within the internal cohort (0.70 [0.64 to 0.75]). External cohort patients with iGray values that exceeded the delivered doses had proportionately higher rates of local failure (P < .001). CONCLUSION: Our results support the development and implementation of new DL-guided treatment guidance tools in the image-replete and highly standardized discipline of radiation oncology.

Deterministic small-scale undulations of image-based risk predictions from the deep learning of lung tumors in motion.

INTRODUCTION: Deep learning (DL) models that use medical images to predict clinical outcomes are poised for clinical translation. For tumors that reside in organs that move, however, the impact of motion (i.e., degenerated object appearance or blur) on DL model accuracy remains unclear. We examine the impact of tumor motion on an image-based DL framework that predicts local failure risk after lung stereotactic body radiotherapy (SBRT). METHODS: We input pre-therapy free breathing (FB) computed tomography (CT) images from 849 patients treated with lung SBRT into a multitask deep neural network to generate an image fingerprint signature (or DL score) that predicts time-to-event local failure outcomes. The network includes a convolutional neural network encoder for extracting imaging features and building a task-specific fingerprint, a decoder for estimating handcrafted radiomic features, and a task-specific network for generating image signature for radiotherapy outcome prediction. The impact of tumor motion on the DL scores was then examined for a holdout set of 468 images from 39 patients comprising: (1) FB CT, (2) four-dimensional (4D) CT, and (3) maximum-intensity projection (MIP) images. Tumor motion was estimated using a 3D vector of the maximum distance traveled, and its association with DL score variance was assessed by linear regression. FINDINGS: The variance and amplitude in 4D CT image-derived DL scores were associated with tumor motion (R2  = 0.48 and 0.46, respectively). Specifically, DL score variance was deterministic and represented by sinusoidal undulations in phase with the respiratory cycle. DL scores, but not tumor volumes, peaked near end-exhalation. The mean of the scores derived from 4D CT images and the score obtained from FB CT images were highly associated (Pearson r = 0.99). MIP-derived DL scores were significantly higher than 4D- or FB-derived risk scores (p < 0.0001). INTERPRETATION: An image-based DL risk score derived from a series of 4D CT images varies in a deterministic, sinusoidal trajectory in a phase with the respiratory cycle. These results indicate that DL models of tumors in motion can be robust to fluctuations in object appearance due to movement and can guide standardization processes in the clinical translation of DL models for patients with lung cancer.

Reducing the tracking drift of an uncontoured tumor for a portal-image-based dynamically adapted conformal radiotherapy treatment.

Accurate tracking of organ motion during treatment is needed to improve the efficacy of radiation therapy. This work investigates the feasibility of tracking an uncontoured target using the motion detected within a moving treatment aperture. Tracking was achieved with a weighted optical flow algorithm, and three different techniques for updating the reference image were evaluated. The accuracy and susceptibility of each approach to the accumulation of position errors were verified using a 3D-printed tumor (mounted on an actuator) and a virtual treatment aperture. Tumor motion up to 15.8 mm (peak-to-peak) taken from the breathing patterns of seven lung cancer patients was acquired using an amorphous silicon portal imager at ~ 7.5 frames/s. The first approach (INI) used the initial image detected, as a fixed reference, to determine the target motion for each new incoming image, and performed the best with the smallest errors. This method was also the most robust against the accumulation of position errors. Mean absolute errors of 0.16, 0.32, and 0.38 mm were obtained for the three methods, respectively. Although the errors are comparable to other tracking methods, the proposed method does not require prior knowledge of the tumor shape and does not need a tumor template or contour for tracking. Graphical abstract.

Evaluating a potential technique with local optical flow vectors for automatic organ-at-risk (OAR) intrusion detection and avoidance during radiotherapy.

Various techniques of deep inspiration breath hold (DIBH) have been used to mitigate the likelihood and risk of exposing the heart, an organ-at-risk (OAR) for unintended radiation during left breast radiotherapy. However, issues of reproducibility of these techniques warrant further investigation into the feasibility of detecting the intrusion of an OAR into the treatment field during intra-fractional treatment delivery. The increase of high-dose, low-fraction radiotherapy treatments makes it important to immediately adapt treatment once an OAR is detected in the treatment field. This proof-of-concept implementation includes an algorithm that detects and tracks the motion at the edges of a treatment field and a control algorithm that adapts the treatment aperture according to the motion detected. In accordance to the AAPM Task-Group (TG-132) report, image registration techniques should be verified with virtual and physical phantoms prior to clinical application. Since most OARs move as a result of respiration-induced motion, we have used a lung phantom to generate images of a generic OAR intruding into a treatment field with known velocity. The phantom was programmed to move with sinusoidal and lung patient tumor motion patterns and the accuracy of intrusion tracking and MLC adaptation were benchmarked with the ground truth-programmed motion of the OAR. The motions were recorded with an electronic portal imaging device (EPID). An optimal cluster size of 9 × 9 motion vectors was found to provide the smallest average absolute position error of 0.3 mm. A strong linear correlation between the adapted MLC leaves and the actual OAR position was observed. The algorithm had a mean position tracking error of -0.4 ± 0.3 mm and a precision of 1.1 mm. It is possible to adapt MLC leaves based on the motion detected at the edges of the irradiated field, and it would be feasible to shield an unplanned intrusion of an OAR into the treatment field.

Application of TG-100 risk analysis methods to the acceptance testing and commissioning process of a Halcyon linear accelerator.

PURPOSE: A new type of linear accelerator (linac) was recently introduced into the market by a major manufacturer. Our institution is one of the early users of this preassembled and preconfigured dual-layer multileaf collimator (MLC), ring-gantry linac - Halcyon™ (1st version). We performed a set of full acceptance testing and commissioning (ATC) measurements for three Halcyon machines and compared the measured data with the standard beam model provided by the manufacturer. The ATC measurements were performed following the guidelines given in different AAPM protocols as well as guidelines provided by the manufacturer. The purpose of the present work was to perform a risk assessment of the ATC process for this new type of linac and investigate whether the results obtained from this analysis could potentially be used as a guideline for improving the design features of this type of linac. METHODS: AAPM's TG100 risk assessment methodology was applied to the ATC process. The acceptance testing process relied heavily on the use of a manufacturer-supplied phantom and the automated analysis of electronic portal imaging device (EPID) images. For the commissioning process, a conventional measurement setup and process (e.g., use of water tank for scanning) was largely used. ATC was performed using guidelines recommended in various AAPM protocols (e.g., TG-106, TG-51) as well as guidelines provided by the manufacturer. Six medical physicists were involved in this study. Process maps, process steps, and failure modes (FMs) were generated for the ATC procedures. Failure modes and effects analysis (FMEA) were performed following the guidelines given in AAPM TG-100 protocol. The top 5 and top 10 highest-ranked FMs were identified for the acceptance and commissioning procedures, respectively. Quality control measures were suggested to mitigate these FMs. RESULTS: A total of 38 steps and 88 FMs were identified for the entire ATC process. Fourteen steps and 34 FMs arose from acceptance testing. The top 5 FMs that were identified could potentially be mitigated by the manufacturer. For commissioning, a total of 24 steps and 54 potential FMs were identified. The use of separate measurement tools that are not machine-integrated has been identified as a cause for the higher number of steps and FMs generated from the conventional ATC approach. More than half of the quality control measures recommended for both acceptance and commissioning could potentially be incorporated by the manufacturer in the design of the Halcyon machine. CONCLUSION: This paper presents the results of FMEA and quality control measures to mitigate the FMs for the ATC process for Halcyon machine. Unique FMs that result from the differences in the ATC guidelines provided by the vendor and current conventional protocols, and the challenges of performing the ATC due to the new linac features and ring-gantry design were highlighted for the first time. The FMs identified in the present work along with the suggested quality control measures, could potentially be used to improve the design features of future ring-gantry type of linacs that are likely to be preassembled, preconfigured, and heavily reliant on automation and image guidance.

Alloantigen recognition is critical for CD8 T cell-mediated graft anti-tumor activity against murine BCL1 lymphoma after myeloablative bone marrow transplantation.

The goal of the current study was to determine whether whole bone marrow cells or splenic CD8(+) T cells from C57BL/6 (H-2(b)) donor mice, which are tolerant to BALB/c (H-2(d)) alloantigens, are capable of mediating graft anti-tumor activity against a BALB/c B-cell lymphoma after injection into irradiated BALB/c hosts. The experimental results show that high doses of splenic CD8(+) T cells mixed with T cell-depleted bone marrow cells from C57BL/6 non-tolerant (normal) donors eliminate the BCL(1) B-cell lymphoma cells and induce lethal graft-versus-host disease (GVHD). CD8(+) T cells from tolerant donors simultaneously lose both their ability to induce GVHD and their anti-tumor activity. Whole bone marrow cell transplants from normal donors eliminated BCL(1) tumor cells without inducing GVHD, and bone marrow cells from tolerant donors failed to eliminate the tumor cells. The infused BCL(1) tumor cells expressed an immunogenic tumor-specific idiotype antigen disparate from host alloantigens, indicating that recognition of the tumor-specific antigen alone was insufficient to elicit graft anti-tumor activity from unimmunized allotolerant donor splenic CD8(+) T cells or whole bone marrow cells. We conclude that CD8(+) T cells from unimmunized normal donor mice require alloantigen recognition to mediate their anti-tumor activity following allogeneic BMT.

High resolution allelotype of microdissected primary nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC) is a common cancer in South China but is rare in other parts of the world. To better understand the molecular basis of this cancer, we performed high-resolution allelotyping on 27 microdissected primary tumors using 382 microsatellite markers. We have detected high frequencies of allelic imbalance on 3p (96.3%), 9p (85.2%), 9q (88.9%), 11q (74.1%), 12q (70.4%), 13q (55.6%), 14q (85.2%), and 16q (55.6%). Nonrandom allelic changes of 12q and 16q were revealed for the first time. In addition, loss of heterozygosity on chromosomal arms 1p (37.0%), 5q (44.4%), and 12p (44.4%) were also common in NPC. Multiple minimally deleted regions, 7-40 cM, were identified at 3p14-24.2, 11q21-23, 13q12-14, 13q31-32, 14q24-32, and 16q22-23. Frequent deletions of these minimally deleted regions implied the presence of tumor suppressor genes that may be involved in the development of NPC. Consistent loss of heterozygosity on 3p, 9p, and 14q in almost all tumors suggested that such changes are critical events in NPC tumorigenesis.

High frequency of promoter hypermethylation of RASSF1A in nasopharyngeal carcinoma.

We have investigated the genetic and epigenetic changes of a newly isolated tumor suppressor gene on 3p21.3, RASSF1A, in nasopharyngeal carcinoma (NPC). Four xenografts, four cell lines and 21 primary tumors were examined. Promoter hypermethylation of the 5'CpG island of RASSF1A was detected in 4 of 4 (100%) xenografts, in 3 of 4 (75%) cell lines, and in 14 of 21 (66.7%) primary tumors but not in the normal nasopharyngeal epithelia. Mutations were found in 2 of 21 (9.5%) primary tumors. In the cell lines and xenografts with extensive methylation, no RASSF1A gene expression was found. After treatment with 5'-aza-2'deoxycytidine, reexpression and demethylation of the RASSF1A gene were detected in a NPC cell line. These findings suggest that promoter hypermethylation may participate in the transcriptional inactivation of the RASSF1A gene in NPC. The high incidence of RASSF1A alterations suggest that it is the critical target gene on chromosome 3p21.3 involved in the development of NPC.

Taste intensities of ten vegetables commonly consumed in the Netherlands.

Bitterness has been suggested to be the main reason for the limited palatability of several vegetables. Vegetable acceptance has been associated with preparation method. However, the taste intensity of a variety of vegetables prepared by different methods has not been studied yet. The objective of this study is to assess the intensity of the five basic tastes and fattiness of ten vegetables commonly consumed in the Netherlands prepared by different methods using the modified Spectrum method. Intensities of sweetness, sourness, bitterness, umami, saltiness and fattiness were assessed for ten vegetables (cauliflower, broccoli, leek, carrot, onion, red bell pepper, French beans, tomato, cucumber and iceberg lettuce) by a panel (n=9) trained in a modified Spectrum method. Each vegetable was assessed prepared by different methods (raw, cooked, mashed and as a cold pressed juice). Spectrum based reference solutions were available with fixed reference points at 13.3mm (R1), 33.3mm (R2) and 66.7mm (R3) for each taste modality on a 100mm line scale. For saltiness, R1 and R3 differed (16.7mm and 56.7mm). Mean intensities of all taste modalities and fattiness for all vegetables were mostly below R1 (13.3mm). Significant differences (p<0.05) within vegetables between preparation methods were found. Sweetness was the most intensive taste, followed by sourness, bitterness, fattiness, umami and saltiness. In conclusion, all ten vegetables prepared by different methods showed low mean intensities of all taste modalities and fattiness. Preparation method affected taste and fattiness intensity and the effect differed by vegetable type.

Multicenter phase II trial of mitoxantrone in patients with advanced nasopharyngeal carcinoma in Southeast Asia: an Asian-Oceanian Clinical Oncology Association Group study.

PURPOSE: Patients with advanced nasopharyngeal carcinoma (NPC) have a high incidence of recurrence and often develop distant metastases despite local control. This prospective multicenter phase II trial was conducted to evaluate the safety and efficacy of Novantrone (mitoxantrone; Lederle Laboratories, Wayne, NJ) in the therapy of patients with advanced NPC. PATIENTS AND METHODS: One hundred eight patients with advanced NPC, namely, those with recurrent or persistent disease following primary radiotherapy, or newly diagnosed metastatic disease, were treated with mitoxantrone. Mitoxantrone was administered intravenously at an initial dose of 12 mg/m2 and repeated every 3 weeks, with dose escalation to a maximum of 14 mg/m2. The distribution of histologic subtypes was representative of NPC, with the majority being (61%) undifferentiated (or anaplastic) carcinoma. RESULTS: The overall response rate (complete response [CR] and partial response [PR]) was 25% (95% confidence interval, 17% to 33%). The median response duration, time to treatment failure, and survival duration were 140, 82, and 394 days, respectively. Histology (poorly differentiated squamous cell) was found to be the only important factor in predicting response (P = .04) based on a multivariate analysis of nine pretreatment characteristics. The major dose-limiting toxicity was leukopenia. The incidences of nausea/vomiting, alopecia, and stomatitis/mucositis were 34%, 6%, and 3%, respectively. None were severe. Two patients had asymptomatic, moderate Alexander-grade cardiotoxicity. CONCLUSION: This study represents a large, controlled multicenter trial of single-agent mitoxantrone in the treatment of advanced NPC. Mitoxantrone was well tolerated and produced an overall response rate comparable to that of other single-agent therapies used in the treatment of advanced head and neck cancer. Combination trials with mitoxantrone for advanced disease should be considered.

Concurrent chemotherapy-radiotherapy compared with radiotherapy alone in locoregionally advanced nasopharyngeal carcinoma: progression-free survival analysis of a phase III randomized trial.

PURPOSE: Nasopharyngeal carcinoma (NPC) is highly sensitive to both radiotherapy (RT) and chemotherapy. This randomized phase III trial compared concurrent cisplatin-RT (CRT) with RT alone in patients with locoregionally advanced NPC. PATIENTS AND METHODS: Patients with Ho's N2 or N3 stage or N1 stage with nodal size > or = 4 cm were randomized to receive cisplatin 40 mg/m(2) weekly up to 8 weeks concurrently with radical RT (CRT) or RT alone. The primary end point was progression-free survival (PFS). RESULTS: Three hundred fifty eligible patients were randomized. Baseline patient characteristics were comparable in both arms. There were significantly more toxicities, including mucositis, myelosuppression, and weight loss in the CRT arm. There were no treatment-related deaths in the CRT arm, and one patient died during treatment in the RT-alone arm. At a median follow-up of 2.71 years, the 2-year PFS was 76% in the CRT arm and 69% in the RT-alone arm (P =.10) with a hazards ratio of 1.367 (95% confidence interval [CI], 0.93 to 2.00). The treatment effect had a significant covariate interaction with tumor stage, and a subgroup analysis demonstrated a highly significant difference in favor of the CRT arm in Ho's stage T3 (P =.0075) with a hazards ratio of 2.328 (95% CI, 1.26 to 4.28). For T3 stage, the time to first distant failure was statistically significantly different in favor of the CRT arm (P =.016). CONCLUSION: Concurrent CRT is well tolerated in patients with advanced NPC in endemic areas. Although PFS was not significantly different between the concurrent CRT arm and the RT-alone arm in the overall comparison, PFS was significantly prolonged in patients with advanced tumor and node stages.

Increased incidence of tongue cancer after primary radiotherapy for nasopharyngeal carcinoma--the possibility of radiation carcinogenesis.

The aim of this study was to define the risk of tongue and other aerodigestive tract cancers developing after primary radiation therapy for nasopharyngeal carcinoma (NPC). A cohort of 903 patients with non-disseminated NPC given radical radiotherapy between 1984 and 1989 was studied for the incidence of tongue cancer and other malignancies during follow-up. A contemporary cohort of 87 patients with tongue cancer, without a history of NPC, was studied for demographic data, cigarette smoking and alcohol consumption habits. These were then compared with all the NPC patients and with the NPC patients who later developed tongue cancers. There was a significantly increased number of tongue cancers following radiotherapy for NPC. The risk of developing tongue cancer after radiotherapy for NPC was 0.13% per patient per year. There was no increase in the number of other malignancies. The association between NPC and tongue cancer was that of a non-random temporal sequence with tongue cancers following NPC but not in the reverse order. The demographic data and smoking and alcohol consumption history of the 7 NPC patients who subsequently developed tongue cancer were significantly different from the de novo tongue cancer patient population. The absence of common aetiological factors between NPC and tongue cancer and the non-random sequence of tongue cancers occurring after NPC suggests that these seven tongue cancers could be radiation induced. The estimated radiation dose received by the part of the tongue developing cancer was substantial and significantly higher than the dose to the cancer-free tongue. An increase of tongue cancers after radiotherapy for NPC is reported and arguments are made in support of the hypothesis that these were radiation-induced malignancies. We suggest a decrease in the volume of tongue included within the planning target volume of NPC in the absence of oropharyngeal and/or parapharyngeal infiltration. Awareness of the association should make early diagnosis of this likely radiation-induced cancer possible.