Seminal Vesicle Treatment for Localized Prostate Cancer Treated with External Beam Radiotherapy.

This study retrospectively reviewed data from men with localized prostate cancer treated with external beam radiotherapy (EBRT). We identified 359 men with localized prostate cancer treated with curative EBRT at the Cross Cancer Institute between 2010-2011. The volume of seminal vesicles (SVs) treated as well as dose values were extracted. These volumes were compared to gold standard contours drawn by a trained expert based on consensus European Society for Radiotherapy and Oncology (ESTRO) contouring guidelines. Patient and tumor characteristics were extracted for these patients. Memorial Sloan Kettering prostate cancer nomogram was used to assign a predicted risk of SV involvement for each patient based on baseline tumor characteristics. In patients with a predicted risk of SV involvement greater than 15% (n = 184), 86.5% (SD = 18.6) of the base of the SVs were treated with EBRT, compared to 66.7% (SD = 32.6) for patients with a predicted risk of SV involvement less than 15% (n = 175, p < 0.0001). Similarly, the mean percentage of proximal and total SV volumes treated with EBRT was 75.6% (SD = 24.4) and 68.7% (SD = 26.0) for patients with a predicted risk of SV involvement of greater than 15%, compared to 50.3% (SD = 31.0, p < 0.0001) and 41.0% (SD = 27.8, p < 0.0001) for patients with a risk of less than 15%. The results indicate that all parts of the SVs are more likely to be contoured in men with >15% risk of SV involvement than those with <15% risk. However, radiation oncologists still contour a high percentage of SVs in men with <15% risk of SV involvement, suggesting that there may be over-treatment of SVs that increases the risk of rectal or bladder toxicity.

Inhibitory effect of fucoidan on TNF-α-induced inflammation in human retinal pigment epithelium cells.

Sargassum horneri (S. horneri) is a brown seaweed that contains a fucose-rich sulfated polysaccharide called fucoidan and is known to possess beneficial bioactivities, such as anti-inflammatory, antiviral, antioxidative, and antitumoral effects. This study aimed to determine the anti-inflammatory effects of AB_SH (hydrothermal extracts from S. horneri) and its bioactive compound (fucoidan) against tumor necrosis factor alpha (TNF-α)-induced inflammation in human retinal pigment epithelial (RPE) cells. AB_SH did not exhibit any cytotoxicity, and it decreased the mRNA expression of interleukin (IL)-6 and IL-8 and the production of the cytokines IL-6 and TNF-α. It also suppressed the expression levels of phosphorylated nuclear factor kappa B (NF-κB) and mitogen-activated protein kinases (MAPKs), including c-Jun amino-terminal kinases (JNK), p38 protein kinases (p38), and extracellular signal-regulated kinase (ERK) proteins, suggesting that AB_SH inhibits activation of the NF-kB/MAPK signaling pathway. Since fucoidan was identified in the composition analysis of AB_SH, it was additionally shown to be required for its anti-inflammatory effects in TNF-α-stimulated human RPE cells. In line with the AB_SH results, fucoidan reduced the mRNA levels of IL-6, IL-1ß, and IL-8 and production of the cytokines IL-6, TNF-α, and IL-8 through the downregulation of the NF-kB/MAPK signaling pathway in a dose-dependent manner. Collectively, the ability of AB_SH from S. horneri hydrothermal extracts to reduce inflammation indicates that it may be a good functional ingredient for managing ocular disorders.

National Survey of Sharps Injuries Incidence Amongst Healthcare Workers in the United States.

Purpose: Reporting sharps injuries is crucial for healthcare worker occupational safety. However, these incidents are often underreported, thus posing potentially dangerous working environments. Previous small and limited studies have quantified this underreporting in specific groups of healthcare workers. This study aims to expand on these studies by further quantifying sharps injury incidences through a national study, thus better understanding healthcare reporting behaviors and the reasons for underreporting. Patients and Methods: This is a national, multi-center, cross-sectional study conducted via an online anonymous survey distributed through email among United States attending physicians, fellows, residents, medical students, and nurses of all specialties (ie, surgery, medicine, pediatrics). Data analysis used descriptive statistics and regressive modeling with significance defined as p<0.05. Results: Of over 3000 surveys emailed, 460 (15.3%) healthcare workers responded. The most vulnerable cohort to report sharps injuries were medical students (0.87 injuries per year ±0.69, n=92) and Postgraduate Year (PGY) 1 (0.67±0.81, n=71), PGY2 (0.86±-0.82, n=48), and PGY3 (0.92±0.8, n=45) resident physicians. Healthcare workers in surgical fields reported significantly higher likelihoods (odds ratio=4.61, p<0.001, 95% confidence interval 2.83-7.26) of sharps injuries. Medical students reported sharps injuries the least (40%) and nurses reported sharps injuries the most frequently (71%). The three most common reasons for not reporting sharps injuries included (1) healthcare workers perceiving low infection risk based on patient medical history, (2) fear of peer perception, and (3) belief of lack of reporting utility or that reporting is inconsequential. Conclusion: Medical students and physicians early in training, especially those in surgical fields, are more vulnerable to sharps injuries, but are less likely to report, while nurses are the most likely to report. Dedicated sharps training, education to reduce stigma around injury, and implementing a simplified reporting process may help encourage reporting as well as consistency in reporting, leading to improved workplace safety.

Tumor Volume Predicts for Pathologic Complete Response in Rectal Cancer Patients Treated With Neoadjuvant Chemoradiation.

OBJECTIVES: Nonoperative management (NOM) of locally advanced rectal cancer is an emerging approach allowing patients to preserve their anal sphincter. Identifying clinical factors associated with pathologic complete response (pCR) is essential for physicians and patients considering NOM. MATERIALS AND METHODS: In total, 412 locally advanced rectal cancer patients were included in this retrospective analysis. Tumor volumes were derived from pretreatment MRI. Clinical parameters such as tumor volume, stage, and location were analyzed by univariate and multivariate analysis, against pCR. A receiver operator characteristic curve was generated to identify a tumor volume cut-off with the highest clinically relevant Youden index for predicting pCR. RESULTS: Seventy-five of 412 patients (18%) achieved pCR. A tumor volume threshold of 37.3 cm 3 was identified as predictive for pCR. On regression analysis, a tumor volume >37.3 cm 3 was associated with a greater than 78% probability of not achieving pCR. On multivariate analysis, a GTV <37.3 cm 3 [odds ratio (OR)=3.7, P <0.0001] was significantly associated with an increased pCR rate, whereas tumor length > 4.85 cm was associated with pCR on univariate (OR=3.03, P <0.01) but not on multivariate analysis (OR=1.45, P =0.261). Other clinical parameters did not impact pCR rates. CONCLUSIONS: A tumor volume threshold of 37.3 cm 3 was identified as predictive for pCR in locally advanced rectal cancer patients receiving neoadjuvant chemoradiation. Tumors above this volume threshold corresponded to a greater than 78% probability of not achieving pCR. This information will be helpful at diagnosis for clinicians who are considering potential candidates for NOM.

More Is Not Better When It Comes to Treating Rectal Cancer With Multimodal Chemoradiation Beyond the Standard Radiation Dose of 5040 cGy.

BACKGROUND: Radiation dose schedules for neoadjuvant chemoradiation for rectal cancers differ, with the most common dose schedule using 5040 cGy in 28 fractions. OBJECTIVES: The aim of this retrospective study was to assess the benefit of higher radiation doses beyond 5040 cGy in the context of pathological response and follow-up events. SETTING: The database from a provincial tertiary cancer center in Canada was the source of information for this study. PATIENTS: Included in this study were 508 consecutive patients with rectal cancer with locally advanced disease (clinical T3/T4 or N1/N2) who received neoadjuvant chemoradiation followed by surgery. Of the 508 patients, 281 received the standard radiation dose of 4500 to 5040 cGy and 227 received a dose >5040 cGy. MAIN OUTCOME MEASURE: The postsurgical pathology, late toxicities, and follow-up outcomes were analyzed. The outcomes were evaluated in relation to the dose of radiation received. RESULTS: Data regarding the clinical outcomes were comparable between the 4500 to 5040 cGy and >5040 cGy radiation groups with pathological complete response rates of 20.9% and 15.4% (p = 0.104); distant recurrence rates of 17.4% and 19.4% (p = 0.36); local recurrence rates of 3.2% and 3.5% (p = 0.36); and the median overall survival rates of 61 and 60.5 months (p = 0.8). No statistically significant correlation of improvement in outcomes was noted with radiation doses beyond 5040 cGy. LIMITATIONS: This is a retrospective study. CONCLUSION: Our study showed that dose escalation beyond the standard dose of 4500 to 5040cGy failed to achieve meaningful clinical outcomes. See Video Abstract at http://links.lww.com/DCR/B633. MS NO ES MEJOR CUANDO SE TRATA DE TRATAR EL CNCER DE RECTO CON QUIMIORRADIACIN MULTIMODAL MS ALL DE LA DOSIS DE RADIACIN ESTNDAR DE CGY: ANTECEDENTES:En neoadyuvancia de cáncer rectal es posible encontrar muchas variaciones, en radioterapia la dosis más común que usa 5040 cGy en 28 fracciones.OBJETIVOS:El objetivo de este estudio retrospectivo fue evaluar el beneficio de dosis de radiación más altas más allá de 5040cGy en el contexto de la respuesta patológica y en su seguimiento.AJUSTE:Base de datos de un centro de cáncer terciario provincial en Canadá.PACIENTES:Se incluyeron en este estudio quinientos ocho pacientes consecutivos con cáncer de recto y enfermedad localmente avanzada (clínica T3 / T4 o N1 / N2) que recibieron quimiorradiación neoadyuvante seguida de cirugía. De los 508 pacientes, 281 recibieron la dosis de radiación estándar de 4500-5040 cGy y 227 recibieron una dosis > 5040 cGy.PRINCIPAL MEDIDA DE RESULTADO:Se analizo evolucion posquirúrgica, toxicidad tardía y seguimiento. Los resultados se evaluaron en relación con la dosis de radiación recibida.RESULTADOS:Los datos con respecto a los resultados clínicos fueron comparables entre los grupos de radiación de 4500-5040 cGy y> 5040 cGy con tasas de respuesta patológica completa de 20,9% y 15,4% respectivamente (p = 0,104); tasas de recurrencia a distancia de 17,4% y 19,4%, respectivamente (p = 0,36); tasas de recurrencia local de 3,2% y 3,5%, respectivamente (p = 0,36); y la mediana de las tasas de supervivencia global de 61 y 60,5 meses, respectivamente (p = 0,8). No se observó una correlación estadísticamente significativa de mejoría en los resultados con dosis de radiación superiores a 5040 cGy.LIMITACIONES:Este es un estudio retrospectivo.CONCLUSIONES:Nuestro estudio mostró que el aumento de la dosis más allá de la dosis estándar de 4500-5040cGy no logró resultados clínicos significativos. Consulte Video Resumen en http://links.lww.com/DCR/B633. (Traducción-Dr. Gunther Bocic).

Time domain principal component analysis for rapid, real-time 2D MRI reconstruction from undersampled data.

PURPOSE: A rapid real-time 2D accelerated method was developed for magnetic resonance imaging (MRI) using principal component analysis (PCA) in the temporal domain. This method employs a moving window of previous dynamic frames to reconstruct the current, real-time frame within this window. This technique could be particularly useful in real-time tracking applications such as in MR-guided radiotherapy, where low latency real-time reconstructions are essential. METHODS: The method was tested retrospectively on 15 fully-sampled data sets of lung patient data acquired on a 3T Philips Achieva system. High frequency data are incoherently undersampled, while the central low-frequency data are always acquired to characterize the temporal fluctuations through PCA. The undersampling pattern is derived in such a way that all of k-space is acquired within a pre-determined number of frames. The missing data in the current frame are then filled in by fitting the temporal characterizations to the acquired undersampled data, using a pre-determined number of PCs. A subset of six patients was used to test the contour ability of the images. Various accelerations between 3x and 8x were tested along with the optimal number of PCs for fitting. A comparison was also performed with previous work from our group proposed by Dietz et al. as well as with a standard low resolution acquisition. In order to determine how the method would perform at lower signal to noise ratio (SNR), noise levels of 2×, 4×, and 6× were added to the 3T data. Metrics such as normalised mean square error and Dice coefficient were used to measure the reconstruction image quality and contour ability. RESULTS: The proposed method demonstrated good temporal robustness as consistent metrics were detected for the duration of the imaging session. It was found that the optimal number of PCs for temporal fitting was dependent on the acceleration rate. For the data tested, five PCs were found to be optimal at the acceleration rates of 3× and 4×. This number decreases to three at accelerations of 5× and 6× and further decreases to two at an acceleration rate of 8×, likely due to greater instability with fewer acquired data points. The use of too many PCs for fitting increased the chances of noisy reconstruction which affected contourability. CONCLUSIONS: The proposed 2D real-time MR acceleration method demonstrated greater robustness in the metrics over time when compared with previous real-time PCA methods using metrics such as normalised mean squared error, peak SNR and structural similarity up to an acceleration of 8x. Improved temporal robustness of image structure contourability and accurate definition was also demonstrated using several metrics including the Dice coefficient. Reconstruction of raw acquired data can be performed at approximately 50 ms per frame using an Intel core i5 CPU. The method has the advantage of being very flexible in terms of hardware requirements as it can operate successfully on a single coil channel and does not require specialized computing power to implement in real-time.

Brevilactibacter coleopterorum sp. nov., isolated from the intestine of the dark diving beetle Hydrophilus acuminatus, and Weissella coleopterorum sp. nov., isolated from the intestine of the diving beetle Cybister lewisianus.

A polyphasic taxonomic approach was used to characterize two novel bacterial strains, designated as HDW11T and HDW19T, isolated from intestine samples of the dark diving beetle Hydrophilus acuminatus and the diving beetle Cybister lewisianus, respectively. Both isolates were Gram-stain-positive, facultatively anaerobic and non-motile. Strain HDW11T grew optimally at 30 °C, pH 8 and in the presence of 1% (w/v) NaCl. Strain HDW19T grew optimally at 25 °C, pH 7 and in the presence of 0.3% (w/v) NaCl. Phylogenetic analysis based on 16S rRNA gene sequences and genome sequences revealed that strain HDW11T is a member of the genus Brevilactibacter and is closely related to Brevilactibacter flavus VG341T [with 97.9% 16S rRNA sequence identity and 79.1% average nucleotide identity (ANI)], and that strain HDW19T belongs to the genus Weissella and is closely related to W. koreensis KCTC 3621T (with 98.9% 16S rRNA sequence identity and 79.5% ANI). The major cellular fatty acids of strains HDW11T and HDW19T were C18:1 ω9c and anteiso-C15:0, respectively. The sole respiratory quinone of strain HDW11T was MK-9 (H4). The major polar lipid components of strain HDW11T were diphosphatidylglycerol and phosphatidylglycerol, and the major polar lipid component of strain HDW19T was diphosphatidylglycerol. The genomic DNA G+C content of strains HDW11T and HDW19T were 72.1 and 37.2 mol%, respectively. The results of phylogenetic, phenotypic, chemotaxonomic and genotypic analyses suggest that strain HDW11T represents a novel species within the genus Brevilactibacter, and that strain HDW19T represents a novel species within the genus Weissella. We propose the name Brevilactibacter coleopterorum sp. nov. for strain HDW11T (=KACC 21335T=KCTC 49320T=JCM 33680T) and the name Weissella coleopterorum for strain HDW19T (=KACC 21347T=KCTC 43114T=JCM 33684T).

Leucobacter coleopterorum sp. nov., Leucobacter insecticola sp. nov., and Leucobacter viscericola sp. nov., isolated from the intestine of the diving beetles, Cybister brevis and Cybister lewisianus, and emended description of the genus Leucobacter.

Three novel bacterial strains, HDW9AT, HDW9BT, and HDW9CT, isolated from the intestine of the diving beetles Cybister lewisianus and Cybister brevis, were characterized as three novel species using a polyphasic approach. The isolates were Gram-staining-positive, strictly aerobic, non-motile, and rod-shaped. They grew optimally at 30°C (pH 7) in the presence of 0.5% (wt/vol) NaCl. Phylogenetic analysis based on the 16S rRNA gene sequences revealed that they belong to the genus Leucobacter and are closely related to L. denitrificans M1T8B10T (98.4-98.7% sequence similarity). Average nucleotide identity (ANI) values among the isolates were 76.4-84.1%. ANI values for the isolates and the closest taxonomic species, L. denitrificans KACC 14055T, were 72.3-73.1%. The isolates showed ANI values of < 76.5% with all analyzable Leucobacter strains in the EzBioCloud database. The genomic DNA G + C content of the isolates was 60.3-62.5%. The polar lipid components were phosphatidylglycerol, diphosphatidylglycerol, and other unidentified glycolipids, phospholipids, and lipids. The major cellular fatty acids were anteiso-C15:0, iso-C16:0, and anteiso-C17:0. MK-10 was the major respiratory quinone, and MK-7 and MK-11 were the minor respiratory quinones. The whole-cell sugar components of the isolates were ribose, glucose, galactose, and mannose. The isolates harbored L-2,4-diaminobutyric acid, L-serine, L-lysine, L-aspartic acid, glycine, and D-glutamic acid within the cell wall peptidoglycan. Based on phylogenetic, phenotypic, chemotaxonomic, and genotypic analyses, strains HDW9AT, HDW9BT, and HDW9CT represent three novel species within the genus Leucobacter. We propose the name Leucobacter coleopterorum sp. nov. for strain HDW9AT (= KACC 21331T = KCTC 49317T = JCM 33667T), the name Leucobacter insecticola sp. nov. for strain HDW9BT (= KACC 21332T = KCTC 49318T = JCM 33668T), and the name Leucobacter viscericola sp. nov. for strain HDW9CT (= KACC 21333T = KCTC 49319T = JCM 33669T).

Tessaracoccus coleopterorum sp. nov., isolated from the intestine of the dark diving beetle, Hydrophilus acuminatus.

A polyphasic taxonomic approach was used to characterize a novel bacterium, designated as strain HDW20T, isolated from the intestine of the dark diving beetle Hydrophilus acuminatus. The isolate was Gram-stain-positive, facultatively anaerobic, non-motile, coccus-shaped, and formed pale orange colonies. Phylogenetic analysis based on 16S rRNA gene sequences and genome sequences showed that the isolate belonged to the genus Tessaracoccus in the phylum Actinobacteria and was closely related to T. flavescens SST-39T, T. defluvii JCM 17540T, and T. aquimaris NSG39T, with the highest 16S rRNA gene sequence similarity of 98.5 % and a highest average nucleotide identity (ANI) value of 80.6 %. The major cellular fatty acids were C18 : 1 ω9c and anteiso-C15 : 0. The main respiratory quinone was MK-9 (H4). The major polar lipid components were phosphatidylglycerol and diphosphatidylglycerol. The genomic DNA G+C content was 69.0 %. The isolate contains ʟʟ-diaminopimelic acid, ʟ-alanine, and ʟ-lysine as amino acid components, and ribose, glucose, and galactose as sugar components of the cell wall peptidoglycan. The results of phylogenetic, phenotypic, chemotaxonomic, and genotypic analyses suggested that strain HDW20T represents a novel species within the genus Tessaracoccus. We propose the name Tessaracoccus coleopterorum sp. nov. The type strain is HDW20T (=KACC 21348T=KCTC 49324T=JCM 33674T).

Dosimetric Parameters Predicting Late Small Bowel Toxicity in Patients With Rectal Cancer Receiving Neoadjuvant Chemoradiation.

PURPOSE: The aim of this study was to identify dosimetric parameters that predict late small bowel (SB) toxicity after neoadjuvant long course chemoradiation (CRT) for rectal cancer. METHODS AND MATERIALS: Four hundred eighty-six consecutive patients with locally advanced rectal cancers (clinical T3/T4 or N1/N2) who received CRT followed by surgery and had dosimetric data available for analysis were included in this study. The dose-volume relationship between small bowel irradiation and late small bowel toxicity was evaluated and a mathematical model to predict for late SB toxicity was derived. RESULTS: Among the 486 patients with a median follow-up of 60 months from completion of radiation, 36 (7.4%) patients experienced ≥ grade 2 and 21 (4.3%) developed ≥ grade 3 late SB toxicity. A statistically significant association between the development of grade ≥3 late small bowel toxicity and the volume of small bowel irradiated was found at each dose level from 5 to 40 Gy (P < .001 for all dose volumes) in 5 Gy intervals. The average SB volume for patients who experienced grade ≥2 SB toxicity was 2149.9 cm3 and the average SB volume for patients who experienced grade ≥3 SB toxicity was 2179.9 cm3. The predicted V30 for a 5% risk for grade ≥2 SB toxicity was 101.5 cm3 and for grade ≥3 SB toxicity was 201.5 cm3. The volume of small bowel receiving at least 30 Gy (V30) was most strongly associated with grade ≥3 SB toxicity. CONCLUSIONS: This study demonstrates the significant dose-volume relationship between volume of small bowel receiving 30 Gy (V30 Gy) and late grade ≥3 SB toxicity. When planning CRT for patients with rectal cancer, restricting V30 to <200 cm3 will be a useful guideline to minimize the 5 year grade ≥3 late SB toxicity to <5%.

Two-Ply Carbon Nanotube Fiber-Typed Enzymatic Biofuel Cell Implanted in Mice.

Implantable devices have emerged as a promising industry. It is inevitable that these devices will require a power source to operate in vivo. Thus, to power implantable medical devices, biofuel cells (BFCs) that generate electricity using glucose without an external power supply have been considered. Although implantable BFCs have been developed for application in vivo, they are limited by their bulky electrodes and low power density. In the present study, we attempted to apply to living mice an implantable enzymatic BFC (EBFC) that was previously reported to be a high-power EBFC comprising carbon nanotube yarn electrodes. To improve their mechanical properties and for convenient implantation, the electrodes were coated with Nafion and twisted into a micro-sized, two-ply, one-body system. When the two-ply EBFC system was implanted in the abdominal cavity of mice, it provided a high-power density of 0.3 mW/cm2. The two-ply EBFC system was injected through a needle using a syringe without surgery and the inflammatory response in vivo initially induced by the injection of the EBFC system was attenuated after 7 days, indicating the biocompatibility of the system in vivo.

Real-Time Lung Tumor Tracking Using a CUDA Enabled Nonrigid Registration Algorithm for MRI.

OBJECTIVE: This study intends to develop an accurate, real-time tumor tracking algorithm for the automated radiation therapy for cancer treatment using Graphics Processing Unit (GPU) computing. Although a previous moving mesh based tumor tracking approach has been shown to be successful in delineating the tumor regions from a sequence of magnetic resonance image, the algorithm is computationally intensive and its computation time on standard Central Processing Unit (CPU) processors is too slow to be used clinically especially for automated radiation therapy system. METHOD: A re-implementation of the algorithm on a low-cost parallel GPU-based computing platform is utilized to accelerate this computation at a speed that is amicable to clinical usages. Several components in the registration algorithm such as the computation of similarity metric are inherently parallel which fits well with the GPU parallel processing capabilities. Solving a partial differential equation numerically to generate the mesh deformation is one of the computationally intensive components which has been accelerated by utilizing a much faster shared memory on the GPU. RESULTS: Implemented on an NVIDIA Tesla K40c GPU, the proposed approach yielded a computational acceleration improvement of over 5 times its implementation on a CPU. The proposed approach yielded an average Dice score of 0.87 evaluated over 600 images acquired from six patients. CONCLUSION: This study demonstrated that the GPU computing approach can be used to accelerate tumor tracking for automated radiation therapy for mobile lung tumors. Clinical Impact: Accurately tracking mobile tumor boundaries in real-time is important to automate radiation therapy and the proposed study offers an excellent option for fast tumor region tracking for cancer treatment.

Single patient convolutional neural networks for real-time MR reconstruction: coherent low-resolution versus incoherent undersampling.

Accelerated MRI involves undersampling k-space, creating unwanted artifacts when reconstructing the data. While the strategy of incoherent k-space acquisition is proven for techniques such as compressed sensing, it may not be optimal for all techniques. This study compares the use of coherent low-resolution (coherent-LR) and incoherent undersampling phase-encoding for real-time 3D CNN image reconstruction. Data were acquired with our 3 T Philips Achieva system. A retrospective analysis was performed on six non-small cell lung cancer patients who received dynamic acquisitions consisting of 650 free breathing images using a bSSFP sequence. We retrospectively undersampled the data by 5x and 10x acceleration using the two phase-encoding schemes. A quantitative analysis was conducted evaluating the tumor segmentations from the CNN reconstructed data using the Dice coefficient (DC) and centroid displacement. The reconstruction noise was evaluated using the structural similarity index (SSIM). Furthermore, we qualitatively investigated the CNN reconstruction using prospectively undersampled data, where the fully sampled training data set is acquired separately from the accelerated undersampled data. The patient averaged DC, centroid displacement, and SSIM for the tumor segmentation at 5x and 10x was superior using coherent low-resolution undersampling. Furthermore, the patient-specific CNN can be trained in under 6 h and the reconstruction time was 54 ms per image. Both the incoherent and coherent-LR prospective CNN reconstructions yielded qualitatively acceptable images; however, the coherent-LR reconstruction appeared superior to the incoherent reconstruction. We have demonstrated that coherent-LR undersampling for real-time CNN image reconstruction performs quantitatively better for the retrospective case of lung tumor segmentation, and qualitatively better for the prospective case. The tumor segmentation mean DC increased for all six patients at 5x acceleration and the temporal (dynamic) variance of the segmentation was reduced. The reconstruction speed achieved for our current implementation was 54 ms, providing an acceptable frame rate for real-time on-the-fly MR imaging.

Single patient convolutional neural networks for real-time MR reconstruction: a proof of concept application in lung tumor segmentation for adaptive radiotherapy.

Investigate 3D (spatial and temporal) convolutional neural networks (CNNs) for real-time on-the-fly magnetic resonance imaging (MRI) reconstruction. In particular, we investigated the applicability of training CNNs on a patient-by-patient basis for the purpose of lung tumor segmentation. Data were acquired with our 3 T Philips Achieva system. A retrospective analysis was performed on six non-small cell lung cancer patients who received fully sampled dynamic acquisitions consisting of 650 free breathing images using a bSSFP sequence. We retrospectively undersampled the six patient's data by 5× and 10× acceleration. The retrospective data was used to quantitatively compare the CNN reconstruction to gold truth data via the Dice coefficient (DC) and centroid displacement to compare the tumor segmentations. Reconstruction noise was investigated using the normalized mean square error (NMSE). We further validated the technique using prospectively undersampled data from a volunteer and motion phantom. The retrospectively undersampled data at 5× and 10× acceleration was reconstructed using patient specific trained CNNs. The patient average DCs for the tumor segmentation at 5× and 10× acceleration were 0.94 and 0.92, respectively. These DC values are greater than the inter- and intra-observer segmentations acquired by radiation oncologist experts as reported in a previous study of ours. Furthermore, the patient specific CNN can be trained in under 6 h and the reconstruction time was 65 ms per image. The prospectively undersampled CNN reconstruction data yielded qualitatively acceptable images. We have shown that 3D CNNs can be used for real-time on-the-fly dynamic image reconstruction utilizing both spatial and temporal data in this proof of concept study. We evaluated the technique using six retrospectively undersampled lung cancer patient data sets, as well as prospectively undersampled data acquired from a volunteer and motion phantom. The reconstruction speed achieved for our current implementation was 65 ms per image.

Tracking tumor boundary using point correspondence for adaptive radio therapy.

BACKGROUND AND OBJECTIVE: Tracking mobile tumor regions during the treatment is a crucial part of image-guided radiation therapy because of two main reasons which negatively affect the treatment process: (1) a tiny error will lead to some healthy tissues being irradiated; and (2) some cancerous cells may survive if the beam is not accurately positioned as it may not cover the entire cancerous region. However, tracking or delineation of such a tumor region from magnetic resonance imaging (MRI) is challenging due to photometric similarities of the region of interest and surrounding area as well as the influence of motion in the organs. The purpose of this work is to develop an approach to track the center and boundary of tumor region by auto-contouring the region of interest in moving organs for radiotherapy. METHODS: We utilize a nonrigid registration method as well as a publicly available RealTITracker algorithm for MRI to delineate and track tumor regions from a sequence of MRI images. The location and shape of the tumor region in the MRI image sequence varies over time due to breathing. We investigate two approaches: the first one uses manual segmentation of the first frame during the pretreatment stage; and the second one utilizes manual segmentation of all the frames during the pretreatment stage. RESULTS: We evaluated the proposed approaches over a sequence of 600 images acquired from 6 patients. The method that utilizes all the frames in the pretreatment stage with moving mesh based registration yielded the best performance with an average Dice Score of 0.89 ±â€¯0.04 and Hausdorff Distance of 3.38 ±â€¯0.10 mm. CONCLUSIONS: This study demonstrates a promising boundary tracking tool for delineating the tumor region that can deal with respiratory movement and the constraints of adaptive radiation therapy.

Peri-anal surface dose in anal canal VMAT radiotherapy.

INTRODUCTION: Skin bolus may routinely be used in the perineum to build up the surface dose in the treatment of anal cancer (ACC); this may contribute to significant acute skin toxicity. Skin bolus may not be needed with the introduction of modern radiotherapy techniques if these planning techniques would achieve adequate surface dose. Our study is to ascertain if appropriate skin dose can be achieved without the use of bolus when VMAT is used in the treatment of ACC. METHODS: The study includes 10 ACC patients treated with VMAT radiotherapy. Optically stimulated luminescence dosimeters (OSLD) are used to evaluate whether the calculated dose for the VMAT planning technique (VMAT-PT) accurately predicted the dose delivered to peri-anal target region without bolus. The OSLD recorded the dose at the anal verge or at the lower most extent of the tumour for each patient over two fractions. The OSLD was read after each of the two fractions, and the average value was reported. The mean dose over a volume centred on the anal marker was calculated in the treatment planning system (TPS). RESULTS: The mean TPS-calculated dose was 186.1 cGy. The mean of the OSLD-measured doses was 205.7 cGy for a single fraction. The mean of the measured doses was 10.6% higher than the mean of the calculated doses. CONCLUSIONS: The calculated dose for the VMAT-PT consistently under-predicted the dose delivered to the peri-anal target region without bolus. Routine use of skin bolus could be avoided with VMAT-PT when the patient is treated in a supine position.

Evaluating performance of a user-trained MR lung tumor autocontouring algorithm in the context of intra- and interobserver variations.

PURPOSE: Real-time tracking of lung tumors using magnetic resonance imaging (MRI) has been proposed as a potential strategy to mitigate the ill-effects of breathing motion in radiation therapy. Several autocontouring methods have been evaluated against a "gold standard" of a single human expert user. However, contours drawn by experts have inherent intra- and interobserver variations. In this study, we aim to evaluate our user-trained autocontouring algorithm with manually drawn contours from multiple expert users, and to contextualize the accuracy of these autocontours within intra- and interobserver variations. METHODS: Six nonsmall cell lung cancer patients were recruited, with institutional ethics approval. Patients were imaged with a clinical 3 T Philips MR scanner using a dynamic 2D balanced SSFP sequence under free breathing. Three radiation oncology experts, each in two separate sessions, contoured 130 dynamic images for each patient. For autocontouring, the first 30 images were used for algorithm training, and the remaining 100 images were autocontoured and evaluated. Autocontours were compared against manual contours in terms of Dice's coefficient (DC) and Hausdorff distances (dH ). Intra- and interobserver variations of the manual contours were also evaluated. RESULTS: When compared with the manual contours of the expert user who trained it, the algorithm generates autocontours whose evaluation metrics (same session: DC = 0.90(0.03), dH  = 3.8(1.6) mm; different session DC = 0.88(0.04), dH  = 4.3(1.5) mm) are similar to or better than intraobserver variations (DC = 0.88(0.04), and dH  = 4.3(1.7) mm) between two sessions. The algorithm's autocontours are also compared to the manual contours from different expert users with evaluation metrics (DC = 0.87(0.04), dH  = 4.8(1.7) mm) similar to interobserver variations (DC = 0.87(0.04), dH  = 4.7(1.6) mm). CONCLUSIONS: Our autocontouring algorithm delineates tumor contours (<20 ms per contour), in dynamic MRI of lung, that are comparable to multiple human experts (several seconds per contour), but at a much faster speed. At the same time, the agreement between autocontours and manual contours is comparable to the intra- and interobserver variations. This algorithm may be a key component of the real time tumor tracking workflow for our hybrid Linac-MR device in the future.

Kushneria konosiri sp. nov., isolated from the Korean salt-fermented seafood Daemi-jeot.

A halophilic bacterial strain, X49T, was isolated from the Korean traditional salt-fermented seafood Daemi-jeot. X49T was an obligately aerobic, Gram-stain-negative, motile, oval or rod-shaped (0.5-1.0×1.2-3.2 µm) bacterium. After 2 days of growth, colonies on Marine agar medium were orange and circular with entire margins. X49T growth was detected at 10-37 °C and pH 4.5-8.5 in the presence of 0-26 % (w/v) NaCl. The 16S rRNA gene sequence of strain X49T was most similar to that of the type strain of Kushneria marisflavi SW32T and shared a sequence similarity of 94.7-98.6 % with type strains of species of the genus Kushneria. The predominant fatty acids were C16 : 0, C18 : 1ω7c and C12 : 0 3OH. The major isoprenoid quinone was Q9 (93 %), and minor quinones were Q8 (4 %) and Q10 (3 %). The polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine and phosphatidylserine, two unidentified aminolipids, two unidentified phospholipids and two unidentified lipids. The genomic DNA G+C content was 59.1 mol%. The level of the ANI value between strain X49T and K. marisflavi SW32T, the most closely related species of the genus Kushneria, was 89.32 %. Based on the low ANI value, strain X49T and its reference strains represent genotypically distinct species. Based on this polyphasic taxonomic analysis, strain X49T represents a novel species of the genus Kushneria. The name Kushneria konosiri sp. nov. is proposed and the type strain is X49T (=KACC 14623T=JCM 16805T).

Real-time dynamic MR image reconstruction using compressed sensing and principal component analysis (CS-PCA): Demonstration in lung tumor tracking.

PURPOSE: This work presents a real-time dynamic image reconstruction technique, which combines compressed sensing and principal component analysis (CS-PCA), to achieve real-time adaptive radiotherapy with the use of a linac-magnetic resonance imaging system. METHODS: Six retrospective fully sampled dynamic data sets of patients diagnosed with non-small-cell lung cancer were used to investigate the CS-PCA algorithm. Using a database of fully sampled k-space, principal components (PC's) were calculated to aid in the reconstruction of undersampled images. Missing k-space data were calculated by projecting the current undersampled k-space data onto the PC's to generate the corresponding PC weights. The weighted PC's were summed together, and the missing k-space was iteratively updated. To gain insight into how the reconstruction might proceed at lower fields, 6× noise was added to the 3T data to investigate how the algorithm handles noisy data. Acceleration factors ranging from 2 to 10× were investigated using CS-PCA and Split Bregman CS for comparison. Metrics to determine the reconstruction quality included the normalized mean square error (NMSE), as well as the dice coefficients (DC) and centroid displacement of the tumor segmentations. RESULTS: Our results demonstrate that CS-PCA performed superior than CS alone. The CS-PCA patient averaged DC for 3T and 6× noise added data remained above 0.9 for acceleration factors up to 10×. The patient averaged NMSE gradually increased with increasing acceleration; however, it remained below 0.06 up to an acceleration factor of 10× for both 3T and 6× noise added data. The CS-PCA reconstruction speed ranged from 5 to 20 ms (Intel i7-4710HQ CPU @ 2.5 GHz), depending on the chosen parameters. CONCLUSIONS: A real-time reconstruction technique was developed for adaptive radiotherapy using a Linac-MRI system. Our CS-PCA algorithm can achieve tumor contours with DC greater than 0.9 and NMSE less than 0.06 at acceleration factors of up to, and including, 10×. The reconstruction speed for the Split Bregman CS ranged from 200 to 260 ms, whereas the CS-PCA reconstruction speed ranged from 5 to 20 ms implemented using nonoptimized MATLAB code.

Sliding window prior data assisted compressed sensing for MRI tracking of lung tumors.

PURPOSE: Hybrid magnetic resonance imaging and radiation therapy devices are capable of imaging in real-time to track intrafractional lung tumor motion during radiotherapy. Highly accelerated magnetic resonance (MR) imaging methods can potentially reduce system delay time and/or improves imaging spatial resolution, and provide flexibility in imaging parameters. Prior Data Assisted Compressed Sensing (PDACS) has previously been proposed as an acceleration method that combines the advantages of 2D compressed sensing and the KEYHOLE view-sharing technique. However, as PDACS relies on prior data acquired at the beginning of a dynamic imaging sequence, decline in image quality occurs for longer duration scans due to drifts in MR signal. Novel sliding window-based techniques for refreshing prior data are proposed as a solution to this problem. METHODS: MR acceleration is performed by retrospective removal of data from the fully sampled sets. Six patients with lung tumors are scanned with a clinical 3 T MRI using a balanced steady-state free precession (bSSFP) sequence for 3 min at approximately 4 frames per second, for a total of 650 dynamics. A series of distinct pseudo-random patterns of partial k-space acquisition is generated such that, when combined with other dynamics within a sliding window of 100 dynamics, covers the entire k-space. The prior data in the sliding window are continuously refreshed to reduce the impact of MR signal drifts. We intended to demonstrate two different ways to utilize the sliding window data: a simple averaging method and a navigator-based method. These two sliding window methods are quantitatively compared against the original PDACS method using three metrics: artifact power, centroid displacement error, and Dice's coefficient. The study is repeated with pseudo 0.5 T images by adding complex, normally distributed noise with a standard deviation that reduces image SNR, relative to original 3 T images, by a factor of 6. RESULTS: Without sliding window implemented, PDACS-reconstructed dynamic datasets showed progressive increases in image artifact power as the 3 min scan progresses. With sliding windows implemented, this increase in artifact power is eliminated. Near the end of a 3 min scan at 3 T SNR and 5× acceleration, implementation of an averaging (navigator) sliding window method improves our metrics by the following ways: artifact power decreases from 0.065 without sliding window to 0.030 (0.031), centroid error decreases from 2.64 to 1.41 mm (1.28 mm), and Dice coefficient agreement increases from 0.860 to 0.912 (0.915). At pseudo 0.5 T SNR, the improvements in metrics are as follows: artifact power decreases from 0.110 without sliding window to 0.0897 (0.0985), centroid error decreases from 2.92 mm to 1.36 mm (1.32 mm), and Dice coefficient agreements increases from 0.851 to 0.894 (0.896). CONCLUSIONS: In this work we demonstrated the negative impact of slow changes in MR signal for longer duration PDACS dynamic scans, namely increases in image artifact power and reductions of tumor tracking accuracy. We have also demonstrated sliding window implementations (i.e., refreshing of prior data) of PDACS are effective solutions to this problem at both 3 T and simulated 0.5 T bSSFP images.