QPOs: Einstein's gravity non-linear resonances

There is strong evidence that the observed kHz Quasi Periodic Oscillations (QPOs) in the X-ray flux of neutron star and black hole sources in LMXRBs are linked to Einstein's General Relativity. Abramowicz&Klu\'zniak (2001) suggested a non-linear resonance model to explain the QPOs origin: here we summarize their idea and the development of a mathematical toy-model which begins to throw light on the nature of Einstein's gravity non-linear oscillations.Comment: Proceeding of the Einstein's Legacy, Munich 200

Review of MR-Guided Radiotherapy for Esophageal Cancer

In this review, we outline the potential benefits and the future role of MRI and MR-guided radiotherapy (MRgRT) in the management of esophageal cancer. Although not currently used in most clinical practice settings, MRI is a useful non-invasive imaging modality that provides excellent soft tissue contrast and the ability to visualize cancer physiology. Chemoradiation therapy with or without surgery is essential for the management of locally advanced esophageal cancer. MRI can help stage esophageal cancer, delineate the gross tumor volume (GTV), and assess the response to chemoradiotherapy. Integrated MRgRT systems can help overcome the challenge of esophageal motion due to respiratory motion by using real-time imaging and tumor tracking with respiratory gating. With daily on-table MRI, shifts in tumor position and tumor regression can be taken into account for online-adaptation. The combination of accurate GTV visualization, respiratory gating, and online adaptive planning, allows for tighter treatment volumes and improved sparing of the surrounding normal organs. This could lead to a reduction in radiotherapy induced cardiac toxicity, pneumonitis and post-operative complications. Tumor physiology as seen on diffusion weighted imaging or dynamic contrast enhancement can help individualize treatments based on the response to chemoradiotherapy. Patients with a complete response on MRI can be considered for organ preservation while patients with no response can be offered an earlier resection. In patients with a partial response to chemoradiotherapy, areas of residual cancer can be targeted for dose escalation. The tighter and more accurate targeting enabled with MRgRT may enable hypofractionated treatment schedules

A robust semi-automatic delineation workflow using denoised diffusion weighted magnetic resonance imaging for response assessment of patients with esophageal cancer treated with neoadjuvant chemoradiotherapy

Background and Purpose: Diffusion weighted magnetic resonance imaging (DW-MRI) can be prognostic for response to neoadjuvant chemotherapy (nCRT) in patients with esophageal cancer. However, manual tumor delineation is labor intensive and subjective. Furthermore, noise in DW-MRI images will propagate into the corresponding apparent diffusion coefficient (ADC) signal. In this study a workflow is investigated that combines a denoising algorithm with semi-automatic segmentation for quantifying ADC changes. Materials and Methods: Twenty patients with esophageal cancer who underwent nCRT before esophagectomy were included. One baseline and five weekly DW-MRI scans were acquired for every patient during nCRT. A self-supervised learning denoising algorithm, Patch2Self, was used to denoise the DWI-MRI images. A semi-automatic delineation workflow (SADW) was next developed and compared with a manually adjusted workflow (MAW). The agreement between workflows was determined using the Dice coefficients and Brand Altman plots. The prognostic value of ADCmean increases (%/week) for pathologic complete response (pCR) was assessed using c-statistics. Results: The median Dice coefficient between the SADW and MAW was 0.64 (interquartile range 0.20). For the MAW, the c-statistic for predicting pCR was 0.80 (95% confidence interval (CI):0.56–1.00). The SADW showed a c-statistic of 0.84 (95%CI:0.63–1.00) after denoising. No statistically significant differences in c-statistics were observed between the workflows or after applying denoising. Conclusions: The SADW resulted in non-inferior prognostic value for pCR compared to the more laborious MAW, allowing broad scale applications. The effect of denoising on the prognostic value for pCR needs to be investigated in larger cohorts.</p

A robust semi-automatic delineation workflow using denoised diffusion weighted magnetic resonance imaging for response assessment of patients with esophageal cancer treated with neoadjuvant chemoradiotherapy

Background and Purpose: Diffusion weighted magnetic resonance imaging (DW-MRI) can be prognostic for response to neoadjuvant chemotherapy (nCRT) in patients with esophageal cancer. However, manual tumor delineation is labor intensive and subjective. Furthermore, noise in DW-MRI images will propagate into the corresponding apparent diffusion coefficient (ADC) signal. In this study a workflow is investigated that combines a denoising algorithm with semi-automatic segmentation for quantifying ADC changes. Materials and Methods: Twenty patients with esophageal cancer who underwent nCRT before esophagectomy were included. One baseline and five weekly DW-MRI scans were acquired for every patient during nCRT. A self-supervised learning denoising algorithm, Patch2Self, was used to denoise the DWI-MRI images. A semi-automatic delineation workflow (SADW) was next developed and compared with a manually adjusted workflow (MAW). The agreement between workflows was determined using the Dice coefficients and Brand Altman plots. The prognostic value of ADCmean increases (%/week) for pathologic complete response (pCR) was assessed using c-statistics. Results: The median Dice coefficient between the SADW and MAW was 0.64 (interquartile range 0.20). For the MAW, the c-statistic for predicting pCR was 0.80 (95% confidence interval (CI):0.56–1.00). The SADW showed a c-statistic of 0.84 (95%CI:0.63–1.00) after denoising. No statistically significant differences in c-statistics were observed between the workflows or after applying denoising. Conclusions: The SADW resulted in non-inferior prognostic value for pCR compared to the more laborious MAW, allowing broad scale applications. The effect of denoising on the prognostic value for pCR needs to be investigated in larger cohorts.</p

Intrafraction motion analysis in online adaptive radiotherapy for esophageal cancer

Intrafraction motion during magnetic resonance (MR)-guided dose delivery of esophageal cancer tumors was retrospectively analyzed. Deformable image registration of cine-MR series resulted in gross tumor volume motion profiles in all directions, which were subsequently filtered to isolate respiratory and drift motion. A large variability in intrafraction motion patterns was observed between patients. Median 95% peak-to-peak motion was 7.7 (3.7 - 18.3) mm, 2.1 (0.7 - 5.7) mm and 2.4 (0.5 - 5.6) mm in cranio-caudal, left-right and anterior-posterior directions, relatively. Furthermore, intrafraction drift was generally modest (<5mm). A patient specific approach could lead to very small margins (<3mm) for most patients

The association between hospital variation in curative treatment for esophagogastric cancer and health-related quality of life and survival

Background: As previous studies showed significant hospital variation in curative treatment of esophagogastric cancer, this study assesses the association between this variation and overall, cancer-specific and recurrence-free survival, and Health-Related Quality of Life (HRQoL). Methods: Patients diagnosed with potentially curable esophageal or gastric cancer between 2015 and 2018 as registered in the Netherlands Cancer Registry were included. Data on overall survival was available for all patients, data on cancer-specific and recurrence-free survival and HRQoL was available for subgroups. Patients were classified according to diagnosis in hospitals with low, medium or high probability of treatment with curative intent (LP, MP or HP). Multivariable models were used to assess the association between LP, MP and HP hospitals and HRQoL and survival. Results: This study includes 7,199 patients with esophageal, and 2,407 with gastric cancer. Overall and cancer-specific survival was better for patients diagnosed in HP versus LP hospitals for both esophageal (HR = 0.82, 95%CI:0.77–0.88 and HR = 0.82, 95%CI:0.75–0.91, respectively), and gastric cancer (HR = 0.82, 95%CI:0.73–0.92 and HR = 0.74, 95%CI:0.64–0.87, respectively). These differences disappeared after adjustments for treatment. Recurrence-free survival was worse for gastric cancer patients diagnosed in HP hospitals (HR = 1.50, 95%CI:1.14–1.96), which disappeared after adjustment for radicality of surgery. Minor, but no clinically relevant, differences in HRQoL were observed.Conclusions: Patients diagnosed in hospitals with a high probability of treatment with curative intent have a better overall and cancer-specific but not recurrence-free survival, while minor differences in HRQoL were observed.</p

A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the proliferation, immune response and RNA splicing modules in breast cancer.

INTRODUCTION: Several gene expression signatures have been proposed and demonstrated to be predictive of outcome in breast cancer. In the present article we address the following issues: Do these signatures perform similarly? Are there (common) molecular processes reported by these signatures? Can better prognostic predictors be constructed based on these identified molecular processes? METHODS: We performed a comprehensive analysis of the performance of nine gene expression signatures on seven different breast cancer datasets. To better characterize the functional processes associated with these signatures, we enlarged each signature by including all probes with a significant correlation to at least one of the genes in the original signature. The enrichment of functional groups was assessed using four ontology databases. RESULTS: The classification performance of the nine gene expression signatures is very similar in terms of assigning a sample to either a poor outcome group or a good outcome group. Nevertheless the concordance in classification at the sample level is low, with only 50% of the breast cancer samples classified in the same outcome group by all classifiers. The predictive accuracy decreases with the number of poor outcome assignments given to a sample. The best classification performance was obtained for the group of patients with only good outcome assignments. Enrichment analysis of the enlarged signatures revealed 11 functional modules with prognostic ability. The combination of the RNA-splicing and immune modules resulted in a classifier with high prognostic performance on an independent validation set. CONCLUSIONS: The study revealed that the nine signatures perform similarly but exhibit a large degree of discordance in prognostic group assignment. Functional analyses indicate that proliferation is a common cellular process, but that other functional categories are also enriched and show independent prognostic ability. We provide new evidence of the potentially promising prognostic impact of immunity and RNA-splicing processes in breast cancer.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Long-term survival after sequential local treatments for oligometastatic esophageal squamous cell carcinoma: A case report

Introduction and importance: Patients with metastatic esophageal cancer generally have a poor prognosis. In patients with oligometastatic disease (OMD), local treatment of metastases may improve overall survival (OS). Case presentation: This case report describes a 57-year-old female with a cT4bN2M1 mid-esophageal squamous cell carcinoma with ingrowth in the aorta and pathologic para-aortic lymph node metastases in the left thorax (i.e. synchronous OMD). The patient first underwent a robot-assisted thoracoscopic para-aortic lymph node dissection (R1, aorta). After response to definitive chemoradiotherapy (ycT4aN1), a salvage robot-assisted minimally-invasive esophagectomy was performed (ypT0N1, R0). During follow-up, metastasectomy and repeated cryoablations for pulmonary metastases were performed (repeat OMD). The patient is currently alive in very good condition without evidence of disease 4.5 years after the first diagnosis of OMD and free of systemic therapy. Discussion: Clinical decision-making, local treatment options, and favorable biological tumor behavior in OMD are discussed. Conclusion: In this case of oligometastatic esophageal squamous cancer with favorable biological behavior, sequential local treatment of OMD (i.e. metastasectomy and cryoablations) combined with primary tumor resection was associated with long-term OS

An in-silico assessment of the dosimetric benefits of MR-guided radiotherapy for esophageal cancer patients

Purpose: To assess the dosimetric benefits of online MR-guided radiotherapy (MRgRT) for esophageal cancer patients and to assess how these benefits could be translated into a local boosting strategy to improve future outcomes. Methods: Twenty-nine patients were in-silico treated with both a MRgRT regimen and a conventional image guided radiotherapy (IGRT) regimen using dose warping techniques. Here, the inter and intrafractional changes that occur over the course of treatment (as derived from 5 MRI scans that were acquired weekly during treatment) were incorporated to assess the total accumulated dose for each regimen. Results: A significant reduction in dose to the organs-at-risk (OARs) was observed for all dose–volume-histogram (DVH) parameters for the MRgRT regimen without concessions to target coverage compared to the IGRT regimen. The mean lung dose was reduced by 28%, from 7.9 to 5.7 Gy respectively and V20Gy of the lungs was reduced by 55% (6.3–2.8%). A reduction of 24% was seen in mean heart dose (14.8–11.2 Gy), while the V25Gy of the heart was decreased by 53% (14.3–6.7%) and the V40Gy of the heart was decreased by 69% (3.9–1.2%). In addition, MRgRT dose escalation regimens with a boost up to 66% of the prescription dose to the primary tumor yielded approximately the same dose levels to the OARs as from the conventional IGRT regimen. Conclusion: This study revealed that MRgRT for esophageal cancer has the potential to significantly reduce the dose to heart and lungs. In addition, online high precision targeting of the primary tumor opens new perspectives for local boosting strategies to improve outcome of the local management of this disease