Golden standard for radical cystectomy:open or robot assisted?

De open radicale cystectomie wordt beschouwd als de standaardbehandeling van het spierinvasief blaascarcinoom en bij recidiverend hoogrisico niet-spierinvasief blaascarcinoom. Sinds 2000 wordt de cystectomie steeds meer laparoscopisch en met assistentie van de robot uitgevoerd, al dan niet met een intracorporeel aangelegde urinedeviatie. De resultaten uit de literatuur komen vooral uit retrospectieve studies, waarin de resultaten worden vergeleken met historische open cystectomieseries. In combinatie met de resultaten van enkele kleinere prospectieve series is er aanzienlijk bewijs dat de robotgeassisteerde radicale cystectomie (RARC) een veilige techniek is waarbij minder bloedverlies en bloedtransfusiebehoefte optreedt en patiënten minder lang opgenomen zijn ten opzichte van de open radicale cystectomie (ORC). Ten aanzien van de functionele en oncologische resultaten lijkt de RARC niet onder te doen voor de ORC. Daarbij heeft de RARC een groot ergonomisch voordeel. Een nadeel is dat de aanschaf en het gebruik van een daVinci™-systeem gepaard gaan met hogere kosten. Zowel internationaal als nationaal wordt momenteel gewerkt aan prospectieve multicentrische vergelijkende studies om het mogelijke verschil aan te tonen ten opzichte van de ORC op het oncologische en/of functionele vlak, maar daarnaast meer duidelijkheid te verkrijgen ten aanzien van de kosteneffectiviteit van de RARC

Topographical Mapping of 436 Newly Diagnosed IDH Wildtype Glioblastoma With vs. Without MGMT Promoter Methylation

Introduction: O6-methylguanine-methyltransferase (MGMT) promoter methylation and isocitrate dehydrogenase (IDH) mutation status are important prognostic factors for patients with glioblastoma. There are conflicting reports about a differential topographical distribution of glioblastoma with vs. without MGMT promoter methylation, possibly caused by molecular heterogeneity in glioblastoma populations. We initiated this study to re-evaluate the topographical distribution of glioblastoma with vs. without MGMT promoter methylation in light of the updated WHO 2016 classification. Methods: Preoperative T2-weighted/FLAIR and postcontrast T1-weighted MRI scans of patients aged 18 year or older with IDH wildtype glioblastoma were collected. Tumors were semi-automatically segmented, and the topographical distribution between glioblastoma with vs. without MGMT promoter methylation was visualized using frequency heatmaps. Then, voxel-wise differences were analyzed using permutation testing with Threshold Free Cluster Enhancement. Results: Four hundred thirty-six IDH wildtype glioblastoma patients were included; 211 with and 225 without MGMT promoter methylation. Visual examination suggested that when compared with MGMT unmethylated glioblastoma, MGMT methylated glioblastoma were more frequently located near bifrontal and left occipital periventricular area and less frequently near the right occipital periventricular area. Statistical analyses, however, showed no significant difference in topographical distribution between MGMT methylated vs. MGMT unmethylated glioblastoma. Conclusions: This study re-evaluated the

Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

This work validates the generalizability of MRI-based classification of Alzheimer’s disease (AD) patients and controls (CN) to an external data set and to the task of prediction of conversion to AD in individuals with mild cognitive impairment (MCI).We used a conventional support vector machine (SVM) and a deep convolutional neural network (CNN) approach based on structural MRI scans that underwent either minimal pre-processing or more extensive pre-processing into modulated gray matter (GM) maps. Classifiers were optimized and evaluated using cross-validation in the Alzheimer’s Disease Neuroimaging Initiative (ADNI; 334 AD, 520 CN). Trained classifiers were subsequently applied to predict conversion to AD in ADNI MCI patients (231 converters, 628 non-converters) and in the independent Health-RI Parelsnoer Neurodegenerative Diseases Biobank data set. From this multi-center study representing a tertiary memory clinic population, we included 199 AD patients, 139 participants with subjective cognitive decline, 48 MCI patients converting to dementia, and 91 MCI patients who did not convert to dementia.AD-CN classification based on modulated GM maps resulted in a similar area-under-the-curve (AUC) for SVM (0.940; 95%CI: 0.924–0.955) and CNN (0.933; 95%CI: 0.918–0.948). Application to conversion prediction in MCI yielded significantly higher performance for SVM (AUC = 0.756; 95%CI: 0.720-0.788) than for CNN (AUC = 0.742; 95%CI: 0.709-0.776) (p<0.01 for McNemar’s test). In external validation, performance was slightly decreased. For AD-CN, it again gave similar AUCs for SVM (0.896; 95%CI: 0.855–0.932) and CNN (0.876; 95%CI: 0.836–0.913). For prediction in MCI, performances decreased for both SVM (AUC = 0.665; 95%CI: 0.576-0.760) and CNN (AUC = 0.702; 95%CI: 0.624-0.786). Both with SVM and CNN, classification based on modulated GM maps significantly outperformed classification based on minimally processed images (p=0.01).Deep and conventional classifiers performed equally well for AD classification and their performance decreased only slightly when applied to the external cohort. We expect that this work on external validation contributes towards translation of machine learning to clinical practice

The Dutch Parelsnoer Institute - Neurodegenerative diseases; methods, design and baseline results

Background: The is a collaboration between 8 Dutch University Medical Centers in which clinical data and biomaterials from patients suffering from chronic diseases (so called "Pearls") are collected according to harmonized protocols. The Pearl Neurodegenerative Diseases focuses on the role of biomarkers in the early diagnosis, differential diagnosis and in monitoring the course of neurodegenerative diseases, in particular Alzheimer's disease. Methods: The Pearl Neurodegenerative Diseases is a 3-year follow-up study of patients referred to a memory clinic with cognitive complaints. At baseline, all patients are subjected to a standardized examination, including clinical data and biobank materials, e.g. blood samples, MRI and cerebrospinal fluid. At present, in total more than 1000 patients have been included, of which cerebrospinal fluid and DNA samples are available of 211 and 661 patients, respectively. First descriptives of a subsample of the data (n = 665) shows that patients are diagnosed with dementia (45%), mild cognitive impairment (31%), and subjective memory complaints (24%). Discussion: The Pearl Neurodegenerative Diseases is an ongoing large network collecting clinical data and biomaterials of more than 1000 patients with cognitive impairments. The project has started with data analyses of the baseline characteristics and biomarkers, which will be the starting point of future specific research questions that can be answered by this unique dataset

Two-year follow-up of the phase II marker lesion study of intravesical apaziquone for patients with non-muscle invasive bladder cancer

Item does not contain fulltextOBJECTIVES: To study the time-to-recurrence and duration of response in non-muscle invasive bladder cancer (NMIBC) patients, with a complete ablative response after intravesical apaziquone instillations. METHODS: Transurethral resection of bladder tumour(s) (TURBT) was performed in patients with multiple pTa-T1 G1-2 urothelial cell carcinoma (UCC) of the bladder, with the exception of one marker lesion of 0.5-1.0 cm. Intravesical apaziquone was administered at weekly intervals for six consecutive weeks, without maintenance instillations. A histological confirmed response was obtained 2-4 weeks after the last instillation. Routine follow-up (FU) was carried out at 6, 9, 12, 18 and 24 months from the first apaziquone instillation. RESULTS: At 3 months FU 31 of 46 patients (67.4%) had a complete response (CR) to ablative treatment. Side-effects on the long-term were only mild. Two CR patients dropped out during FU. On intention-to-treat (ITT) analysis 49.5% of the CR patients were recurrence-free at 24 months FU, with a median duration of response of 18 months. Of 15 no response (NR) patients, only two received additional prophylactic instillations after TURBT. On ITT-analysis 26.7% of the NR patients were recurrence-free (log rank test, P = 0.155). The overall recurrence-free survival was 39% (18 of 46 patients) at 24 months FU. CONCLUSIONS: The CR of the marker lesion in 67% of patients was followed by a recurrence-free rate of 56.5% at 1-year FU, and 49.5% at 2-year FU. These long-term results are good in comparison with the results of other ablative studies

Impact of donor lung quality on post-transplant recipient outcome in the Lung Allocation Score era in Eurotransplant – a historical prospective study

The aim of this study was to investigate whether there is an impact of donation rates on the quality of lungs used for transplantation and whether donor lung quality affects post-transplant outcome in the current Lung Allocation Score era. All consecutive adult LTx performed in Eurotransplant (ET) between January 2012 and December 2016 were included (N = 3053). Donors used for LTx in countries with high donation rate were younger (42% vs. 33% ≤45 years, P < 0.0001), were less often smokers (35% vs. 46%, P < 0.0001), had more often clear chest X-rays (82% vs. 72%, P < 0.0001), had better donor oxygenation ratios (20% vs. 26% with PaO2/FiO2 ≤ 300 mmHg, P < 0.0001), and had better lung donor score values (LDS; 28% vs. 17% with LDS = 6, P < 0.0001) compared with donors used for LTx in countries with low donation rate. Survival rates for the groups LDS = 6 and ≥7 at 5 years were 69.7% and 60.9% (P = 0.007). Lung donor quality significantly impacts on long-term patient survival. Countries with a low donation rate are more oriented to using donor lungs with a lesser quality compared to countries with a high donation rate. Instead of further stretching donor eligibility criteria, the full potential of the donor pool should be realized

Imaging practice in low-grade gliomas among European specialized centers and proposal for a minimum core of imaging

Objective: Imaging studies in diffuse low-grade gliomas (DLGG) vary across centers. In order to establish a minimal core of imaging necessary for further investigations and clinical trials in the field of DLGG, we aimed to establish the status quo within specialized European centers. Methods: An online survey composed of 46 items was sent out to members of the European Low-Grade Glioma Network, the European Association of Neurosurgical Societies, the German Society of Neurosurgery and the Austrian Society of Neurosurgery. Results: A total of 128 fully completed surveys were received and analyzed. Most centers (n=96, 75%) were academic and half of the centers (n=64, 50%) adhered to a dedicated treatment program for DLGG. There were national differences regarding the sequences enclosed in MRI imaging and use of PET, however most included T1 (without and with contrast, 100%), T2 (100%) and TIRM or FLAIR (20, 98%). DWI is performed by 80% of centers and 61% of centers regularly performed PWI.ConclusionA minimal core of imaging composed of T1 (w/wo contrast), T2, TIRM/FLAIR, PWI and DWI could be identified. All morphologic images should be obtained in a slice thickness of 3mm. No common standard could be obtained regarding advanced MRI protocols and PET. Importance of the study: We believe that our study makes a significant contribution to the literature because we were able to determine similarities in numerous aspects of LGG imaging. Using the proposed minimal core of imaging in clinical routine will facilitate future cooperative studies

Impact of Complications After Pancreatoduodenectomy on Mortality, Organ Failure, Hospital Stay, and Readmission Analysis of a Nationwide Audit:Analysis of a Nationwide Audit

OBJECTIVE: To quantify the impact of individual complications on mortality, organ failure, hospital stay, and readmission after pancreatoduodenectomy. SUMMARY OF BACKGROUND DATA: An initial complication may provoke a sequence of adverse events potentially leading to mortality after pancreatoduodenectomy. This study was conducted to aid prioritization of quality improvement initiatives. METHODS: Data from consecutive patients undergoing pancreatoduodenectomy (2014-2017) were extracted from the Dutch Pancreatic Cancer Audit. Population attributable fractions (PAF) were calculated for the association of each complication (ie, postoperative pancreatic fistula, postpancreatectomy hemorrhage, bile leakage, delayed gastric emptying, wound infection, and pneumonia) with each unfavorable outcome [ie, in-hospital mortality, organ failure, prolonged hospital stay (>75th percentile), and unplanned readmission), whereas adjusting for confounders and other complications. The PAF represents the proportion of an outcome that could be prevented if a complication would be eliminated completely. RESULTS: Overall, 2620 patients were analyzed. In-hospital mortality occurred in 95 patients (3.6%), organ failure in 198 patients (7.6%), and readmission in 427 patients (16.2%). Postoperative pancreatic fistula and postpancreatectomy hemorrhage had the greatest independent impact on mortality [PAF 25.7% (95% CI 13.4-37.9) and 32.8% (21.9-43.8), respectively] and organ failure [PAF 21.8% (95% CI 12.9-30.6) and 22.1% (15.0-29.1), respectively]. Delayed gastric emptying had the greatest independent impact on prolonged hospital stay [PAF 27.6% (95% CI 23.5-31.8)]. The impact of individual complications on unplanned readmission was smaller than 11%. CONCLUSION: Interventions focusing on postoperative pancreatic fistula and postpancreatectomy hemorrhage may have the greatest impact on in-hospital mortality and organ failure. To prevent prolonged hospital stay, initiatives should in addition focus on delayed gastric emptying

Care after pancreatic resection according to an algorithm for early detection and minimally invasive management of pancreatic fistula versus current practice (PORSCH-trial):design and rationale of a nationwide stepped-wedge cluster-randomized trial

Background: Pancreatic resection is a major abdominal operation with 50% risk of postoperative complications. A common complication is pancreatic fistula, which may have severe clinical consequences such as postoperative bleeding, organ failure and death. The objective of this study is to investigate whether implementation of an algorithm for early detection and minimally invasive management of pancreatic fistula may improve outcomes after pancreatic resection. Methods: This is a nationwide stepped-wedge, cluster-randomized, superiority trial, designed in adherence to the Consolidated Standards of Reporting Trials (CONSORT) guidelines. During a period of 22 months, all Dutch centers performing pancreatic surgery will cross over in a randomized order from current practice to best practice according to the algorithm. This evidence-based and consensus-based algorithm will provide daily multilevel advice on the management of patients after pancreatic resection (i.e. indication for abdominal imaging, antibiotic treatment, percutaneous drainage and removal of abdominal drains). The algorithm is designed to aid early detection and minimally invasive step-up management of postoperative pancreatic fistula. Outcomes of current practice will be compared with outcomes after implementation of the algorithm. The primary outcome is a composite of major complications (i.e. post-pancreatectomy bleeding, new-onset organ failure and death) and will be measured in a sample size of at least 1600 patients undergoing pancreatic resection. Secondary endpoints include the individual components of the primary endpoint and other clinical outcomes, healthcare resource utilization and costs analysis. Follow up will be up to 90 days after pancreatic resection. Discussion: It is hypothesized that a structured nationwide implementation of a dedicated algorithm for early detection and minimally invasive step-up management of postoperative pancreatic fistula will reduce the risk of major complications and death after pancreatic resection, as compared to current practice. Trial registration: Netherlands Trial Register: NL 6671. Registered on 16 December 2017

Reproducible radiomics through automated machine learning validated on twelve clinical applications

Radiomics uses quantitative medical imaging features to predict clinical outcomes. Currently, in a new clinical application, findingthe optimal radiomics method out of the wide range of available options has to be done manually through a heuristic trial-anderror process. In this study we propose a framework for automatically optimizing the construction of radiomics workflows perapplication. To this end, we formulate radiomics as a modular workflow and include a large collection of common algorithms foreach component. To optimize the workflow per application, we employ automated machine learning using a random search andensembling. We evaluate our method in twelve different clinical applications, resulting in the following area under the curves: 1)liposarcoma (0.83); 2) desmoid-type fibromatosis (0.82); 3) primary liver tumors (0.80); 4) gastrointestinal stromal tumors (0.77);5) colorectal liver metastases (0.61); 6) melanoma metastases (0.45); 7) hepatocellular carcinoma (0.75); 8) mesenteric fibrosis(0.80); 9) prostate cancer (0.72); 10) glioma (0.71); 11) Alzheimer’s disease (0.87); and 12) head and neck cancer (0.84). Weshow that our framework has a competitive performance compared human experts, outperforms a radiomics baseline, and performssimilar or superior to Bayesian optimization and more advanced ensemble approaches. Concluding, our method fully automaticallyoptimizes the construction of radiomics workflows, thereby streamlining the search for radiomics biomarkers in new applications.To facilitate reproducibility and future research, we publicly release six datasets, the software implementation of our framework,and the code to reproduce this study