Primary hepatic embryonal sarcoma masquerading as metastatic ovarian cancer

<p>Abstract</p> <p>Background</p> <p>Hepatic embryonal sarcoma (HES) is a rare but aggressive primary tumor of the liver occurring most frequently in childhood.</p> <p>Case presentation</p> <p>We report a case of a 52 year old woman having previously undergone treatment for ovarian serous papillary carcinoma who subsequently presented with a large solitary mass in the liver. Initially this was presumed to be metastasis from the ovarian primary however, on further examination it was shown to be a primary hepatic embryonal sarcoma.</p> <p>Conclusion</p> <p>Primary liver tumors should be considered in differential diagnoses in patients with ovarian cancer who subsequently present with liver tumors. This is particularly important when there is no direct evidence of recurrence of ovarian cancer.</p

Mediastinal extension of a complicated pancreatic pseudocyst; a case report and literature review

BACKGROUND: Mediastinal pancreatic pseudocyst is a rare complication of acute or chronic pancreatitis. CASE PRESENTATION: This case report describes the management of a difficult case of pancreatic pseudocyst with a mediastinal extension in a patient having chronic pancreatitis. Different management strategies were used until complete resolution of this complex pseudocyst occurred using open surgical cystogastrostomy. CONCLUSION: Despite the availablity of different minimally invasive techniques to treat pancreatic pseudocysts, management of complex mediastinal pseudocyst may still require open surgical drainage procedures

Colorectal liver metastases: Current management and future perspectives.

The liver is the commonest site of metastatic disease for patients with colorectal cancer, with at least 25% developing colorectal liver metastases (CRLM) during the course of their illness. The management of CRLM has evolved into a complex field requiring input from experienced members of a multi-disciplinary team involving radiology (cross sectional, nuclear medicine and interventional), Oncology, Liver surgery, Colorectal surgery, and Histopathology. Patient management is based on assessment of sophisticated clinical, radiological and biomarker information. Despite incomplete evidence in this very heterogeneous patient group, maximising resection of CRLM using all available techniques remains a key objective and provides the best chance of long-term survival and cure. To this end, liver resection is maximised by the use of downsizing chemotherapy, optimisation of liver remnant by portal vein embolization, associating liver partition and portal vein ligation for staged hepatectomy, and combining resection with ablation, in the context of improvements in the functional assessment of the future remnant liver. Liver resection may safely be carried out laparoscopically or open, and synchronously with, or before, colorectal surgery in selected patients. For unresectable patients, treatment options including systemic chemotherapy, targeted biological agents, intra-arterial infusion or bead delivered chemotherapy, tumour ablation, stereotactic radiotherapy, and selective internal radiotherapy contribute to improve survival and may convert initially unresectable patients to operability. Currently evolving areas include biomarker characterisation of tumours, the development of novel systemic agents targeting specific oncogenic pathways, and the potential re-emergence of radical surgical options such as liver transplantation

Surgical outcomes of gallbladder cancer:the OMEGA retrospective, multicentre, international cohort study

Background: Gallbladder cancer (GBC) is rare but aggressive. The extent of surgical intervention for different GBC stages is non-uniform, ranging from cholecystectomy alone to extended resections including major hepatectomy, resection of adjacent organs and routine extrahepatic bile duct resection (EBDR). Robust evidence here is lacking, however, and survival benefit poorly defined. This study assesses factors associated with recurrence-free survival (RFS), overall survival (OS) and morbidity and mortality following GBC surgery in high income countries (HIC) and low and middle income countries (LMIC). Methods: The multicentre, retrospective Operative Management of Gallbladder Cancer (OMEGA) cohort study included all patients who underwent GBC resection across 133 centres between 1st January 2010 and 31st December 2020. Regression analyses assessed factors associated with OS, RFS and morbidity. Findings: On multivariable analysis of all 3676 patients, wedge resection and segment IVb/V resection failed to improve RFS (HR 1.04 [0.84–1.29], p = 0.711 and HR 1.18 [0.95–1.46], p = 0.13 respectively) or OS (HR 0.96 [0.79–1.17], p = 0.67 and HR 1.48 [1.16–1.88], p = 0.49 respectively), while major hepatectomy was associated with worse RFS (HR 1.33 [1.02–1.74], p = 0.037) and OS (HR 1.26 [1.03–1.53], p = 0.022). Furthermore, EBDR (OR 2.86 [2.3–3.52], p &lt; 0.0010), resection of additional organs (OR 2.22 [1.62–3.02], p &lt; 0.0010) and major hepatectomy (OR 3.81 [2.55–5.73], p &lt; 0.0010) were all associated with increased morbidity and mortality. Compared to LMIC, patients in HIC were associated with poorer RFS (HR 1.18 [1.02–1.37], p = 0.031) but not OS (HR 1.05 [0.91–1.22], p = 0.48). Adjuvant and neoadjuvant treatments were infrequently used. Interpretation: In this large, multicentre analysis of GBC surgical outcomes, liver resection was not conclusively associated with improved survival, and extended resections were associated with greater morbidity and mortality without oncological benefit. Aggressive upfront resections do not benefit higher stage GBC, and international collaborations are needed to develop evidence-based neoadjuvant and adjuvant treatment strategies to minimise surgical morbidity and prioritise prognostic benefit. Funding:Cambridge Hepatopancreatobiliary Department Research Fund.</p

An Optimal Arc Consistency Algorithm for a Chain of Atmost Constraints with Cardinality

International audienceThe ATMOSTSEQCARD constraint is the conjunction of a cardinality constraint on a sequence of n variables and of n - q + 1 constraints ATMOST u on each subsequence of size q. This constraint is useful in car-sequencing and crew-rostering problems. In [18], two algorithms designed for the AMONGSEQ constraint were adapted to this constraint with a O(2^q n) and O(n^3) worst case time complexity, respectively. In [10], another algorithm with a O(n2 log n) worst case time complexity and similarly adaptable to filter ATMOSTSEQCARD in O(n log n) was proposed. In this paper, we introduce an algorithm for achieving Arc Consistency on the ATMOSTSEQCARD constraint with a O(n) (hence optimal) worst case time complexity. We then empirically study the efficiency of our propagator on instances of the car-sequencing and crew-rostering problems

An optimal arc consistency algorithm for a particular case of sequence constraint

Abstract. The ATMOSTSEQCARD constraint is the conjunction of a cardinality constraint on a sequence of n variables and of n − q + 1 constraints ATMOST u on each subsequence of size q. This constraint is useful in car-sequencing and crew-rostering problems. In [?], two algorithms designed for the AMONGSEQ constraint were adapted to this constraint with an O(2 q n) and O(n 3 ) worst case time complexity, respectively. In [?], another algorithm similarly adaptable to filter the ATMOSTSEQCARD constraint with a time complexity of O(n 2 ) was proposed. In this paper, we introduce an algorithm for achieving arc consistency on the ATMOSTSEQCARD constraint with an O(n) (hence optimal) worst case time complexity. Next, we show that this algorithm can be easily modified to achieve arc consistency on some extensions of this constraint. In particular, the conjunction of a set of m ATMOSTSEQCARD constraints sharing the same scope can be filtered in O(nm). We then empirically study the efficiency of our propagator on instances of the car-sequencing and crew-rostering problems

Algorithme optimal d'arc-consistance pour une séquence de contraintes AtMost avec cardinalité

National audienceLa contrainte ATMOSTSEQCARD est la conjonction entre une contrainte de cardinalité sur une séquence de n variables et de n q + 1 contraintes ATMOST u sur toutes sous-séquences de variables de taille q. Elle se retrouve en particuliers dans des problèmes de type car-sequencing et crew-rostering. Une adaptation de deux algorithmes conçus pour la contrainte AMONGSEQ afin de traiter la contrainte ATMOSTSEQCARD a été proposée dans [18]. Ces algorithmes ont une complexité temporelle respective au pire en O(2q1n) et O(n3). Dans [10], un autre algorithme a été adapté de manière similaire pour la contrainte ATMOSTSEQCARD avec une complexité temporelle au pire en O(n2 log n). Cet article présente un algorithme réalisant l'arc-consistance de la contrainte ATMOSTSEQCARD avec une complexité temporelle au pire en O(n) (et donc optimal). Enfin, des expérimentations sont présentées pour évaluer l'efficacité de cet algorithme sur des problèmes de carsequencing et de crew-rostering

A study of constraint programming heuristics for the car-sequencing problem

International audienceIn the car-sequencing problem, a number of cars has to be sequenced on an assembly line respecting several constraints. This problem was addressed by both Operations Research (OR) and Constraint Programming (CP) com-munities, either as a decision problem or as an optimization problem. In this paper, we consider the decision variant of the car sequencing problem and we propose a systematic way to classify heuristics for solving it. This classification is based on a set of four criteria, and we consider all relevant combinations for these criteria. Some combinations correspond to common heuristics used in the past, whereas many others are novel. Not surprisingly, our empirical evaluation confirms earlier findings that specific heuristics are very important for efficiently solving the car-sequencing problem (see for in-stance [17]), in fact, often as important or more than the propagation method. Moreover, through a criteria analysis, we are able to get several new insights into what makes a good heuristic for this problem. In particular, we show that the criterion used to select the most constrained option is critical, and the best choice is fairly reliably the "load" of an option. Similarly, branching on the type of vehicle is more efficient than branching on the use of an option. Overall, we can therefore indicate with a relatively high confidence which is the most robust strategy, or at least outline a small set of potentially best strategies. Last, following a remark in [14] stating that the notion of slack used in heuristics induces a pruning rule, we propose an algorithm for this method and experimentally evaluate it, showing that, although computationally cheap and easy to implement, this is in practice a very efficient way to solve car-sequencing benchmarks

Solving hard sequencing problems via the AtMostSeqCard constraint

Prix jeune chercheurInternational audienceSequence constraints are useful in a number of applications. Constraints of this class enforce upper and/or lower bounds on all sub-sequences of variables of a given length within a main sequence. For instance, in Crew-Rostering problems, we may want to have an upper bound on the number of worked days in every sub-sequence to meet working regulations. Several constraints of this class have been studied in the Constraint Programming (CP) literature such as GenSequence, AmongSeq, etc. An even more general constraint, Regular, can be used to enforce arbitrary patterns on all sub-sequences. However, the more general a constraint is, the higher is the complexity of reasoning about it. We therefore investigate the AtMostSeqCard constraint, a particular case where the sequence of variables is subject to a chain of AtMost constraints (all subsequences of size q have at most u values in a set v) along with a global cardinality. This constraint is useful in Car-Sequencing and Crew-Rosterning problems. In [van Hoeve et al.], two algorithms designed for the AmongSeq constraint were adapted to this constraint with an O(2^q . n) and O(\n^3) worst case time complexity, respectively. In [Maher et al.], another algorithm similarly adaptable to filter the AtMostSeqCard constraint with a time complexity of O(n^2) was proposed. We summarize our contributions regarding this constraint in three different axis. We first introduce an algorithm for achieving arc consistency on the AtMostSeqCard constraint with an O(n) (hence optimal) worst case time complexity. Next, we present practical extensions of this constraint and show how the propagator scales accordingly. We finally propose a novel linear time mechanism for explaining this constraint in a hybrid CP/SAT context.Our experiments show significant improvements on Car-sequencing and Crew-Rostering problems