Purpose: Glioblastomas are treated by surgical resection followed by radiotherapy [X-ray therapy (XRT)] and the alkylating chemotherapeutic agent temozolomide. Recently, inactivating mutations in the mismatch repair gene MSH6 were identified in two glioblastomas recurrent post-temozolomide. Because mismatch repair pathway inactivation is a known mediator of alkylator resistance in vitro, these findings suggested that MSH6 inactivation was causally linked to these two recurrences. However, the extent of involvement of MSH6 in glioblastoma is unknown. We sought to determine the overall frequency and clinical relevance of MSH6 alterations in glioblastomas. Experimental Design: The MSH6 gene was sequenced in 54 glioblastomas. MSH6 and O 6 -methylguanine methyltransferase (MGMT) immunohistochemistry was systematically scored in a panel of 46 clinically well-characterized glioblastomas, and the corresponding patient response to treatment evaluated. Results: MSH6 mutation was not observed in any pretreatment glioblastoma (0 of 40), whereas 3 of 14 recurrent cases had somatic mutations (P = 0.015). MSH6 protein expression was detected in all pretreatment (17 of 17) cases examined but, notably, expression was lost in 7 of 17 (41%) recurrences from matched post^XRT + temozolomide cases (P = 0.016). Loss of MSH6 was not associated with O 6 -methylguanine methyltransferase status. Measurements of in vivo tumor growth using three-dimensional reconstructed magnetic resonance imaging showed that MSH6-negative glioblastomas had a markedly increased rate of growth while under temozolomide treatment (3.17 versus 0.04 cc/mo for MSH6-positive tumors; P = 0.020). Conclusions: Loss of MSH6 occurs in a subset of post^XRT + temozolomide glioblastoma recurrences and is associated with tumor progression during temozolomide treatment, mirroring the alkylator resistance conferred by MSH6 inactivation in vitro. MSH6 deficiency may therefore contribute to the emergence of recurrent glioblastomas during temozolomide treatment.

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Concentric tube robots are catheter-sized continuum robots that are well suited for minimally invasive surgery inside confined body cavities. These robots are constructed from sets of pre-curved superelastic tubes and are capable of assuming complex 3D curves. The family of 3D curves that the robot can assume depends on the number, curvatures, lengths and stiffnesses of the tubes in its tube set. The robot design problem involves solving for a tube set that will produce the family of curves necessary to perform a surgical procedure. At a minimum, these curves must enable the robot to smoothly extend into the body and to manipulate tools over the desired surgical workspace while respecting anatomical constraints. This paper introduces an optimization framework that utilizes procedureor patient-specific image-based anatomical models along with surgical workspace requirements to generate robot tube set designs. The algorithm searches for designs that minimize robot length and curvature and for which all paths required for the procedure consist of stable robot configurations. Two mechanics-based kinematic models are used. Initial designs are sought using a model assuming torsional rigidity. These designs are then refined using a torsionally-compliant model. The approach is illustrated with clinically relevant examples from neurosurgery and intracardiac surgery.