Purpose Detecting circulating plasma tumor DNA (ptDNA) in early stage cancer patients has the potential to change how oncologists recommend systemic therapies for solid tumors after surgery. Droplet digital polymerase chain reaction (ddPCR) is a novel sensitive and specific platform for mutation detection. Experimental Design In this prospective study, primary breast tumors and matched pre- and post-surgery blood samples were collected from early stage breast cancer patients (n=29). Tumors (n=30) were analyzed by Sanger sequencing for common PIK3CA mutations, and DNA from these tumors and matched plasma were then analyzed for PIK3CA mutations using ddPCR. Results Sequencing of tumors identified seven PIK3CA exon 20 mutations (H1047R) and three exon 9 mutations (E545K). Analysis of tumors by ddPCR confirmed these mutations and identified five additional mutations. Pre-surgery plasma samples (n=29) were then analyzed for PIK3CA mutations using ddPCR. Of the fifteen PIK3CA mutations detected in tumors by ddPCR, fourteen of the corresponding mutations were detected in pre-surgical ptDNA, while no mutations were found in plasma from patients with PIK3CA wild type tumors (sensitivity 93.3%, specificity 100%). Ten patients with mutation positive ptDNA pre-surgery had ddPCR analysis of post-surgery plasma, with five patients having detectable ptDNA post-surgery. Conclusions This prospective study demonstrates accurate mutation detection in tumor tissues using ddPCR, and that ptDNA can be detected in blood before and after surgery in early stage breast cancer patients. Future studies can now address whether ptDNA detected after surgery identifies patients at risk for recurrence, which could guide chemotherapy decisions for individual patients.

Digital PCR is a new technology that enables detection and quantification of cancer DNA molecules from peripheral blood. Using this technique, we identified mutant PIK3CA DNA in circulating plasma tumor DNA (ptDNA) from a patient with concurrent early stage breast cancer and non-small cell lung cancer. The patient underwent successful resection of both her breast and lung cancers, and using standard Sanger sequencing the breast cancer was shown to harbor the identical PIK3CA mutation identified in peripheral blood. This case report highlights potential applications and concerns that can arise with the use of ptDNA in clinical oncology practice.

Our survey revealed the vast difference between literature suggestions and actual clinical practice on the use of PET in radiotherapy. Additional training and standardization of protocols for use of PET in radiotherapy is essential for fully utilizing the capability of PET.

Abstract. This paper presents an improved GrowCut (IGC), a positron emission tomography-based segmentation algorithm, and tests its clinical applicability. Contrary to the traditional method that requires the user to provide the initial seeds, the IGC algorithm starts with a threshold-based estimate of the tumor and a threedimensional morphologically grown shell around the tumor as the foreground and background seeds, respectively. The repeatability of IGC from the same observer at multiple time points was compared with the traditional GrowCut algorithm. The algorithm was tested in 11 nonsmall cell lung cancer lesions and validated against the clinician-defined manual contour and compared against the clinically used 25% of the maximum standardized uptake value [SUV-(max)], 40% SUV max , and adaptive threshold methods. The time to edit IGC-defined functional volume to arrive at the gross tumor volume (GTV) was compared with that of manual contouring. The repeatability of the IGC algorithm was very high compared with the traditional GrowCut (p ¼ 0.003) and demonstrated higher agreement with the manual contour with respect to threshold-based methods. Compared with manual contouring, editing the IGC achieved the GTV in significantly less time (p ¼ 0.11). The IGC algorithm offers a highly repeatable functional volume and serves as an effective initial guess that can well minimize the time spent on labor-intensive manual contouring.

Glioblastoma Multiforme (GBM) is a high-grade brain tumour with the most dismal prognosis. There are very few reports on second malignancies occurring in GBM patients, as the survival has been short. Second malignancies have been reported after treatment of malignancies with radiation therapy and chemotherapy especially after 5 to 10 y of treatment. Here in, we present a very unique case where a patient succumbed to sinonasal carcinoma occurring one and half years after treatment of GBM. A 17-year-old boy was diagnosed to have GBM and underwent surgery followed by chemoradiation and adjuvant chemotherapy with Temozolamide. He presented with undifferentiated sinonasal carcinoma, in the sinonasal region outside the radiation field within two years of treatment. Here we discuss the histology and possible chances of it being a second malignancy.

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In areas like adaptive therapy, multi-phase radiotherapy, and single fraction palliative treatment or in the treatment of patients with metal implants where megavoltage(MV) CT could be considered as a treatment planning modality, the reduced contrast in the MV CT images could lead to limited accuracy in localization of the structures. This would affect the precision of the treatment. In this study, as an extension our previous work on bespoke MV cone beam CT (MV CBCT), we propose to register the MV CBCT with kilovoltage (kV) CT for treatment planning. The MV CBCT images registered with kV CT would be effective for treatment planning as it would account for the inadequate soft tissue information in the MV CBCT and would allow comparison of changes in patient dimensions and assist in localization of the structures. The intensity based registration algorithm of the BrainSCAN therapy planning software was used for image registration of the MV CBCT and kV CT images. The accuracy of the registration was validated using qualitative and quantitative measures. The effect of image quality on the level of agreement between the contouring done on both the MV CBCT and kV CT was assessed by comparing the volumes of six structures delineated. To assess the level of agreement between the plans after the registration, two independent plans were generated on the MV CBCT and the planning CT using the posterior fossa of the skull as the target. The dose volume histograms and conformity indices of the plans were compared. The results of this study show that treatment planning with MV CBCT images would be effective, using additional anatomical structure information derived from registering the MV CBCT image with a standard kVCT.

BackgroundTo introduce a method to generate a ‘dose–volume histogram (DVH) band’ for plan evaluation of photon therapy and explore its various potentials.Materials and methodsIntensity-modulated radiotherapy (IMRT) plans for head and neck cancer patients were analysed, retrospectively, for setup errors noted during treatment. From the maximum observed random errors, absolute displacement was calculated using Euclidian formula. The original plan with same beam parameters and leaf sequence were used to generate six plans with shifts applied in three axes in six directions. The DVH curves from these six plans were superimposed to form the DVH band. Plans were reviewed with set tolerance criteria.ResultsMethod to generate and visualise DVH band was developed. DVH bands were created for 20 patients with head and neck cancer who underwent treatment with IMRT. It was found that seven out these 20 plans were rejected as they crossed the set tolerance criteria using DVH band as an evaluation tool.ConclusionsDVH band in photon therapy can help the clinician visualise the impact of setup errors at planning and may help select the plan with lesser influence of setup errors over another.