An Iterative Diffeomorphic Algorithm for Registration of Subdivision Surfaces: Application to Congenital Heart Disease

In this paper, we present a new diffeomorphic registration algorithm for the registration of 3D models to 3D points. A biventricular template is iteratively fitted to the data by a series of implicitly constrained diffeomorphic linear least squares fits with decreasing regularization weights before performing an explicitly constrained diffeomorphic fit. The algorithm has been tested on a set of manual contours from 20 patients with a variety of congenital heart disease. Registration accuracy was assessed by calculating the mean point-to-point distance and the Dice overlap metric. Results showed that the method was able to accurately fit the biventricular model to 3D points and that the deformable model was able to fit all the pathologies while being diffeomorphic. The algorithm took approximately 5 minutes to fit each case, with an average of 52,580 points per case.

The development of a prediction tool to identify cancer patients at high risk for chemotherapy-induced nausea and vomiting

Background

Despite the availability of effective antiemetics and evidence-based guidelines, up to 40% of cancer patients receiving chemotherapy fail to achieve complete nausea and vomiting control. In addition to type of chemotherapy, several patient-related risk factors for chemotherapy-induced nausea and vomiting (CINV) have been identified. To incorporate these factors into the optimal selection of prophylactic antiemetics, a repeated measures cycle-based model to predict the risk of ≥ grade 2 CINV (≥2 vomiting episodes or a decrease in oral intake due to nausea) from days 0 to 5 post-chemotherapy was developed.

Patients and methods

Data from 1198 patients enrolled in one of the five non-interventional CINV prospective studies were pooled. Generalized estimating equations were used in a backwards elimination process with the P-value set at <0.05 to identify the relevant predictive factors. A risk scoring algorithm (range 0–32) was then derived from the final model coefficients. Finally, a receiver-operating characteristic curve (ROCC) analysis was done to measure the predictive accuracy of the scoring algorithm.

Results

Over 4197 chemotherapy cycles, 42.2% of patients experienced ≥grade 2 CINV. Eight risk factors were identified: patient age <60 years, the first two cycles of chemotherapy, anticipatory nausea and vomiting, history of morning sickness, hours of sleep the night before chemotherapy, CINV in the prior cycle, patient self-medication with non-prescribed treatments, and the use of platinum or anthracycline-based regimens. The ROC analysis indicated good predictive accuracy with an area-under-the-curve of 0.69 (95% CI: 0.67–0.70). Before to each cycle of therapy, patients with risk scores ≥16 units would be considered at high risk for developing ≥grade 2 CINV.

Conclusions

The clinical application of this prediction tool will be an important source of individual patient risk information for the oncology clinician and may enhance patient care by optimizing the use of the antiemetics in a proactive manner.

In vitro discrimination of wound-associated bacteria by volatile compound profiling using selected ion flow tube-mass spectrometry

AIMS

To determine if bacterial species responsible for clinically relevant wound infection produce specific volatile profiles that would allow their speciation.

METHODS AND RESULTS

Selected ion flow tube-mass spectrometry (SIFT-MS) in full mass scan mode was used to analyse headspace gases produced by wound-associated bacteria grown in vitro, so as to enable identification of bacterial volatile product ion profiles in the resulting mass spectra. Applying multivariate statistical analysis (hierarchical clustering and principal component analysis) to the resultant mass spectra enabled clear speciation. Moreover, bacterial volatile product ions could be detected from artificially contaminated wound dressing material, although the pattern of product ions detected was influenced by culture conditions.

CONCLUSIONS

Using selected product ions from the SIFT-MS mass spectra it is possible to discriminate wound-associated bacterial species grown under specific in vitro culture conditions.

SIGNIFICANCE AND IMPACT OF THE STUDY

The results of this study have shown that wound-associated bacteria can be discriminated using volatile analysis in vitro and that bacterial volatiles can be detected from wound dressing material. This indicates that volatile analysis of wounds or dressing material to identify infecting microbes has potential and warrants further study.

Advanced magnetic resonance imaging and neuropsychological assessment for detecting brain injury in a prospective cohort of university amateur boxers

BACKGROUND/AIM

The safety of amateur and professional boxing is a contentious issue. We hypothesised that advanced magnetic resonance imaging and neuropsychological testing could provide evidence of acute and early brain injury in amateur boxers.

METHODS

We recruited 30 participants from a university amateur boxing club in a prospective cohort study. Magnetic resonance imaging (MRI) and neuropsychological testing was performed at three time points: prior to starting training; within 48 h following a first major competition to detect acute brain injury; and one year follow-up. A single MRI acquisition was made from control participants. Imaging analysis included cortical thickness measurements with Advanced Normalization Tools (ANTS) and FreeSurfer, voxel based morphometry (VBM), and Tract Based Spatial Statistics (TBSS). A computerized battery of neuropsychological tests was performed assessing attention, learning, memory and impulsivity.

RESULTS

During the study period, one boxer developed seizures controlled with medication while another developed a chronic subdural hematoma requiring neurosurgical drainage. A total of 10 boxers contributed data at to the longitudinal assessment protocol. Reasons for withdrawal were: logistics (10), stopping boxing (7), withdrawal of consent (2), and development of a chronic subdural hematoma (1). No significant changes were detected using VBM, TBSS, cortical thickness measured with FreeSurfer or ANTS, either cross-sectionally at baseline, or longitudinally. Neuropsychological assessment of boxers found attention/concentration improved over time while planning and problem solving ability latency decreased after a bout but recovered after one year.

CONCLUSION

While this neuroimaging and neuropsychological assessment protocol could not detect any evidence of brain injury, one boxer developed seizures and another developed a chronic sub-dural haematoma.

Abstract P4-06-05: Treatment of ESR1 mutant and PIK3CA mutant patient-derived breast cancer xenograft models reveals differential anti-tumor responses to estrogen receptor degraders and PI3K inhibitors in vivo

The phosphoinositide 3-kinase (PI3K) pathway is a key driver of hormone receptor (HR)–positive breast cancer growth and survival. It is estimated that 40-45% of HR+ breast cancers harbor oncogenic mutations in the PIK3CA gene, which encodes the p110α isoform of PI3K. Taselisib (GDC-0032) is a mutant-selective PI3K inhibitor that demonstrates enhanced potency in PIK3CA mutant breast cancer cells and is being developed as a treatment for metastatic breast cancer that targets PIK3CA-mutant, HR-positive, HER2-negative patients. Activating mutations in the ESR1 gene were recently described in metastatic breast cancer. These mutations confer hormone independent growth and may be associated with resistance to aromatase inhibitors. Drugs that selectively bind and antagonize the Estrogen Receptor alpha (ERα) protein and target it for degradation, such as fulvestrant, are referred to as selective estrogen receptor degraders (SERDs). Preclinical activity of the orally bioavailable SERD, GDC-0810, has not been well characterized in ESR1 mutant PDX models. Therefore, our aim was to evaluate the efficacy and pharmacodynamic responses to agents that target ERα and PI3K as monotherapies and in combination, in ESR1 and PIK3CA mutant HR+ breast cancer patient-derived xenograft (PDX) models. We hypothesized that mutational status of ESR1 and PIK3CA may predict the responsiveness of HR+ PDX models to SERDs and PI3K inhibitors in vivo. Characterization of seven PDX models included authentication of hormone receptor status by immunohistochemistry (IHC) and determination of ESR1 and PIK3CA genotype and allele frequency by exome sequencing. For a subset of models that utilize estrogen for growth, mice were supplemented with 17β-estradiol, and cells or tumor fragments were implanted into the fat pad of intact female NOD-SCID or NOD-SCID-IL2Rgamma null mice and treated with fulvestrant, GDC-0810, or taselisib. Both fulvestrant and GDC-0810 were efficacious in ESR1 wild type (WT) and mutant PDX models but to variable degrees ranging from tumor stasis to growth delay, with GDC-0810 resulting in superior single agent activity at relevant clinical exposure in the WHIM20 and WHIM43 ESR1 mutant models. PIK3CA mutations (E542K, E545K, M1004V, and H1047R) were confirmed in six PDX models and PI3K pathway activation verified by strong pS6RP IHC staining. Taselisib induced tumor growth inhibition and tumor regressions in models harboring PIK3CA mutations, and models with no detectable expression of WT p110α were the most sensitive. In the WHIM43 (ESR1 D538G, PIK3CA M1004V), HCI-011 (ESR1 WT, PIK3CA E545K) and HCI-013 (ESR1 Y537S, PIK3CA H1047R) PDX models, combining fulvestrant and taselisib treatment further enhanced tumor growth inhibition with respect to either treatment alone. Our studies demonstrate the diverse anti-tumor responses of HR+ PDX models to SERDs and the PI3K inhibitor taselisib in the context of clinically relevant ESR1 and PIK3CA mutations. Pharmacological and genomic characterization of additional PDX models may aid in strengthening associations between genotype, drug sensitivity and predictive biomarkers of response.

Citation Format: Young A, Crocker L, Cheng E, Lacap J, Hamilton P, Oeh J, Ingalla E, Arrazate A, Hager J, Nannini M, Friedman L, Daemen A, Giltnane J, Sampath D. Treatment of ESR1 mutant and PIK3CA mutant patient-derived breast cancer xenograft models reveals differential anti-tumor responses to estrogen receptor degraders and PI3K inhibitors in vivo [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-06-05.

Abstract P5-04-01: Cell cycle dynamics at single cell level dictates response to CDK4/6 inhibition

This abstract was withdrawn by the authors.