Tissue modeling schemes in low energy breast brachytherapy

Breast tissue is heterogeneous and is mainly composed of glandular (G) and adipose (A) tissues. The proportion of G versus A varies considerably among the population. The absorbed dose distributions in accelerated partial breast irradiation therapy with low energy photon brachytherapy sources are very sensitive to tissue heterogeneities. Current clinical algorithms use the recommendations of the AAPM TG43 report which approximates the human tissues by unit density water. The aim of this study is to investigate various breast tissue modeling schemes for low energy brachytherapy. A special case of breast permanent seed implant is considered here. Six modeling schemes are considered. Uniform and non-uniform water breast (UWB and NUWB) consider the density but neglect the effect of the composition of tissues. The uniform and the non-uniform G/A breast (UGAB and NUGAB) as well the age-dependent breast (ADB) models consider the effect of the composition. The segmented breast tissue (SBT) method uses a density threshold to distinguish between G and A tissues. The PTV D(90) metric is used for the analysis and is based on the dose to water (D(90(w,m))). D(90(m,m)) is also reported for comparison to D(90(w,m)). The two-month post-implant D(90(w,m)) averaged over 38 patients is smaller in NUWB than in UWB by about 4.6% on average (ranging from 5% to 13%). Large average differences of G/A breast models with TG43 (17% and 26% in UGAB and NUGAB, respectively) show that the effect of the chemical composition dominates the effect of the density on dose distributions. D(90(w,m)) is 12% larger in SBT than in TG43 when averaged. These differences can be as low as 4% or as high as 20% when the individual patients are considered. The high sensitivity of dosimetry on the modeling scheme argues in favor of an agreement on a standard tissue modeling approach to be used in low energy breast brachytherapy. SBT appears to generate the most geometrically reliable breast tissue models in this report.     

Survival benefit of adding Hyperthermic IntraPEritoneal Chemotherapy (HIPEC) at the different time-points of treatment of ovarian cancer: review of evidence

The standard treatment for advanced ovarian cancer consists in complete cytoreductive surgery (CRS) and intravenous combination chemotherapy with a platinum compound and a taxane. Although response rates to initial therapy are high, many patients will recur and die of peritoneal carcinomatosis. The addition of Hyperthermic IntraPEritoneal Chemotherapy (HIPEC) to the standard therapy aims at increasing survival by reducing peritoneal recurrence. This review describes the survival results of HIPEC at the different time-points of the treatment of ovarian cancer: at upfront CRS, at interval CRS, at consolidation CRS after complete response to initial therapy, at secondary CRS after incomplete response, at salvage CRS for recurrence and as palliative treatment without CRS for unresectable ovarian cancer with chemotherapy resistant ascites. The available evidence suggests that a potential survival benefit of adding HIPEC may be largest in the settings of secondary CRS for stage III ovarian cancer and salvage CRS for recurrent ovarian cancer, two time-points representing failure of initial standard therapy. There is much less evidence for a potential benefit of HIPEC for less advanced stages (I-II) and for earlier time-points in the treatment of ovarian cancer (upfront, interval and consolidation). Postoperative mortality is not higher after CRS and HIPEC (0.7%) than after CRS only (1.4%). Four randomised trials are ongoing and their results are eagerly awaited. Palliative HIPEC without CRS might be used more in patients with incapacitating ascites due to recurrent ovarian cancer which has become resistant to systemic chemotherapy.     

Neoadjuvant treatment of breast cancer: implications for the pathologist

These past few years, neoadjuvant strategy has taken an increasing place in the management of breast cancer patients. This strategy is mainly indicated to obtain a tumour bulk regression allowing a breast conserving surgery in patients that otherwise would have undergone mastectomy. Of note, development of new chemotherapy agents and targeted therapies has critically helped in the progress of neoadjuvant strategy as it is currently associated with better pathological response rates. In this context, the pathologist is at the crossroad of this multidisciplinary process. First, he provides on the initial core needle biopsy the tumour pathological characteristics that are critical for the choice of treatment strategy, i.e. histological type, histological grade, proliferative activity (mitotic count and Ki67/MIB1 index labeling), hormone receptor status (oestrogen receptor and progesterone receptor) and HER2 status. Secondly, the pathologist evaluates the pathological response and the status of surgical margins with regards to the residual tumour on the surgical specimen after neoadjuvant treatment. These parameters are important for the management of the patient, since it has been shown that complete pathological response is associated with improved disease free survival. Several grading systems are used to assess the pathological response in breast and axillary lymph nodes. The most frequently used in France are currently the systems described by Sataloff et al. and Chevallier et al. In this review, we detail the different steps involving the pathologist in neoadjuvant setting, with special regards to the quality process and future perspectives such as emerging predictive biomarkers.     

SUVmax reduction improves early prognosis value of interim positron emission tomography scans in diffuse large B-cell lymphoma

The prognostic value of interim positron emission tomography (PET) interpreted according to visual criteria is a matter of debate in diffuse large B-cell lymphoma (DLBCL). Maximal standardized uptake value reduction (ΔSUVmax) may better predict outcome. To compare the prognostic value of both methods, we analyzed PET done at baseline (PET0) and after 2 (PET2) and 4 (PET4) cycles in 85 patients with high-risk DLBCL enrolled on a prospective multicenter trial. All images were centrally reviewed and interpreted visually according to the International Harmonization Project criteria and by computing ΔSUVmax between PET0 and PET2 (ΔSUVmaxPET0-2) or PET4 (ΔSUVmaxPET0-4). Optimal cutoff to predict progression or death was 66% for ΔSUVmaxPET0-2 and 70% for ΔSUVmaxPET0-4. Outcomes did not differ significantly whether PET2 and PET4 were visually positive or negative. Inversely, ΔSUVmaxPET0-2 analysis (> 66% vs ≤ 66%) identified patients with significantly different 2-year progression-free survival (77% vs 57%; P = .0282) and overall survival (93% vs 60%; P < .0001). ΔSUVmaxPET0-4 analysis (> 70% vs ≤ 70%) seemed even more predictive for 2-year progression-free survival (83 vs 40%; P < .0001) and overall survival (94% vs 50%; P < .0001). ΔSUVmax analysis of sequential interim PET is feasible for high-risk DLBCL and better predicts outcome than visual analysis. The trial was registered at http://clinicaltrials.gov as NCT00498043.     

Single-cell gene-expression profiling reveals qualitatively distinct CD8 T cells elicited by different gene-based vaccines

CD8 T cells play a key role in mediating protective immunity against selected pathogens after vaccination. Understanding the mechanism of this protection is dependent upon definition of the heterogeneity and complexity of cellular immune responses generated by different vaccines. Here, we identify previously unrecognized subsets of CD8 T cells based upon analysis of gene-expression patterns within single cells and show that they are differentially induced by different vaccines. Three prime-boost vector combinations encoding HIV Env stimulated antigen-specific CD8 T-cell populations of similar magnitude, phenotype, and functionality. Remarkably, however, analysis of single-cell gene-expression profiles enabled discrimination of a majority of central memory (CM) and effector memory (EM) CD8 T cells elicited by the three vaccines. Subsets of T cells could be defined based on their expression of Eomes, Cxcr3, and Ccr7, or Klrk1, Klrg1, and Ccr5 in CM and EM cells, respectively. Of CM cells elicited by DNA prime-recombinant adenoviral (rAd) boost vectors, 67% were Eomes(-) Ccr7(+) Cxcr3(-), in contrast to only 7% and 2% stimulated by rAd5-rAd5 or rAd-LCMV, respectively. Of EM cells elicited by DNA-rAd, 74% were Klrk1(-) Klrg1(-)Ccr5(-) compared with only 26% and 20% for rAd5-rAd5 or rAd5-LCMV. Definition by single-cell gene profiling of specific CM and EM CD8 T-cell subsets that are differentially induced by different gene-based vaccines will facilitate the design and evaluation of vaccines, as well as enable our understanding of mechanisms of protective immunity.