‘Out of house’ virtual surgical planning for mandible reconstruction after cancer resection: is it oncologically safe?

The purpose of this study was to investigate whether the time delay between ‘out of house’ proprietary virtual surgical planning (OH-VSP) of the mandibular resection for oral cancer and the actual surgery results in compromised margins and oncological disadvantage for the patient. Outcomes of patients who had OH-VSP of their mandibular resection and reconstruction were compared with those of patients who had the same surgery using a conventional non-VSP approach. The groups were similar in patient demographics, tumour stage and size, nodal status, and reconstruction complexity. VSP resulted in a significant reduction in operating time (P < 0.01). VSP did not affect bony (P = 0.49) or soft tissue (P = 0.22) margin status. In summary, VSP reduced the operating theatre time, and despite the time interval between bony resection planning and surgery, there was no compromise to the oncological safety of the operation.     

Dynamic instability during post-stroke hemiparetic walking

Falls and fall-related injuries cause extremely costly and potentially fatal health problems in people post-stroke. However, there is no global indicator of walking instability for detecting which individuals will have increased risk of falls. The purposes of this study were to directly quantify walking stability in stroke survivors and neurologically intact controls and to determine which stability measures would reveal the changes in walking stability following stroke. This study thus provided an initial step to establish objective measures for identifying potential fallers. Nine post-stroke individuals and nine controls walked on a treadmill at four different speeds. We computed short-term local divergence exponent (LDE) and maximum Floquet multiplier (maxFM) of the trunk motion, average and variability of dynamic margins of stability (MOS) and step spatiotemporal measures. Post-stroke individuals demonstrated larger short-term LDE (p = 0.002) and maxFM (p = 0.041) in the mediolateral (ML) direction compared to the controls but remained orbitally stable (maxFM < 1). In addition, post-stroke individuals walked with greater average step width (p = 0.003) but similar average ML MOS (p = 0.154) compared to the controls. Post-stroke individuals also exhibited greater variability in all MOS and step measures (all p < 0.005). Our findings indicate that post-stroke individuals walked with greater local and orbital instability and gait variability than neurologically intact controls. The results suggest that short-term LDE of ML trunk motion and the variability of MOS and step spatiotemporal measures detect the changes in walking stability associated with stroke. These stability measures may have the potential for identifying those post-stroke individuals at increased risk of falls.     

A prediction model for treatment decisions in high-grade extremity soft-tissue sarcomas: Personalised sarcoma care (PERSARC)

BackgroundTo support shared decision-making, we developed the first prediction model for patients with primary soft-tissue sarcomas of the extremities (ESTS) which takes into account treatment modalities, including applied radiotherapy (RT) and achieved surgical margins. The PERsonalised SARcoma Care (PERSARC) model, predicts overall survival (OS) and the probability of local recurrence (LR) at 3, 5 and 10 years.AimDevelopment and validation, by internal validation, of the PERSARC prediction model.MethodsThe cohort used to develop the model consists of 766 ESTS patients who underwent surgery, between 2000 and 2014, at five specialised international sarcoma centres. To assess the effect of prognostic factors on OS and on the cumulative incidence of LR (CILR), a multivariate Cox proportional hazard regression and the Fine and Gray model were estimated. Predictive performance was investigated by using internal cross validation (CV) and calibration. The discriminative ability of the model was determined with the C-index.ResultsMultivariate Cox regression revealed that age and tumour size had a significant effect on OS. More importantly, patients who received RT showed better outcomes, in terms of OS and CILR, than those treated with surgery alone. Internal validation of the model showed good calibration and discrimination, with a C-index of 0.677 and 0.696 for OS and CILR, respectively.ConclusionsThe PERSARC model is the first to incorporate known clinical risk factors with the use of different treatments and surgical outcome measures. The developed model is internally validated to provide a reliable prediction of post-operative OS and CILR for patients with primary high-grade ESTS.Level of significancelevel III.     

Inclusion of geometric uncertainties in treatment plan evaluation

: To correctly evaluate realistic treatment plans in terms of absorbed dose to the clinical target volume (CTV), equivalent uniform dose (EUD), and tumor control probability (TCP) in the presence of execution (random) and preparation (systematic) geometric errors.

: The dose matrix is blurred with all execution errors to estimate the total dose distribution of all fractions. To include preparation errors, the CTV is randomly displaced (and optionally rotated) many times with respect to its planned position while computing the dose, EUD, and TCP for the CTV using the blurred dose matrix. Probability distributions of these parameters are computed by combining the results with the probability of each particular preparation error. We verified the method by comparing it with an analytic solution. Next, idealized and realistic prostate plans were tested with varying margins and varying execution and preparation error levels.

: Probability levels for the minimum dose, computed with the new method, are within 1% of the analytic solution. The impact of rotations depends strongly on the CTV shape. A margin of 10 mm between the CTV and planning target volume is adequate for three-field prostate treatments given the accuracy level in our department; i.e., the TCP in a population of patients, TCP_pop, is reduced by less than 1% due to geometric errors. When reducing the margin to 6 mm, the dose must be increased from 80 to 87 Gy to maintain the same TCP_pop. Only in regions with a high-dose gradient does such a margin reduction lead to a decrease in normal tissue dose for the same TCP_pop. Based on a rough correspondence of 84% minimum dose with 98% EUD, a margin recipe was defined. To give 90% of patients at least 98% EUD, the planning target volume margin must be approximately 2.5 Σ + 0.7 σ − 3 mm, where Σ and σ are the combined standard deviations of the preparation and execution errors. This recipe corresponds accurately with 1% TCP_pop loss for prostate plans with clinically reasonable values of Σ and σ.

: The new method computes in a few minutes the influence of geometric errors on the statistics of target dose and TCP_pop in clinical treatment plans. Too small margins lead to a significant loss of TCP_pop that is difficult to compensate for by dose escalation.     

Ductal carcinoma in-situ: an update for clinical practice

Introduction

Ductal carcinoma in-situ (DCIS) is a heterogeneous entity with an elusive natural history. The objective of radiological, histological and molecular characterisation remains to reliably predict the biological behaviour and optimise clinical management strategies. Increases in diagnostic frequency have followed the introduction of mammographic screening and increased utility of magnetic resonance imaging. However, progress remains limited in distinguishing non-progressive incidental lesions from their progressive and clinically relevant counterparts. This article reviews current management strategies for DCIS in the context of recent randomized trials, including the role of sentinel lymph node biopsy (SLNB), adjuvant radiotherapy (RT) and endocrine treatment.

Methods

Literature review facilitated by Medline, PubMed, Embase and Cochrane databases.

Results

DCIS should be managed in the context of a multidisciplinary team. Local control depends upon adequate surgical clearance with margins of at least 2 mm. SLNB is not routinely indicated and should be reserved for those with concurrent or recurrent invasive disease. SLNB can be considered in patients undergoing mastectomy (MX) and those with risk factors for invasion such as palpability, comedo morphology, necrosis or recurrent disease. RT following BCS significantly reduces local recurrence (LR), particularly in those at high-risk. There remains a lack of level-1 evidence supporting the omission of adjuvant RT in selected low-risk cases. Large, multi-centric or recurrent lesions (particularly in cases of prior RT) should be treated by MX with the opportunity for immediate reconstruction. Adjuvant Tamoxifen may reduce the risk of LR in selected cases with hormone sensitive disease.

Conclusion

Further research is required to determine the role of contemporary RT regimes and endocrine therapies. Biological profiling and molecular analysis represent an opportunity to improve our understanding of the tumour biology of this condition and rationalise its treatment. Reliable identification of low-risk lesions could allow treatment to be less radical or safely omitted.     

Risk factors for the presence of residual disease in women after partial mastectomy for invasive breast cancer: A single institution experience

BackgroundWe hypothesize that in addition to specimen margin widths other clinical variables may help predict the presence of residual disease in the lumpectomy bed.MethodsPatients with Stage I-III invasive breast cancer (BC) who underwent partial mastectomy (PM) and re-excision from July 2010–June 2015 were retrospectively reviewed. Bivariate analyses were conducted using two-sample t-tests for continuous variables and Fisher's Exact tests for categorical variables. A multivariate logistic regression was then performed on significant bivariate analyses variables.Resultsne-hundred and eighty-four patients were included in our analysis; 47% had residual disease on re-excision, while 53% had no residual disease. Tumor and nodal stage, operation type, type of disease present at margin, and number of positive margins were significantly associated with residual disease. On multivariate logistic regression, DCIS alone at the margin (p = 0.02), operation type (PM with cavity margins) (p = 0.003), and number of positive margins (3 or more) (p < 0.001) remained predictive of residual disease at re-excision.ConclusionBased on a more comprehensive review of the initial pathology, there are additional factors that can help predict the likelihood of finding residual disease and help guide the surgeon in the decision for re-excision.