RECIST measurements in cancer treatment: is there a role for physician assistants? - A pilot study

Background: Decision making in cancer treatment is influenced by standardized RECIST measurements which are subjective to interobserver variability. Aim of this pilot study was to evaluate whether it is feasible to transfer the radiologist's task of RECIST measurements to a trained radiology physician assistant and whether this influences diagnostic performance. Methods: 177 lesions in twenty patients were measured on baseline and two follow-up CTs using RECIST 1.1: Arm A according to routine clinical practice where various radiologists read scans of the referred patients. Arm B according to the experimental setting where a radiology physician assistant performed RECIST measurements of target lesions defined by the radiologists on baseline scans. Performance and agreement were compared between groups. Results: Standard deviation between lesion measurements of arm A and B was four millimeters. Interobserver agreement comparing response category classification was substantial, kappa = 0.77 (95% CI: 0.66 - 0.87). Sensitivity and specificity for the radiology physician assistant for assessing progressive disease were 100% (95% CI: 61% - 100%) and 94% (95% CI: 81% - 98%) respectively. Conclusion: RECIST measurements performed by a paramedic are a feasible alternative to standard practice. This could impact the workflow of radiological units, opening ways to re-assigning radiologists' important, standardized but time consuming tasks to paramedics

Prediction of incomplete primary debulking surgery in patients with advanced ovarian cancer: An external validation study of three models using computed tomography

OBJECTIVE: To test the ability of three prospectively developed computed tomography (CT) models to predict incomplete primary debulking surgery in patients with advanced (International Federation of Gynecology and Obstetrics stages III-IV) ovarian cancer. METHODS: Three prediction models to predict incomplete surgery (any tumor residual >1cm in diameter) previously published by Ferrandina (models A and B) and by Gerestein were applied to a validation cohort consisting of 151 patients with advanced epithelial ovarian cancer. All patients were treated with primary debulking surgery in the Eastern part of the Netherlands between 2000 and 2009 and data were retrospectively collected. Three individual readers evaluated the radiographic parameters and gave a subjective assessment. Using the predicted probabilities from the models, the area under the curve (AUC) was calculated which represents the discriminative ability of the model. RESULTS: The AUC of the Ferrandina models was 0.56, 0.59 and 0.59 in model A, and 0.55, 0.60 and 0.59 in model B for readers 1, 2 and 3, respectively. The AUC of Gerestein's model was 0.69, 0.61 and 0.69 for readers 1, 2 and 3, respectively. AUC values of 0.69 and 0.63 for reader 1 and 3 were found for subjective assessment. CONCLUSIONS: Models to predict incomplete surgery in advanced ovarian cancer have limited predictive ability and their reproducibility is questionable. Subjective assessment seems as successful as applying predictive models. Present prediction models are not reliable enough to be used in clinical decision-making and should be interpreted with caution

FDG-PET provides the best correlation with the tumor specimen compared to MRI and CT in rectal cancer

AbstractPurposeTo compare CT-, MR- and PET-CT based tumor length measurements in rectal cancer with pathology.Patients and MethodsTwenty-six rectal cancer patients underwent both MR and PET-CT imaging followed by short-course radiotherapy (RT 5×5Gy) and surgery within 3days after RT. Tumor length was measured manually and independently by 2 observers on CT, MR and PET. PET-based tumor length measurements were also generated automatically using the signal-to-background-ratio (SBR) method. All measurements were correlated with the tumor length on the pathological specimen.ResultsCT-based measurements did not show a valuable correlation with pathology. MR-based measurements correlated only weakly, but still significantly (Pearson correlation=0.55resp. 0.57; p<0.001). Manual PET measurements reached a good correlation with pathology, but less strong (Pearson correlation 0.72 and 0.76 for the two different observers) than automatic PET-CT based measurements, which provided the best correlation with pathology (Pearson correlation of 0.91 (p<0.001)). Bland–Altman analysis demonstrated in general an overestimation of the tumor diameter using manual measurements, while the agreement of automatic contours and pathology was within acceptable ranges. A direct comparison of the different modalities revealed a significant better precision for PET-based auto-contours as compared to all other measurements.ConclusionAutomatically generated PET-CT based contours show the best correlation with the surgical specimen and thus provide a useful and powerful tool to accurately determine the largest tumor dimension in rectal cancer. This could be used as a quick and reliable tool for target delineation in radiotherapy. However, a 3D volume analysis is needed to confirm these results

Gadofosveset-enhanced MRI for the assessment of rectal cancer lymph nodes: predictive criteria.

PURPOSE: To confirm the use of the nodal signal intensity (SI) and the 'chemical shift' artefact as diagnostic criteria for detecting nodal metastases from rectal cancer on gadofosveset contrast-enhanced MRI. METHODS: Thirty-three patients underwent a non-enhanced and gadofosveset-enhanced 3D-T1W GRE-MRI at 1.5T. For each lymph node, the SI of the middle part of the node (mSI) and white rim of the chemical shift artefact encircling the node (wSI) were measured on the non-enhanced and gadofosveset-enhanced images. Second, the aspect of the chemical shift artefact encircling the nodes was scored using a 4-point scale. Results were compared with histology on a node-by-node basis. RESULTS: 289 nodes (55 N+) were analysed. On gadofosveset-MRI, mSI and wSI were significantly higher for the benign than for the metastatic lymph nodes (p < 0.001). Areas under the ROC curve (AUC) for identification of metastases were 0.74 (mSI) and 0.73 (wSI). The chemical shift criterion rendered an AUC of 0.85. The combination of mSI and the chemical shift criterion resulted in an AUC of 0.88 and the rendered an AUC of 0.86-0.92 when subjectively (visually) assessed by two independent readers. CONCLUSIONS: Benign lymph nodes show significant contrast enhancement after gadofosveset injection, while metastatic nodes do not. The uptake of gadofosveset in the nodes also affects the chemical shift artefact encircling the nodes. Combined assessment of these two features on gadofosveset-enhanced MRI provides a high diagnostic performance for diagnosing metastatic lymph nodes in patients with rectal cancer