A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics

OBJECTIVES: To determine the value of a deep learning masked (DLM) auto-fixed volume of interest (VOI) segmentation method as an alternative to manual segmentation for radiomics-based diagnosis of clinically significant (CS) prostate cancer (PCa) on biparametric magnetic resonance imaging (bpMRI). MATERIALS AND METHODS: This study included a retrospective multi-center dataset of 524 PCa lesions (of which 204 are CS PCa) on bpMRI. All lesions were both semi-automatically segmented with a DLM auto-fixed VOI method (averaging < 10 s per lesion) and manually segmented by an expert uroradiologist (averaging 5 min per lesion). The DLM auto-fixed VOI method uses a spherical VOI (with its center at the location of the lowest apparent diffusion coefficient of the prostate lesion as indicated with a single mouse click) from which non-prostate voxels are removed using a deep learning-based prostate segmentation algorithm. Thirteen different DLM auto-fixed VOI diameters (ranging from 6 to 30 mm) were explored. Extracted radiomics data were split into training and test sets (4:1 ratio). Performance was assessed with receiver operating characteristic (ROC) analysis. RESULTS: In the test set, the area under the ROC curve (AUCs) of the DLM auto-fixed VOI method with a VOI diameter of 18 mm (0.76 [95% CI: 0.66-0.85]) was significantly higher (p = 0.0198) than that of the manual segmentation method (0.62 [95% CI: 0.52-0.73]). CONCLUSIONS: A DLM auto-fixed VOI segmentation can provide a potentially more accurate radiomics diagnosis of CS PCa than expert manual segmentation while also reducing expert time investment by more than 97%. KEY POINTS: * Compared to traditional expert-based segmentation, a deep learning mask (DLM) auto-fixed VOI placement is more accurate at detecting CS PCa. * Compared to traditional expert-based segmentation, a DLM auto-fixed VOI placement is faster and can result in a 97% time reduction. * Applying deep learning to an auto-fixed VOI radiomics approach can be valuable

Evaluation of National Surgical Practice for Lateral Lymph Nodes in Rectal Cancer in an Untrained Setting

Background: Involved lateral lymph nodes (LLNs) have been associated with increased local recurrence (LR) and ipsi-lateral LR (LLR) rates. However, consensus regarding the indication and type of surgical treatment for suspicious LLNs is lacking. This study evaluated the surgical treatment of LLNs in an untrained setting at a national level. Methods: Patients who underwent additional LLN surgery were selected from a national cross-sectional cohort study regarding patients undergoing rectal cancer surgery in 69 Dutch hospitals in 2016. LLN surgery consisted of either ‘node-picking’ (the removal of an individual LLN) or ‘partial regional node dissection’ (PRND; an incomplete resection of the LLN area). For all patients with primarily enlarged (≥7 mm) LLNs, those undergoing rectal surgery with an additional LLN procedure were compared to those undergoing only rectal resection. Results: Out of 3057 patients, 64 underwent additional LLN surgery, with 4-year LR and LLR rates of 26% and 15%, respectively. Forty-eight patients (75%) had enlarged LLNs, with corresponding recurrence rates of 26% and 19%, respectively. Node-picking (n = 40) resulted in a 20% 4-year LLR, and a 14% LLR after PRND (n = 8; p = 0.677). Multivariable analysis of 158 patients with enlarged LLNs undergoing additional LLN surgery (n = 48) or rectal resection alone (n = 110) showed no significant association of LLN surgery with 4-year LR or LLR, but suggested higher recurrence risks after LLN surgery (LR: hazard ratio [HR] 1.5, 95% confidence interval [CI] 0.7–3.2, p = 0.264; LLR: HR 1.9, 95% CI 0.2–2.5, p = 0.874). Conclusion: Evaluation of Dutch practice in 2016 revealed that approximately one-third of patients with primarily enlarged LLNs underwent surgical treatment, mostly consisting of node-picking. Recurrence rates were not significantly affected by LLN surgery, but did suggest worse outcomes. Outcomes of LLN surgery after adequate training requires further research.</p

Short-term effect of preoperative intravenous iron therapy in colorectal cancer patients with anemia: Results of a cohort study

BACKGROUND: In the treatment of preoperative anemia, which is associated with increased postoperative morbidity, iron supplementation can replace blood transfusion and erythropoiesis-stimulating agents. The aim of this study was to assess the efficacy of preoperative intravenous (IV) iron infusion in optimizing hemoglobin (Hb) levels in anemic colorectal cancer patients. STUDY DESIGN AND METHODS: A retrospective cohort study was performed on patients who underwent surgery for colorectal cancer between 2010 and 2016 in a single teaching hospital. The primary outcome measure, the change in Hb level, was assessed by comparing anemic patients receiving usual care (UC; i.e. no iron therapy and no blood transfusion) with anemic patients receiving IV iron therapy (no blood transfusion). RESULTS: A total of 758 patients with colorectal cancer were eligible, of whom 318 (41.9%) had anemia. The IV and the UC groups included 52 and 153 patients with mean Hb levels at diagnosis of 6.3 and 6.9 mmol/L, respectively. In the IV group, preoperative Hb level was significantly increased compared to the UC group (0.65 mmol/L vs. 0.10 mmol/L, p<0.001). High increase in Hb level after iron infusion was associated with initial higher transferrin and lower ferritin levels (high vs. poor responders: median transferrin 2.9 g/L vs. 2.7 g/L, median ferritin 12 μg/L vs. 27 μg/L). CONCLUSION: Implementation of IV iron therapy in anemic colorectal cancer patients leads to a distinct increase of preoperative Hb level. IV iron therapy is most effective in patients presenting with more severe anemia, and with higher transferrin and lower ferritin levels, markers for an absolute iron deficiency (ID), compared to functional ID

The effects of computed tomography with iterative reconstruction on solid pulmonary nodule volume quantification.

BackgroundThe objectives of this study were to evaluate the influence of iterative reconstruction (IR) on pulmonary nodule volumetry with chest computed tomography (CT).MethodsTwenty patients (12 women and 8 men, mean age 61.9, range 32-87) underwent evaluation of pulmonary nodules with a 64-slice CT-scanner. Data were reconstructed using filtered back projection (FBP) and IR (Philips Healthcare, iDose(4)-levels 2, 4 and 6) at similar radiation dose. Volumetric nodule measurements were performed with semi-automatic software on thin slice reconstructions. Only solid pulmonary nodules were measured, no additional selection criteria were used for the nature of nodules. For intra-observer and inter-observer variability, measurements were performed once by one observer and twice by another observer. Algorithms were compared using the concordance correlation-coefficient (pc) and Friedman-test, and post-hoc analysis with the Wilcoxon-signed ranks-test with Bonferroni-correction (significance-level pResultsSeventy-eight nodules were present including 56 small nodules (volumeConclusionsMeasurements of solid pulmonary nodule volume measured with standard-FBP were comparable with IR, regardless of the IR-level and no significant differences between measured volumes of both small and large solid nodules were found

Agreement of small pulmonary nodule measurements.

<p>Bland-Altman plots of CT measured nodule volume at filtered back projection (FBP) and iterative reconstruction (iDose⁴ level 2 (A), 4 (B) and 6 (C)) for small nodules. The horizontal axis shows the mean value of the measured nodule volume with FBP and iterative reconstruction. The vertical axis shows the difference between the measured nodule volume with FBP and iterative reconstruction. <i>FBP</i> Filtered back projection; <i>L2</i> Level 2; <i>L4</i> Level 4; <i>L6</i> Level 6.</p

Axial CT images of a small pulmonary nodule.

<p>Measured volumes were 112.2 mm³ (A, FBP), 113.2 mm³ (B, iDose⁴ level 2), 113.5 mm³ (C, iDose⁴ level 4), and 115.1 mm³ (D, iDose⁴ level 6).</p

Intra-observer and inter-observer variability.

<p>P-values and concordance correlation coefficients (p_c-values) of measured pulmonary nodule volumes using filtered back projection (FBP) and iterative reconstruction (iDose⁴ level 2, 4 and 6) by two observers.</p><p><i>p-value</i> Based on Wilcoxon signed ranks test; <i>p_c-value</i> Concordance correlation coefficient; <i>FBP</i> Filtered back projection; <i>L2</i> Level 2; <i>L4</i> Level 4; <i>L6</i> Level 6; <i>Observer 1–1</i> First measurement by first observer; <i>Observer 1–2</i> Second measurement by first observer; <i>Observer 2</i> Measurement by second observer.</p