Background: The purpose of this study was to investigate the value of wavelet-transformed radiomic MRI in predicting the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) for patients with locally advanced breast cancer (LABC). Methods: Fifty-five female patients with LABC who underwent contrast-enhanced MRI (CE-MRI) examination prior to NAC were collected for the retrospective study. According to the pathological assessment after NAC, patient responses to NAC were categorized into pCR and non-pCR. Three groups of radiomic textures were calculated in the segmented lesions, including (1) volumetric textures, (2) peripheral textures, and (3) wavelet-transformed textures. Six models for the prediction of pCR were Model I: group (1), Model II: group (1) + (2), Model III: group (3), Model IV: group (1) + (3), Model V: group (2) + (3), and Model VI: group (1) + (2) + (3). The performance of predicting models was compared using the area under the receiver operating characteristic (ROC) curves (AUC). Results: The AUCs of the six models for the prediction of pCR were 0.816 ± 0.033 (Model I), 0.823 ± 0.020 (Model II), 0.888 ± 0.025 (Model III), 0.876 ± 0.015 (Model IV), 0.885 ± 0.030 (Model V), and 0.874 ± 0.019 (Model VI). The performance of four models with wavelet-transformed textures (Models III, IV, V, and VI) was significantly better than those without wavelet-transformed textures (Model I and II). In addition, the inclusion of volumetric textures or peripheral textures or both did not result in any improvements in performance. Conclusions: Wavelet-transformed textures outperformed volumetric and/or peripheral textures in the radiomic MRI prediction of pCR to NAC for patients with LABC, which can potentially serve as a surrogate biomarker for the prediction of the response of LABC to NAC.

To develop a three-dimensional (3D) segmentation and computerized volumetry technique for use in the assessment of neurofibromatosis and to assess the ability of this technique to aid in the calculation of tumor burden in patients with neurofibromatosis types 1 and 2 (NF1 and NF2, respectively) and schwannomatosis detected with whole-body magnetic resonance (MR) imaging. Institutional review board approval and written informed consent were obtained for this prospective HIPAA-compliant study. Fifty-two subjects (27 women, 25 men; mean age, 42 years +/- 15 [standard deviation]; age range, 24-86 years) underwent whole-body MR imaging performed with coronal short inversion time inversion-recovery (STIR) sequences. Whole-body tumor burden was estimated with a 3D segmentation method (the dynamic-threshold [DT] level set method) in 29 subjects (16 with NF1, six with NF2, and seven with schwannomatosis) in whom at least one nerve sheath tumor was reliably identified on MR images. Fifty tumors (25 plexiform and 25 discrete tumors) were randomly selected and subjected to manual and computerized volumetry to assess reliability. Ten plexiform tumors 5 cm or larger in diameter were retrospectively selected and segmented with three initialization methods for computerized volumetry and manually contoured by three radiologists to assess repeatability. Bland-Altman analysis was performed, and intraclass correlation coefficients (ICCs) were calculated. A total of 398 nerve sheath tumors (185 plexiform and 213 discrete tumors) were identified in 29 subjects. Volumetric measurements obtained with the computerized method and manual contouring were highly correlated (r(ICC) = 0.99). Bland-Altman analysis showed that computerized volumetry had a mean difference of -2.6% compared with manual volumetry. The repeatability coefficient of the computerized scheme was +/-5% compared with +/-30% for manual contouring. This 3D segmentation and computerized volumetry technique is reliable relative to manual segmentation and has the advantage of being less labor intensive and more repeatable. This technique can be paired with whole-body MR imaging to determine tumor burden in patients with neurofibromatosis. http://radiology.rsnajnls.org/cgi/content/full/250/3/665/DC1

The objective, accurate, and standardized evaluation of tumor response to treatment is an indispensable procedure in clinical oncology. Compared to manual measurement, computer‐assisted linear measurement can significantly improve the accuracy and reproducibility of tumor burden quantification. For irregular‐shaped and infiltrating or diffuse tumors, which are difficult to quantify by linear measurement, computer‐assisted volumetric measurement may provide a more objective and sensitive quantification to evaluate tumor response to treatment than linear measurement does. In the evaluation of tumor response to novel oncologic treatments such as targeted therapy, changes in overall tumor size do not necessarily reflect tumor response to therapy due to the presence of internal necrosis or hemorrhages. This leads to a new generation of imaging biomarkers to evaluate tumor response by using texture analysis methods, also called radiomics. Computer‐assisted texture analysis technology offers a more comprehensive and in‐depth imaging biomarker to evaluate tumor response. The application of computer‐assisted quantitative imaging analysis techniques not only reduces the inaccuracy and improves the reliability in tumor burden quantification, but facilitates the development of more comprehensive and intelligent approaches to evaluate treatment response, and hence promotes precision imaging in the evaluation of tumor response in clinical oncology. This article summarizes the state‐of‐the‐art technical developments and clinical applications of quantitative imaging analysis in evaluation of tumor response in clinical oncology.

The development of a dual-energy electronic cleansing scheme that minimizes cleansing artifacts with use of the material decomposition capability of dual-energy CT colonography is described. Electronic cleansing (EC) is an emerging technique for the removal of tagged fecal materials at fecal-tagging computed tomographic (CT) colonography. However, existing EC methods may generate vario...