Purpose:The development of computer-aided diagnostic ͑CAD͒ methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography ͑CT͒ scans. The Lung Image Database Consortium ͑LIDC͒ and Image Database Resource Initiative ͑IDRI͒ completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute ͑NCI͒, further advanced by the Foundation for the National Institutes of Health ͑FNIH͒, and accompanied by the Food and Drug Administration ͑FDA͒ through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ͑"noduleՆ 3 mm," "noduleϽ 3 mm," and "non-noduleՆ 3 mm"͒. In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results:The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "noduleՆ 3 mm" by at least one radiologist, of which 928 ͑34.7%͒ received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions:The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.

He was a co-founder of Seragon, purchased by Genentech/Roche in 2014. J.M. is a science advisor and owns company stock in Scholar Rock. H.C. is an inventor on several patents related to organoid technology. S.W.L. is a co-founder and scientific advisory board member for ORIC Pharm, Blueprint, and Mirimus. He also serves on the scientific advisory board for Constellation, Petra, and PMV and has recently served as a consultant for Forma, Boehringer Ingelheim, and Aileron. J.G.-A. has received support from Medtronic (honorarium for consultancy with Medtronic), Johnson & Johnson (honorarium for delivering a talk), and Intuitive Surgical (honorarium for participating in a webinar by Intuitive Surgical). P.B.R. has received honorarium from Corning to discuss 3D cell culture techniques, has served as a consultant for AstraZeneca, and is a consultant for EMD Serono for work on radiation sensitizers.

The watch-and-wait (WW) strategy aims to spare patients with rectal cancer unnecessary resection. OBJECTIVE To analyze the outcomes of WW among patients with rectal cancer who had a clinical complete response to neoadjuvant therapy.

Rectal cancer is prone to local recurrence and systemic metastasis. However, owing to improvements in TNM staging and treatment, including a more widespread use of rectal MRI and increased radiologist awareness of the key rectal cancer TNM staging features, the mortality rate of rectal cancer has been declining over the past few decades in adults over 50 years of age. Currently, rectal MRI plays a key role in the pre-and posttreatment evaluation of rectal cancer, assisting the multidisciplinary team in tailoring the most appropriate treatment option. The benefits achieved with rectal MRI are strictly dependent on obtaining good-quality images, which is important for the characterization of the main anatomic structures and their relationship with the tumor. In primary staging, rectal MRI helps the radiologist (a) describe the tumor location and morphology, (b) provide its T and N categories, (c) detect the presence of extramural vascular invasion, and (d) identify its relationship with surrounding structures, including the sphincter complex and involvement of the mesorectal fascia. These features help diagnose locally advanced rectal tumors (categories T3c-d, T4, N1, and N2), for which neoadjuvant chemoradiotherapy (CRT) is indicated. In restaging after neoadjuvant CRT, in addition to reassessing the features noted during primary staging, rectal MRI can help in the assessment of treatment response, especially with the emergence of nonsurgical approaches such as "watch and wait." © RSNA, 2019 • radiographics.rsna.org