This document may be broadly used as a standard reference regarding the current state of the IVOCT imaging modality, intended for researchers and clinicians who use IVOCT and analyze IVOCT data.

To determine the effects of strength training (ST) on muscle quality (MQ, strength/muscle volume of the trained muscle group), 12 healthy older men (69 +/- 3 yr, range 65-75 yr) and 11 healthy older women (68 +/- 3 yr, range 65-73 yr) were studied before and after a unilateral leg ST program. After a warm-up set, four sets of heavy-resistance knee extensor ST exercise were performed 3 days/wk for 9 wk on the Keiser K-300 leg extension machine. The men exhibited greater absolute increases in the knee extension one-repetition maximum (1-RM) strength test (75 +/- 2 and 94 +/- 3 kg before and after training, respectively) and in quadriceps muscle volume measured by magnetic resonance imaging (1,753 +/- 44 and 1, 955 +/- 43 cm3) than the women (42 +/- 2 and 55 +/- 3 kg for the 1-RM test and 1,125 +/- 53 vs. 1,261 +/- 65 cm3 for quadriceps muscle volume before and after training, respectively, in women; both P < 0.05). However, percent increases were similar for men and women in the 1-RM test (27 and 29% for men and women, respectively), muscle volume (12% for both), and MQ (14 and 16% for men and women, respectively). Significant increases in MQ were observed in both groups in the trained leg (both P < 0.05) and in the 1-RM test for the untrained leg (both P < 0.05), but no significant differences were observed between groups, suggesting neuromuscular adaptations in both gender groups. Thus, although older men appear to have a greater capacity for absolute strength and muscle mass gains than older women in response to ST, the relative contribution of neuromuscular and hypertrophic factors to the increase in strength appears to be similar between genders.

Background Evolving dermoscopic terminology motivated us to initiate a new consensus. Objective We sought to establish a dictionary of standardized terms. Methods We reviewed the medical literature, conducted a survey, and convened a discussion among experts. Results Two competitive terminologies exist, a more metaphoric terminology that includes numerous terms and a descriptive terminology based on 5 basic terms. In a survey among members of the International Society of Dermoscopy (IDS) 23.5% (n = 201) participants preferentially use descriptive terminology, 20.1% (n = 172) use metaphoric terminology, and 484 (56.5%) use both. More participants who had been initially trained by metaphoric terminology prefer using descriptive terminology than vice versa (9.7% vs 2.6%, P < .001). Most new terms that were published since the last consensus conference in 2003 were unknown to the majority of the participants. There was uniform consensus that both terminologies are suitable, that metaphoric terms need definitions, that synonyms should be avoided, and that the creation of new metaphoric terms should be discouraged. The expert panel proposed a dictionary of standardized terms taking account of metaphoric and descriptive terms. Limitations A consensus seeks a workable compromise but does not guarantee its implementation. Conclusion The new consensus provides a revised framework of standardized terms to enhance the consistent use of dermoscopic terminology.

Aging does not affect the muscle mass response to either ST or detraining, whereas gender does, as men increased their muscle volume about twice as much in response to ST as did women and experienced larger losses in response to detraining than women. Young men were the only group that maintained muscle volume adaptation after 31 weeks of detraining. Although myostatin genotype may not explain the observed gender difference in the hypertrophic response to ST, a role for myostatin genotype may be indicated in this regard for women, but future studies are needed with larger subject numbers in each genotype group to confirm this observation.

Although advances in information technology in the past decade have come in quantum leaps in nearly every aspect of our lives, they seem to be coming at a slower pace in the field of medicine. However, the implementation of electronic health records (EHR) in hospitals is increasing rapidly, accelerated by the meaningful use initiatives associated with the Center for Medicare & Medicaid Services EHR Incentive Programs. The transition to electronic medical records and availability of patient data has been associated with increases in the volume and complexity of patient information, as well as an increase in medical alerts, with resulting "alert fatigue" and increased expectations for rapid and accurate diagnosis and treatment. Unfortunately, these increased demands on health care providers create greater risk for diagnostic and therapeutic errors. In the near future, artificial intelligence (AI)/machine learning will likely assist physicians with differential diagnosis of disease, treatment options suggestions, and recommendations, and, in the case of medical imaging, with cues in image interpretation. Mining and advanced analysis of "big data" in health care provide the potential not only to perform "in silico" research but also to provide "real time" diagnostic and (potentially) therapeutic recommendations based on empirical data. "On demand" access to high-performance computing and large health care databases will support and sustain our ability to achieve personalized medicine. The IBM Jeopardy! Challenge, which pitted the best all-time human players against the Watson computer, captured the imagination of millions of people across the world and demonstrated the potential to apply AI approaches to a wide variety of subject matter, including medicine. The combination of AI, big data, and massively parallel computing offers the potential to create a revolutionary way of practicing evidence-based, personalized medicine.

Increasingly greater intervals between axial MRI sections result in substantially reduced agreement with a criterion measure of MV. The use of one axial section results in relatively higher error and thus should be used only when large effect sizes are expected.

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The results indicate that neither age nor gender affects muscle volume response to whole-body ST. Muscle volume, rather than muscle CSA, is recommended for studying muscle mass responses to ST.