Citations

AimsGastric heterotopia (GH) has been described throughout the gastrointestinal tract. However, the colorectal region is an extremely rare location for it. We describe the clinicopathological features of GH of the colon, rectum and anus.Methods and resultsWe identified 33 cases in 20 males and 13 females (median age = 54 years; range = 4 months–73 years). Sites included the rectum (n = 26), anus (n = 4), ileocaecal junction (n = 1), ascending colon (n = 1) and descending colon (n = 1). Presenting symptoms (n = 27) included haematochezia (41%) and altered bowel habits (4%); 15 patients (55%) were asymptomatic. On colonoscopy (n = 31), all appeared as solitary lesions (median size = 6.5 mm, range = 2–55 mm), either as polyps (61%), raised erythematous patches (23%), an ulcer (10%), within a rectal diverticulum (3%) or a haemorrhoid (3%). Patients were managed by polypectomy. One with an associated carcinoma in the area of GH underwent resection. No morbidity related to GH itself was reported following excision. Histologically, heterotopic gastric mucosa was oxyntic (85%), mixed oxyntic and non‐oxyntic (12%) and not specified (3%) types. In five patients a pyloric gland adenoma (PGA) arose from heterotopic gastric mucosa, two of which contained a focus of invasive adenocarcinoma. One case had associated surface foveolar‐type low‐grade dysplasia. Another had associated adenocarcinoma arising from the heterotopic mucosa. One example harboured Helicobacter pylori organisms.ConclusionsWe highlight the features of GH in the distal GIT – the ‘outlet patch’. Association with PGA, surface dysplasia and adenocarcinoma suggests that lower tract GH can undergo neoplastic transformation.

PurposeTo establish a mathematical model to guide prospective T2‐weighted four‐dimensional magnetic resonance imaging (4DMRI) acquisition and to propose an efficient solution to expedite prospective T2‐weighted 4DMRI acquisition.MethodsProspective T2‐weighted 4DMRI acquisition was characterized by a mathematical model with 4DMRI acquisition time as the objective function and completeness of the image set, acquisition timing, image contrast, and image artifacts as constraints. Given the irregular nature of human respiration, an efficient solution based on the greedy strategy (ESGS) was proposed. The efficiency of the ESGS method was validated using healthy human subjects. Comparisons were made with the previous 4DMRI method incorporating the prefixed‐order respiratory state splitting (PO‐RSS) technique.Results4DMRI image sets acquired using the ESGS and PO‐RSS methods had similar image quality. The average time to acquire a 4DMRI image set covering 60 slices at 10 respiratory states was reduced by 30%, from 13.1 min using the PO‐RSS method to 9.0 min using the ESGS method. It was demonstrated that high‐quality T2‐weighted 4DMRI could be obtained within a reasonable amount of time and all slices within each of the three‐dimensional volumes were indeed acquired at the same respiratory state.ConclusionsThe ESGS method substantially reduces the acquisition time for T2‐weighted 4DMRI, making it ready for clinical evaluation to obtain abdominal tumor motion for radiotherapy treatment planning.

BACKGROUNDEarly treatment failure (ETF) in follicular lymphoma (FL), defined as relapse or progression within 2 years of frontline chemoimmunotherapy, is a newly recognized marker of poor survival and identifies a high‐risk group of patients with an expected 5‐year overall survival (OS) rate of approximately 50%. Transplantation is an established option for relapsed FL, but its efficacy in this specific ETF FL population has not been previously evaluated.METHODSThis study compared autologous hematopoietic stem cell transplantation (auto‐HCT) with either matched sibling donor (MSD) or matched unrelated donor (MUD) allogeneic hematopoietic cell transplantation (allo‐HCT) as the first transplantation approach for patients with ETF FL (age ≥ 18 years) undergoing auto‐HCT or allo‐HCT between 2002 and 2014. The primary endpoint was OS. The secondary endpoints were progression‐free survival, relapse, and nonrelapse mortality (NRM).RESULTSFour hundred forty FL patients had ETF (auto‐HCT, 240; MSD hematopoietic stem cell transplantation [HCT], 105; and MUD HCT, 95). With a median follow‐up of 69 to 73 months, the adjusted probability of 5‐year OS was significantly higher after auto‐HCT (70%) or MSD HCT (73%) versus MUD HCT (49%; P = .0008). The 5‐year adjusted probability of NRM was significantly lower for auto‐HCT (5%) versus MSD (17%) or MUD HCT (33%; P < .0001). The 5‐year adjusted probability of disease relapse was lower with MSD (31%) or MUD HCT (23%) versus auto‐HCT (58%; P < .0001).CONCLUSIONSPatients with high‐risk FL, as defined by ETF, undergoing auto‐HCT for FL have low NRM and a promising 5‐year OS rate (70%). MSD HCT has lower relapse rates than auto‐HCT but similar OS. Cancer 2018;124:2541‐51. © 2018 American Cancer Society.

Abstract In 2011, the National Institute on Aging and Alzheimer's Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer's disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer's Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer's Association Research Framework, Alzheimer's disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six‐stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker‐based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker‐based research should not be considered a template for all research into age‐related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β‐amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.