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This is only one of the latest in a long, dismal history of IT projects gone awry This is a list of software (both commercial and otherwise) available for 3D reconstruction of MRI, CT, confocal, and serial-section data for medical/life. It is difficult to imagine that cellphones caused these frontal- lobe tumors: how, or why, would a phone’s toxicity have skipped over the area nearest to it and caused a tumor in a distant site? Most epidemiologists and biologists do not find such a tissue- skipping mechanism plausible and most doubt that there is any causal link between frontal tumors and phones. But a populationwide survey, you might argue, has its limits. The carcinogenic effect of a phone might be so subtle that it never registers in such a survey. A phone may cause cancer after a long lag time — say, 2. The survey data could be incomplete or of poor quality, thus limiting an epidemiologist’s ability to ever find a discernible link. Epidemiologists, fortunately, possess a more powerful alternative to uncover a link between a risk factor and cancer. Consider the classic studies that finally revealed the association between tobacco and lung cancer. In the late 1. 94. Sir Richard Doll and Sir Austin Bradford Hill, working in London, and Ernst Wynder and Evarts Graham, working in St. Louis, began investigating whether tobacco smoking increased the risk of lung cancer. Working independently, Doll and Hill, and Wynder and Graham, devised remarkably similar kinds of surveys to reveal a possible link. Using hospital records, they identified a “case” group (a cohort of men with lung cancer) and a matched group of men without lung cancer (a “control” group). The case group and the control group were asked the same questions, including how much and how often they smoked. By comparing the responses of lung- cancer- afflicted men and nonafflicted men, the two teams of researchers stumbled on a striking association: men with lung cancer had a much longer and deeper history of smoking compared with men without lung cancer. What if you perform a similar case- control study with cellphones — comparing men and women suffering from brain cancer (cases) and men and women without brain cancer (controls) — looking at their past cellphone use? In 2. 01. 0, an enormous study, called Interphone, tried to accomplish this task. Setting up the study took years: Interphone recruited participants in 1. The study was coordinated by the World Health Organization and financed primarily by the European Union and cellphone companies, although by agreement industry representatives did not have privileged access to results before publication. Trials like Interphone are undertaken in the hope that they cleanse the field of doubts. In fact, Interphone achieved just the opposite effect: it ignited even more puzzling questions. Over all, the study found little evidence for an association between brain tumors and cellphones. But when the two cohorts — cancer and no cancer — were subdivided according to the frequency of cellphone use, bizarre results emerged. To start with, there was an apparently decreased risk of brain tumors in regular phone users, compared with rare users or nonusers. In other words, regular cellphone use seemed to reduce the risk of brain tumors. In stark contrast, very high cellphone use (measured as a user’s cumulative call time) seemed to increase the risk of a particular subtype of brain tumor. Needless to say, it is biologically implausible that these results are simultaneously true: how can regular cellphone use protect against cancer while frequent phone use increases risk? To most epidemiologists, including the authors of Interphone, the results point to a systemic flaw in the trial. Similar case- control studies have examined other kinds of brain tumors, including a rare nonmalignant tumor called an acoustic neuroma. Here, too, the trials have been contradictory. Multiple studies found no association with cellphone use. In contrast, one study from Sweden found an increased risk in people who used their phones for more than 1. How can trials that seem so similar at face value arrive at such disparate and contradictory results? The most likely common problem is bias — built into the very structure of these trials. In a case- control trial, patients are asked to remember their risk of exposure after the fact. In the Interphone study, for instance, participants were asked to recall the extent of their phone use years or even decades in their past. And memory, we now know, is a terribly slippery entity. A patient’s memory of his or her past is a particularly charged and malleable thing; burned into David Reynard’s memory, poignantly, is the shape of the cellphone in his wife’s hand and the imprint of the cancer on her brain. In fact, our memories turn out to be systematically fragile, especially when we are summoning our past to understand illness. In 1. 99. 3, a Harvard researcher named Edward Giovannucci set out to measure this phenomenon. Giovannucci identified a cohort of women with breast cancer and an age- matched cohort without cancer, and asked each group about its previous dietary habits. The survey produced a reliable and reasonable trend: women with breast cancer were more likely to have consumed diets high in fat. But the women in Giovannucci’s study had also completed a dietary survey before their diagnosis of breast cancer. How did a woman’s memory of her diet compare with the actual diet that she recorded before her cancer diagnosis? 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