Cervical mobilization and manipulation are frequently used to treat patients diagnosed with cervicogenic headache (CEH); however, there is conflicting evidence on the efficacy of these manual therapy techniques. The purpose of this review is to investigate the effects of cervical mobilization and manipulation on pain intensity and headache frequency, compared to traditional physical therapy interventions in patients diagnosed with CEH. A total of 66 relevant studies were originally identified through a review of the literature, and the 25 most suitable articles were fully evaluated via a careful review of the text. Ultimately, 10 studies met the inclusion criteria: (1) randomized controlled trial (RCT) or open RCT; the study contained at least two separate groups of subjects that were randomly assigned either to a cervical spine mobilization or manipulation or a group that served as a comparison; (2) subjects must have had a diagnosis of CEH; (3) the treatment group received either spinal mobilization or spinal manipulation, while the control group received another physical therapy intervention or placebo control; and (4) the study included headache pain and frequency as outcome measurements. Seven of the 10 studies had statistically significant findings that subjects who received mobilization or manipulation interventions experienced improved outcomes or reported fewer symptoms than control subjects. These results suggest that mobilization or manipulation of the cervical spine may be beneficial for individuals who suffer from CEH, although heterogeneity of the studies makes it difficult to generalize the findings.

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To compare the effects of spinal thrust manipulation and electrical dry needling (TMEDN group) to those of nonthrust peripheral joint/soft tissue mobilization, exercise, and interferential current (NTMEX group) on pain and disability in patients with subacromial pain syndrome (SAPS). U DESIGN: Randomized, single-blinded, multicenter parallel-group trial. U METHODS: Patients with SAPS were randomized into the TMEDN group (n = 73) or the NTMEX group (n = 72). Primary outcomes included the Shoulder Pain and Disability Index and the numeric pain-rating scale. Secondary outcomes included the global rating of change scale (GROC) and medication intake. The treatment period was 6 weeks, with follow-ups at 2 weeks, 4 weeks, and 3 months. U RESULTS: At 3 months, the TMEDN group experienced greater reductions in shoulder pain and disability (P<.001) compared to the NTMEX group. Effect sizes were large in favor of the TMEDN group. At 3 months, a greater proportion of patients within the TMEDN group achieved a successful outcome (GROC score of 5 or greater) and stopped taking medication (P<.001). U CONCLUSION: Cervicothoracic and upper-rib thrust manipulation combined with electrical dry needling resulted in greater reductions in pain, disability, and medication intake than nonthrust peripheral joint/soft tissue mobilization, exercise, and interferential current in patients with SAPS. The effects were maintained at 3 months.

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Computer simulations provide virtual hands-on experience when actual hands-on experience is not possible. To use these simulations in medical science, they need to be able to predict the behavior of actual processes with actual patient-specific geometries. Many uncertainties enter in the process of developing these simulations, starting with creating the geometry. The actual patient-specific geometry is often complex and hard to process. Usually, simplifications to the geometry are introduced in exchange for faster results. However, when simplified, these simulations can no longer be considered patient-specific as they do not represent the actual patient they come from. The ultimate goal is to keep the geometries truly patient-specific without any simplification. However, even without simplifications, the patient-specific geometries are based on medical imaging modalities and consequent use of numerical algorithms to create and process the 3D surface. Multiple users are asked to process medical images of a complex geometry. Their resulting geometries are used to assess how the user’s choices determine the resulting dimensions of the 3D model. It is shown that the resulting geometry heavily depends on user’s choices.