Neuroimaging: A Key Unlocking Phantom Limb Pain

Review Article

Austin Neurol & Neurosci. 2016; 1(3): 1014.

Neuroimaging: A Key Unlocking Phantom Limb Pain

Das SK¹, Yuan YF¹ and Yang HF²*

¹Department of Interventional and Vascular Surgery, Shanghai Tenth People’s Hospital, Tongji University, People’s Republic of China

²Department of Radiology, Affiliated Hospital of North Sichuan Medical College, People’s Republic of China

*Corresponding author: Yang HF, Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Sichuan, People’s Republic of China

Received: October 05, 2016; Accepted: December 17, 2016; Published: December 21, 2016


Post Amputation Pain (PAP) is highly prevalent after limb amputation but unfortunately, the pathophysiology along with consistently effective treatments remain elusive. However, recent advances in neuroimaging and neurophysiology are rapidly expanding our understanding of Phantom Limb Pain (PLP) and have paved a way for mechanism directed treatment approaches. The purpose of this article is to review recent advances in neuroimaging that has led to better understanding of PLP mechanism and how understanding of these mechanisms has been contributing in developing new treatment approaches. We have discussed different proposed mechanism and treatments of PLP in short with emphasis on how neuroimaging has led us to unveil these facts about PLP and how with further advancement in neuroimaging, we would be able to dig in deeper into yet unanswered questions.

Keywords: Phantom limb pain, Maladaptive plasticity, Cortical reorganization, fMRI, fcMRI


PLP first described by French military surgeon, Ambrose Pare, is defined as a painful sensation in the location of an amputated limb, which gets its present name as “phantom limb pain” by a famous civil war surgeon Silas Weir Mitchellis [1-3]. PLP is a common phenomenon occurring in 72% of amputees within the first week of surgery, with 60% continuing to experience pain at 6 months. No change in this prevalence occurs during the next 5 years. Factors that correlate to the development of phantom pain include pain that lasts longer than 1 month before amputation, increased post-surgical pain, and psychological factors, including anxiety [1]. The paradigms of proposed mechanisms for PLP have shifted over the past years from the psychogenic theory to peripheral and central neural changes involving cortical reorganization. More recently, the role of mirror neurons in the brain has been proposed in the generation of phantom pain. A wide variety of treatment approaches have been employed, but mechanism-based specific treatment guidelines are yet to evolve [2]. Mechanism-based pain treatment is generally considered to be superior to etiologic-based therapy but the obstacles involved in identifying the predominant mechanisms can become nearly insurmountable for a condition as phenotypically and pathogenetically disparate as PAP [4]. Over the recent years, neuroimaging has revolutionized our understanding of the physiological responses to PLP thereby, paving the way for better treatment approaches directed towards the mechanisms.

Neuroimaging Modalities

All noninvasive neuroimaging modalities are based on biophysical signals related to either brain electrophysiology or hemodynamics/ metabolism. Neuronal activity intensifies electrophysiological signals, such as action potentials and post-synaptic potentials, which serve as the primary messengers for communication among neurons. In addition, neuronal activity is also coupled with metabolic and hemodynamic processes. As brain function requires sustained blood flow to supply oxygen to compensate for cerebral metabolic energy consumption, changes in neuronal activity often induce cascade of changes in Cerebral Metabolic Rate of Oxygen (CMRO2), Cerebral Blood Flow (CBF), Oxygen Extraction Fraction (OEF), Cerebral Blood Volume (CBV), etc. In contrast to electrophysiological signals, metabolic and hemodynamic responses are much slower and reflect the indirect and secondary effects of neuronal activity [5]. Electro Encephalo Graphy (EEG) [6] and Magneto Encephalo Graphy (MEG) [7] are based on electrophysiological principles. Functional Magnetic Resonance Imaging (fMRI) [8-10], Positron Emission Tomography (PET) [11,12], Single-Photon Emission Computed Tomography (SPECT) and Near-Infrared Spectroscopy (NIRS) are based on hemodynamic and/or metabolic principles. EEG and MEG measure external electric potenials and magnetic fluxes respectiveley. Both of these electricomagnetic signals, electric potenials and magnetic fluxes, arises collectively from mass neuronal responses within the brain and is then propagated (virtually) instantaneously from the activated neuronal tissues via volume conduction to the recording sites on/ above the scalp surface [13-16]. In contrast to EEG and MEG, fMRI is based on changes in oxygenation of hemoglobin that is associated with neural activity. Deoxyhemoglobin (dHb) is paramagnetic whereas oxyhemoglobin is diamagnetic on fMRI [17,18].

As neuronal activity elevates, the concomitant alternation of local oxyhemoglobin versus deoxyhemoglobin content gives rise to a socalled Blood Oxygen Level Dependent (BOLD) Magnetic Resonance (MR) signal [19]. In contrast to the traditional task-based approach (e.g., fMRI), resting state studies (e.g., fcMRI) observe the brain in the absence of overt task performance or stimulation. In these studies, subjects are generally asked to lie quietly under “resting” conditions such as eyes closed or while fixating on a crosshair. Spontaneous modulations in the BOLD signal in the absence of any explicit input or output are then recorded and analyzed. The resting human brain represents only 2% of total body mass but consumes 20% of the body’s energy, most of which is used to support of ongoing neuronal signaling. Task-related increases in neuronal metabolism are usually small (<5%) when compared to this large resting energy consumption. Differences in these task-related changes between normal and pathological populations are smaller still, often less than 1%. When attempting to study disease or diagnose patients based on task-related changes, one is therefore focusing on only a very small fraction of the brain’s overall activity. Ongoing spontaneous activity may provide a window onto the neural processing that appears to consume the vast majority of the brain’s resources and so may prove a richer source of disease-related signal changes [20]. Importantly, resting state fcMRI may enjoy several practical and theoretical advantages over task based fMRI for clinical applications, including improved signal to noise, reduced need for patient compliance, avoidance of task performance confounds, and expanded patient populations [21]. Other imaging modalities like Diffusion Tensor Imaging (DTI) have also been used to study brain connectivity and plasticity. The various indices extracted from DTI enhance image specificity for distinct brain structures (e.g. Fractional Anisotropy (FA) is used to characterize the organization of white matter fibers) [22]. Significant changes in DTI parameters were reported in the relevant white matter pathways after training [23-25], leading to speculation that DTI can detect structural brain plasticity in both gray and white matter [26]. However, the biological and morphological meanings of these changes remain unclear.

Citation: Das SK, Yuan YF and Yang HF. Neuroimaging: A Key Unlocking Phantom Limb Pain. Austin Neurol & Neurosci. 2016; 1(3): 1014.