10 Biofeedback in the diagnosis and treatment of chronic essential pelvic pain disorders
Pain, relaxation and biofeedback
Research applications to pelvic pain problems
Developing evidence-based biofeedback applications for pelvic pain
Selected ongoing international collaborative research
Pain, relaxation and biofeedback
Changes in emotion and expectations have clear effects on level of pain. These underlying connections have been explored recently as part of research into the mechanism of the placebo effect (Wager et al. 2007, Zubieta & Stohler 2009). The conclusions go beyond mental constructs like distraction and endurance; pain intensity turns out to be modulated by specific chemical and neurological changes in a way resembling the gain control on an amplifier. Changes in synapses, in descending excitatory and inhibitory tracts, in specific brain site excitation and inhibition, in opioid receptor sensitivity, and positive and negative expectations about pain, all interact to enlarge or diminish the experience of pain. Evolution has apparently fine-tuned this set of mechanisms to maximize the chance of survival.
In the field of clinical biofeedback, chronic pain has been a frequent symptom of interest because it is common, distressing, and often seems unnecessary when the signal has little value for warning of body damage. Chronic pain seems to become detached from its origin, or spreads out so much (allodynia, spreading cortical representation; Flor 2002) that the mechanistically minded allopathic physician is without answers as to why something hurts so much. Medical imaging may offer little explanation as to pain sources, and blood tests may show nothing that would explain high pain levels not related or only loosely related to body use. Exercise sometimes improves and sometimes aggravates the pain. Decreased tolerance of the pain may be attributed to deconditioning, even though the original advent of the pain may have discouraged activity and thus led to deconditioning.
Biofeedback depends on providing continuous feedback of a signal to the person it is coming from. With pain, however, there is hardly any way to detect and feed back an actual ‘pain signal’. The closest thing to this is the work done by de Charms et al. (2005) using fMRI for continuous monitoring and display of activity in a brain region known for correlating with experienced pain (anterior cingulate cortex (ACC)). Investigating both chronic pain patients and normal experimental subjects, these researchers found that displaying the moment-to-moment fluctuations in amplitude from the ACC provided an opportunity to influence the signal, which would mean influencing the brain area generating the signal and therefore voluntarily adjusting pain intensity. Whether this pain relief came about via emotional modulation, attentional shifts, or neurological–biochemical changes awaits further research, but the question challenges the mind–body distinction which has oversimplified so much research in this area. Subjects felt their pain intensity reduce, and they felt they were controlling it by doing something to manipulate the graphic display on a video screen. However, the subjects were sitting inside an fMRI device in a research lab, and this would be impractical for large-scale application.
Other than the MRI route, a biofeedback approach generally concentrates on altering a system considered responsible for the pain, or at least correlated with it. Thus we can provide biofeedback from voluntary muscles, feedback from the autonomic nervous system (ANS) variables such as skin temperature, skin conductance, heart rate, heart rate variability (RSA, see below), breathing (rate, rhythm, tidal volume, CO2 level) and EEG, including cerebral blood flow and slow cortical potential. For biofeedback overviews see Schwartz & Andrasik (2003) and Basmajian (1989).
There is support (Arena 2002) for the non-specific use of biofeedback, however, and patients rarely question the lack of specificity. They may readily acknowledge that their pain seems responsive to variation in not only physical activity but emotional stress and depression. Thus the variables of effective or less effective coping, mood modulation in response to the pain, and the amount of co-occurring non-pain distress require consideration in pain management. It may seem that such complex emotional variables could not be detected and fed back via biofeedback devices. But emotions have biological correlates and teaching control over them amounts to gaining leverage over the feeling states themselves. And these feeling states (explored by the placebo researchers cited above) have neurochemical effects on pain intensity.
Pelvic floor biofeedback began with Arnold Kegel (1948), who designed a pressure perineometer to measure contractile force from inside the vagina, with pressure changes displayed on an external gauge. The intent was to improve strength of the pubococcygeus muscle, and it was usually successful. More modern use of biofeedback for pelvic pain usually relies on either manometric feedback (inflatable balloons with adjustable size, placed in the rectum) or surface electromyographic (SEMG) information gained via vaginal or rectal sensors. Information may also be gained from monitoring the external muscles of the lower abdomen, perineum, thighs, and buttocks. Pelvic pain can of course come from many sources, but if dysfunctional muscle activity is suspected, it is simple enough to feed back the continuous muscle amplitude to the patient, opening a channel for voluntary control.
Research applications to pelvic pain problems
Hand temperature and pelvic pain
In a small multiple baseline study (Hart et al. 1981) five women with pain from endometriosis were trained in hand-warming with individual sessions twice weekly over 2 months, with home practice in between sessions. The rationale was to reduce physiological arousal, and the intent was to have the skill generalize as a learned and perhaps automatic response to pain. All but one person learned to voluntarily increase hand temperature, and reports of pain relief were accompanied by decreases in life interference from pain, decrease in affective distress, and increase in ‘life control’. One person could not learn the hand-warming skill; her pain remained the same and some indicators got worse.
Muscle biofeedback and pelvic pain
There are several ways that excess muscle tension can cause pain: prolonged ischaemia, accumulation of metabolites such as lactic acid and potassium; reduced intramuscular circulation, release of bradykinin and serotonin, and various aggravators of inflammation (Mense 2000). In addition, pain intensity is mediated by co-occurring emotional factors. Brain sites such as the anterior cingulate cortex are responsive to allodynia and are also involved in conscious mediation of ‘suffering’ (Yoshino et al. 2009). Therefore, negative affect from any source is likely to make pain worse because at some level different kinds of distress are not differentiated. The most reliable predictors of hyperalgesia seem to be varieties of anxiety, fear of movement, fear of injury, and the tendency toward catastrophic thinking (Boersma & Linton 2006a, 2006b).
Muscle tension is often elevated in chronic pain patients as part of an attempt to brace and protect the body from damage. Muscular rigidity is a primary defensive response to threat, pain and trauma, and this response can be triggered by both relevant and irrelevant sensory and emotional stimuli. SEMG monitoring can detect and quantify the degree of inappropriate pelvic muscle hypertonicity and instability (White et al. 1997, Glazer et al. 1998). Many chronic pain syndromes besides pelvic pain are associated with increased muscle tension (Flor et al. 1992) and can be alleviated in part by better muscle control.
Granot et al. (2002) studied pain sensitivity in a group of women with vulvar vestibulitis using a heated bar on the skin. A matched control group without pain was used for comparison. The researchers collected anxiety measures and estimates of pain intensity and unpleasantness, and blood pressure was also recorded. The pain patients had significantly more state and trait anxiety before the procedure began; they gave higher estimates for pain magnitude, unpleasantness, and had higher systolic blood pressure. The authors’ conclusions were that these subjects were more anxious and had higher systemic pain sensitivity.
The study of Bendaña et al. (2009) used a treatment sample of 52 women having problems with urinary frequency and urgency, interstitial cystitis, CPP, dysuria, and evidence of pelvic floor muscle (PFM) spasm. Initial determination of the levator ani muscle complex condition was done by manual vaginal examination. Subject criteria for selection were bladder dysfunction, including pelvic pain, and evidence of PFM tension. The therapeutic goal was to detect and reduce muscle tension and spasms in the PFMs using transvaginal SEMG and electrical stimulation. During six individual sessions the subjects observed computerized visual feedback which reflected their internal muscle tension from moment to moment. First isolating sensations of the relevant muscles from surrounding pelvic, abdominal and back muscles, they learned to increase control of the pertinent muscles in both tensing and relaxing directions.
The study of Heah et al. (1997) of men with levator ani syndrome (LAS) used manometric rectal balloon biofeedback. Average pain report after completion of biofeedback dropped to around 25% of that before biofeedback, with use of analgesics also significantly reduced.
Grimaud et al. (1991) also used a manometric technique to investigate patients with chronic idiopathic anal pain. In the 12 cases studied, the pressure in the anal canal was significantly higher than in a normal comparison group. After an average of eight biofeedback training sessions, in which patients learned voluntary control of the external sphincter, the pain disappeared, and the anal canal pressure dropped to normal or near-normal.
Cornel et al. (2005) reported treatment of 31 men with chronic prostatitis and CPP. They learned to control and relax PFM tension via biofeedback provided by a rectal SEMG sensor. Average muscle tension before treatment was 4.9 µv, and dropped to 1.7 µv afterward. Corresponding drops in symptom scores (NIH Chronic Prostatitis Symptom Index) went from 23.6 to 11.4.
Chiarioni et al. (2009) reports administering nine sessions of counselling plus electrogalvanic stimulation (EGS), massage or biofeedback randomized to 157 patients suffering from LAS. Outcomes were reassessed at 1, 3, 6 and 12 months. Among patients with LAS, adequate relief was reported by 87% for biofeedback, 45% for EGS, and 22% for massage. Pain days per month decreased from 14.7 at baseline to 3.3 after biofeedback, 8.9 after EGS, and 13.3 after massage. Pain intensity decreased from 6.8 (0–10 scale) at baseline to 1.8 after biofeedback, 4.7 after EGS, and 6.0 after massage. Improvements were maintained for 12 months. The authors conclude that biofeedback is the most effective of these treatments, and EGS is somewhat effective.
Jantos (2008) assessed vulvar pelvic muscle tension in 529 cases of vulvodynia, combined with psychological testing, to examine psychophysiological factors. The study also provided biofeedback-based intervention in the form of daily pelvic muscle exercises based on findings of SEMG using the ‘Glazer Protocol’ (Glazer et al. 1995) This involves use of progressively larger dilators to stretch and relax the vulvar and vaginal muscles, intravaginal EMG biofeedback, and brief psychotherapy aimed at improved psychological (anxiety, depression, fear of sexual activity) and sexual functioning. State and trait anxiety differentiated normals from vulvodynia patients, who also had lower sensory thresholds, more autonomic disturbances, and greater emotional responses. General outcomes after treatment included normalizing of muscle characteristics, capacity to accept larger dilators, and greater likelihood of resuming normal sexual activity. PFM improved in several ways, correlating with degree of improvement in the group as a whole, though not individually. Resting baseline and instability declined by more than 50%; maximum phasic and tonic contractions increased.
A unique finding in the Jantos study was the relationship between duration of symptoms and resting PFM EMG (subject characteristics at the onset of the study): severity of symptoms did not decline with time, but muscle tension did. The authors speculated that this could indicate development of contractures, which resemble muscle spasms upon palpation but are produced locally rather than by corticospinal input. As a result they are electrically silent and would not contribute to pelvic EMG. Such contractures could create pain by producing myofascial trigger points (Bornstein & Simon 2002). Trigger points produce a high local EMG signal that does not generalize to the whole muscle. These structures are sensitive to sympathetic nervous system activity (McNulty et al. 1994, Chen et al. 1998), and therefore can be aggravated by anxiety, apprehension and negative psychological states.
The psychophysiological perspective here gives a more complete understanding of how trigger points respond to physiological and emotional arousal by producing more pain (see also Chapter 4). For this reason, any arousal-reduction technique, including general relaxation methods, should be helpful for pain intensity that arises from trigger points.
Intrapelvic SEMG in the treatment of functional chronic urogenital, gastrointestinal and sexual pain and dysfunction
Biofeedback meets evidence-based medicine: The Glazer Protocol
This section of the chapter focuses on a specific methodology and protocol, the Glazer Protocol, for the diagnosis and treatment of essential CPP and dysfunction. The methodology involves the use of non-invasive intrapelvic (intravaginal or intra-anal) SEMG. The first factor differentiating this approach from the self-regulation biofeedback approach, discussed earlier, is the emphasis on the electrophysiology of the SEMG signal, rather than the psychophysiogy of self-regulation. This protocol relies more on the bioelectric information derived from the SEMG signal analysis, rather than the traditional biofeedback use of the SEMG signal to teach the patient voluntary self-regulation through enhanced interoceptive awareness. Unlike traditional biofeedback, this protocol is highly operationally defined, including diagnostic criteria (ICD), medical, psychological and sexual history, patient positioning and muscle use training, muscle activation and deactivation sequence, SEMG signal processing, recording and formatting, to create a standardized SEMG report and database. This approach facilitates the development of multicentre, multidiagnosis, multitreatment databases for statistical analysis. This operationally defined procedural and biometric/psychometric approach creates the foundation for evidence-based research and represents a substantial departure from past work in the field of clinical biofeedback (Glazer & Laine 2007).
Evidence-based medicine applies evidence from scientific methodology to health care practice. It assesses the quality of evidence relating to risks and benefits of treatments. The power of clinical evidence lies in its freedom from bias. The most powerful evidence for therapeutic efficacy comes from randomized, double-blind, placebo-controlled trials with operationally defined patient populations, diagnoses and treatment protocols. Patient testimonials, case studies, clinical experience and expert opinion have little value as scientific evidence. This in no way takes away from the importance of traditional clinical practice experience and thinking. Often clinical practice serves as an ‘incubator’ leading to ideas which are then transformed into more evidence-based hypotheses and subject to evidence-based medicine research. The completion of the cycle is the evidence-based research findings returning to clinical practice where their implementation can benefit clinical thinking and patient care (see Chapter 9).
A recent review article (Glazer & Laine 2007), summarizing the peer-reviewed literature in the use of PFM biofeedback for the treatment of functional urinary incontinence, exemplifies this. This review reports a total of 326 studies found in Medline between 1975 and 2005. Only 8.6% of these studies operationally defined independent and dependent variables, utilized prospective randomized trials with parametric statistical analyses, and used patient selection criteria to rule out organic causes of urinary incontinence. Among these 27 studies are six different operational definitions for the diagnosis, eight operational definitions for treatments, 12 operational definitions for biofeedback protocols, and six operational definitions for treatment outcome. In 30 years of peer-reviewed literature only seven studies reported a comparison of biofeedback to a matched, no treatment, control group. For these seven studies, differences in signal processing, biofeedback instrumentation, assessment and treatment protocols, biofeedback modalities, and multiple uncontrolled variables make each of these groups so different that there is no standardized definition of biofeedback. The same is true within each study, since the biofeedback groups are not comparable to their respective control groups due to non-randomized, uncontrolled variables between groups. This pervasive lack of standardization has hampered the scientific assessment of biofeedback by effectively precluding the application of evidence-based medicine standards to the field.
Applications
The Glazer Protocol is used in the diagnosis and treatment of a wide range of PFM-related disorder specialties as shown in Table 10.1.
Table 10.1 Disorders, categorized by medical specialty and ICD codes, treated with pelvic floor muscle SEMG biofeedback
| Medical specialty | Diagnostic ICD-9/-10 code |
|---|---|
| Gynaecology/Dermatology/Psychiatry | |
| 1. Vulvar vestibulitis syndrome | 625.71, 625.0 |
| 2. Dysaesthetic vulvodynia | 625.70, 625.9 |
| 3. Vaginismus | F94.2, 625.1 |
| 4. Dyspareunia (introital N94.1, deep 302.76) | N94.1, 302.76 |
