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Table of Contents  
Year : 2021  |  Volume : 15  |  Issue : 4  |  Page : 385-390  

Ultrasound block of the medial branch: Learning the technique using CUSUM curves

1 Department of Anesthesia, Critical Care and Emergency, University Hospital ASST Spedali Civili of Brescia, Brescia, Italy
2 Department of Mininvasive Surgery, Pain Medicine Unit, IRCCS, Maugeri, Pavia, Italy

Date of Submission29-Dec-2021
Date of Acceptance04-Feb-2022
Date of Web Publication08-Mar-2022

Correspondence Address:
Dr. Maurizio Marchesini
Department of Mininvasive Surgery, Pain Medicine Unit, IRCCS, Maugeri, Pavia
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/aer.aer_162_21

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Background: Blocking the medial branch of the lumbar facet joints plays a fundamental diagnostic and therapeutic role in the treatment of lumbar pain. Attempts to replace the typical guided X-ray techniques with ultrasound-guided techniques have also involved treating the lumbar medial branches. By applying the cumulative sum control chart (CUSUM method), we sought to evaluate the learning curve associated with ultrasound-guided block of the lumbar medial branches in operators experienced in locoregional anesthesia but without expertise in pain therapy. Aim: This study aimed to use a repeatable method to identify the learning curve of the ultrasound-guided medial branch block. Settings and Design: This study was a prospective application of over forty consecutive procedures of ultrasound lumbar medial branch block. Materials and Methods: The ultrasound medial branch blocks were performed under ultrasound guidance with confirmation of correct positioning using fluoroscopy on a population of patients with low back pain with any body mass index (BMI). Statistical Analysis: The operator's performance was assessed using the learning curve cumulative summation test (LS-CUSUM). Results and Conclusions: The correct target was reached in 29 procedures out of a total of 40 (72.5%) and in 29 out of 36 procedures performed on patients with BMI <30 (80.5%). According to the CUSUM algorithm, 11 further consecutive successes would have been necessary (47 procedures in total) to achieve a proven learning of the technique in the group with only patients with a BMI <30, with a further 22 consecutive successes (62 procedures in total) in the general group. Ultrasound-guided block of the lumbar medial branch appears not to be optimal for training beginner/intermediate operators seeking to replace guided X-ray procedures with guided ultrasound.

Keywords: Facet joint, learning curve, low back pain, medial branch block, nerve block, pain procedure, ultrasound

How to cite this article:
Putzu M, Marchesini M. Ultrasound block of the medial branch: Learning the technique using CUSUM curves. Anesth Essays Res 2021;15:385-90

How to cite this URL:
Putzu M, Marchesini M. Ultrasound block of the medial branch: Learning the technique using CUSUM curves. Anesth Essays Res [serial online] 2021 [cited 2022 Dec 6];15:385-90. Available from:

   Introduction Top

Lower back pain is a highly common pain syndrome, with an estimated prevalence of approximately 84%.[1] It is a frequent cause of disability in the adult population, leading to major health-care costs. In most cases, chronic lower back pain is characterized by mixed patterns, with multiple and concomitant localizations of algogenic lesions. The ability to correctly identify different subgroups of lower back pain is a desirable goal, as it is crucial in determining the best therapeutic path for each patient.

Zygapophyseal joints are joints classifiable as type diarthrosis of arthrodias, as they have only sliding movements. At the lumbar level, the orientation of the articular surfaces corresponds to a sagittal plane. Each joint is innervated by the medial branch of the dorsal branch of the root nerve corresponding to the joint, and from the medial branch coming from the level above.

Following an arthritic-degenerative process, the lumbar joint facets represent the cause of pain in 15%–45% of affected patients, causing chronic low back pain.[2] Nociception can originate from the membrane synovial, cartilage, bone, or fibrous capsule of the joint.[3] The literature contains numerous diagnostic evaluation scales for pain of pertinence of the lumbar facets; however, there is currently no instrument available to facilitate precise diagnosis.

Gòmez Vega et al.[4] outlined the signs and symptoms incorporated into diagnostic algorithms and most frequently found in patients, identifying three symptoms (axial or bilateral lumbar pain, improvement at rest, and absence of root pattern) and three clinical signs (Kemp's sign, pain caused at the level of the joints or transverse processes, signs of facet stress, or signs of Acevedo) that show particular accuracy in their ability to diagnose the syndrome.

In 2017, Petersen et al. identified a Clinical Diagnostic Rule for each specific localization of the pain generator that can quantify the weight that the patient's history, physical examination, and basic laboratory tests, should have in guiding the diagnosis, prognosis, and predictability of the response to treatment. According to these authors, the factors that show the greatest accuracy in excluding the joint genesis of pain are the absence of improvement at rest and the presence of the phenomenon of centralization.[5]

Meanwhile, the factors that are most commonly associated with pain are advanced age, previous episodes of lower back pain, normal walking, pain that worsens with the extension of the lumbar spine but that does not change with the Valsalva maneuver, and lack of pain in the leg and muscle spasm.[6]

Imaging (X-ray, magnetic resonance imaging, and computed tomography) is often concomitant with morphological alterations; however, there is a poor correlation between clinical and radiological findings and imaging is usually not conclusive. Lumbar facet joint syndrome can, therefore, be clinically or radiologically suspected, but not confirmed.

Anesthetic block of the medial branch directed to the presumed lesion site and the site above has been proposed as a diagnostic and therapeutic option for the syndrome. A randomized trial conducted by the Manchikanti group on 200 patients evaluated for a total period of 32 months recognized short- and long-term benefits and noted a cumulative improvement of the clinical picture with 1–3 infiltrative procedures.[7] Elsewhere, another paper of Manchikanti et al. indicated greater short- and long-term therapeutic benefits of this type of block compared with intraarticular infiltration.[8]

Medial branch block also appears to have greater specificity in select patient candidates for neurolysis.[9] A randomized study by van Kleef et al.[10] and other observational studies[11],[12],[13] found short- and long-term benefits following radiofrequency ablation. Change in: fluoroscopy is the technique usually used for lumbar medial branch block. The main the advantage of using ultrasound for medial branch block is that it can be conducted outside the radiological room with reduced cost and organization efforts. In addition, the ultrasound-guided procedure does not expose patients and operators to radiation administered during the fluoroscopy.

In a 2006 paper, Shim et al. claimed to have performed 101 lockout procedures of ultrasound-guided medial branch with subsequent fluoroscopic control, with a success rate of 95%,[14] while in 2004, Greher et al. noted a success rate of 94% in a study conducted on cadavers.[15] Both Shim et al.'s and Greher et al.'s work was conducted on nonobese patients, which reduced the impact of the drawback linked to the low resolution of the ultrasound image for anatomical structures located at depth; in fact, this drawback makes this procedure highly complicated if not impossible to perform on obese patients.

In a recent trial, Rauch et al. studied 20 patients with a body mass index (BMI) >30 for a total of 84 procedures and reported a success rate of 62%.[16] The authors, therefore, concluded that the medial branch block cannot be performed with the ultrasound-guided technique alone in obese patients.

Procedure for the learning evaluation: CUSUM curves

The CUSUM algorithm is a statistical tool originally used in industrial production to study the trends in production processes. It uses a mathematical model that enables the user to determine whether a process is “controlled” or “out of control.” Defining the acceptable failure rate and unacceptable failure rate enables the quality of a process to be monitored in real time, with early errors or deviations recognized above a predefined limit. The predefined limit is the threshold above which the curve is “out of control” (indicating a statistically significant probability that the deviations of the variable depend on the inefficiency of the process), whereby corrective action must be taken.

More recently, CUSUM curves have been used in medicine to evaluate the expertise of an operator or group of operators for various maneuvers. CUSUM curve can suggest the number of procedures necessary to achieve a certain standard of competence, so it allows for the quick evaluation of an operator's performance. In the anesthetic field, CUSUM curves have been used to evaluate learning various procedures, such as catheter placement epidural, the execution of subarachnoid anesthesia, venous and arterial cannulation, and orotracheal intubation in direct laryngoscopy.[17],[19]

There are different types of CUSUM curves: in all curves on the axis of abscissa is reported the progressive number of procedure; in binary CUSUM curves on the ordinate axis are reported binary variables, such as the cumulative score of successes/failures, in linear CUSUM curves on the ordinate axis are reported continuous variables, such as time. Binary CUSUM curves can be further distinguished into a “constant risk of failure chart” and “adjusted risk of failure chart.” The constant risks provide for a decrease “s” for each success and an increase “1-s” for each bankruptcy, while the adjusted risks are constructed using a coefficient that contemplates the presence of a greater or lesser risk of failure linked to the characteristics of the single procedure: The latter is better suited to the clinical setting, where each test is different from the previous one, not reporting a decrease in performance if the risk of failure of the specific one procedure is high.[20]

The construction of a binary CUSUM curve requires the definition and quantification of certain variables:

  • Acceptable failure rate (p0)
  • Unacceptable failure rate (p1)
  • Type I error (α)
  • Type II error (β).

The other variables (a, b, P, Q, h0, h1, and s) are calculated and are a function of p0, p1, α, and β according to the following formulas:

a = ln [(1 − β)/α]

b = ln [(1 −α)/β]

P = ln (p1/p0)

Q = ln [(1 − p0)/(1 − p1)]

h0=−b/(P + Q)

h1 = a/(P + Q)

s = Q/(P + Q)

The “acceptable” failure rate is likely the most critical parameter to establish. The value selected should consider the degree of competence of the operator and any data already available in the literature.

The model proposed by Dreyfus classifies the competence of the operator in a given technique in five levels [Table 1].
Table 1: Competence of operator (mod by Dreyfus)

Click here to view

The “unacceptable” failure rate is usually calculated as 2–5 times the acceptable rate. The graph starts from zero. For each success, the variable “s” (prize) is subtracted from CUSUM score, while for each failure “1-s” (punishment) is added. A negative trend describes a series of prevailing successes (operator competent), whereas a positive trend signals a series of prevalent failures (incompetent operator). When the curve crosses the upper limit h1, the degree of failure detected is significantly greater than that which is acceptable, whereas when the curve crosses the lower limit h0, the detected failure rate is not significantly different from that which is considered acceptable. If the curve lies between the two decision limits and no inference is possible, observation must continue [Figure 1].
Figure 1: Interpretation of CUSUM analysis

Click here to view

Another way of declaring competence based on the curve pattern is described by Williams,[21] as follows: When α = β, then h0 = h1, and it is possible to construct in graph a series of lines corresponding to multiples of h0 (i.e., h0, 2 h0, 3 h0, and onward).

According to the model, competence is reached when at least two of the lines are intersected from top to bottom by the curve, which then remains below the second intersected line.

Although Williams' approach was more advanced, we did not choose it for two reasons:

  • Need for large numbers of procedures to obtain a meaningful process analysis
  • Lack of data in the literature supports the choice of arbitrary values to be included in the model.

Therefore, we chose a more classical “approach,” considering the design of this work as pilot study.

   Materials and Methods Top

The ethical committee (censored), during the May 2018 session, declared the diagnostic role of the study during usual clinical practice with no other procedure of the patient, so need no approval for the EC. All the patients signed informed consent for the procedure and all clinical procedures of this study with the signed permission to collect anonymous data for scientific publication.

From August 2018 to November 2018, 26 consecutive ultrasound-guided blocks of the medial branch were performed. All blocks were prospectively analyzed. The patients were selected previously during an ambulatory visit. All selected patients had lumbar pain with a diagnosis of zygapophyseal origin without any sign of local or systemic infection. The use of anticoagulants was not an exclusion criteria, and for the anatomical purpose of the study, need for collaboration from patients was not necessary. Twelve of the blocks were of the L3 branch, one block was of the L2 branch, and one block was of the L1 branch. There were forty procedures in total. Each patient underwent blockage of the branch corresponding to the joint zygapophyseal identified as the site of the algogenic lesion and of the site above. Patients with L5-S1 involvement underwent a dorsal branch block of relevance L5 under fluoroscopic guidance. The successes and failures, as evaluated by fluoroscopy, were placed in order of progressiveness in the database to calculate the CUSUM score and to graphically construct the curve. The procedure was performed by an anesthesia specialist with more than 10 years' experience in locoregional anesthesia, including ultrasound-guided procedures, but with minimal experience in interventional pain therapy. This placed the operator at an “advanced beginner” level.

In the X-ray room, after a sterile field and with the patient in a prone position, ultrasound exploration of the lumbar spine was conducted using a probe low frequency curvilinear ultrasound (3–8 MHz). The first exploration, which was first conducted on the sagittal plane and then on the transversal plane, aimed to identify the level of the target in the cranial direction caudal. The interlaminar spaces from L5–S1 to L1–L2 were progressively identified and marked. Once the correct level had been identified, a second exploration sought to identify the target structure, at the level of which, using the in-plane technique and with the probe oriented along the transverse plane, the tip of the needle (21G × 120 mm Temena® AMBU A/S Ballerup DK) was placed in the shower located between the base of the superior articular process and the transverse process of the vertebra below the root belonging to the branch affected medial.

Once bone contact was achieved, the probe was rotated in the sagittal plane to verify that the tip of the needle was in the most cranial portion of the process transverse before proceeding with the correction. When the position of the needle tip in the ultrasound image appeared satisfactory to the operator, fluoroscopic control evaluated the adequacy of the position of the needle tip relative to both the segmental level and the target point. If the needle tip position was correct for the level and target, the case was noted as a “success,” and 0.5 mL 0.5% levobupivacaine was injected. If the needle tip position was not correct, it was repositioned under fluoroscopic guidance before administering 0.5 mL 0.5% levobupivacaine, and the case was considered a “failure.”

Success or failure in reaching the correct target was entered in progressive order into the database to calculate the CUSUM score and construct the curve. It was not possible to extrapolate the data from the literature to calculate a coefficient that considered the relative risk associated with each procedure. We, therefore, opted for a “constant risk failure chart” considering an error type I and type II of 0.1.

Data analysis using the CUSUM curve was conducted for two groups of patients: The first group included all the procedures performed, while the second included only those performed on patients with BMI <30.

Statistical analysis was performed using RStudio (ver 1.3). The learning curve summation test was used to assess if the process has reached a predefined level of performance. The null hypothesis is that the process is in control, while the alternative hypothesis H1 is that the process is out of control.

The supposed projection of the ideal number of procedures was performed with a covariance matrix using the data of the previous path.

Continuous variables were expressed as mean SD or medians, categorical.

A standard CUSUM test monitors a sequential procedure to accept or reject the hypotesis H0.

The acceptable risk was 0.15, and the unacceptable risk was 0.3 for both groups. The p0 value was chosen after considering that identified as suitable for other anesthetic procedures studied using the CUSUM algorithm, while the p1 value was arbitrarily set to 2p0.[17],[20]

   Results Top

After ultrasound exploration of the lumbar spine, initially according to the sagittal plane and subsequently according to the transverse plane, the intervertebral levels were correctly identified in 12 patients (of the 14 patients analyzed).

The level was not correctly identified in two patients; the first patient presented a sacralization of L5, subsequently detected with fluoroscopy, which made the interlaminar space L5–S1 unidentifiable, while the second patient showed severe scoliosis. In the first patient, the subsequent targets were correctly identified later with the information provided by fluoroscopy, while in the second patient, the second procedure conducted was also not successful. The correct target was reached in 29 procedures out of 40 total (72.5%) and in 29 procedures out of 36 performed on patients with a BMI <30 (80.5%).

Although only four out of 40 procedures were performed on obese patients, the pattern of the respective CUSUM curves was found to vary significantly between the two groups: The curve of the patients with a BMI <30 [Figure 2] never exceeded the h1 limit, remaining “controlled,” while the curve of the group that included obese patients [Figure 3] was almost consistently “out of control.”
Figure 2: CUSUM Curve in patient with body mass index

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Figure 3: CUSUM Curve in all patients despite body mass index

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The limited number of procedures conducted did not allow the h0 limit to be reached in either of the two groups. However, it was possible to calculate that, if the observation had continued, the number of consecutive successes necessary for ultrasound guidance of the intervertebral level would be 92.5%, considering the single ones procedures. However, these data are of little significance if we consider that, in the two patients for whom the needles were positioned at an incorrect level, they were only correctly positioned after fluoroscopic evaluation had determined the locations of the first. If it is considered that, without the radiological information, needles were also likely to have been positioned at an incorrect level in two of 14 patients, the success in determining the level drops to 85.7%. The success rates of reaching the target in the group of patients with BMI <30 and in the group as a whole were 80.5% and 70.5% respectively; none of the two curve intersected h0 to allow competence to be declared in either group.

The curve for procedures on patients with BMI <30 described the learning as “Controlled” but remained within the space delimited by h0 and h1 without intersecting them, thereby not allowing any inference. Meanwhile, the curve for the group as a whole intersecting h1 showed an “out of control” trend. Applying the methodology proposed by Williams to this curve,[21] it was possible to infer that, in the whole group, the new target line for declaration of competence was that which passed through the zero point. If, in a hypothetical continuation of the observation of the curve, after having intersected the line 0, the curve remained consistently below this line without ever intersecting h0, this could indicate that p0 = 0.15 is an unrealistic target for this technique performed on groups of patients not selected based on BMI. This observation appears to be in agreement with the literature.[15]

   Discussion Top

The limited evidence available suggests that gaining proficiency in US-guided spinal procedures is challenging difficult and requires numerous procedures.[22],[23],[24] Training a single operator does not allow for a minimum or average number of procedures necessary to achieve competence to be established. However, based on observations, they number that would be needed is likely to be significant. According to the CUSUM algorithm, 11 further consecutive successes would have been necessary (47 procedures in total) because the curve intersected h0 in the group comprising only patients with BMI <30. There were a further 22 consecutive successes (62 procedures in total) when h0 was intersected in the group as a whole. These values clearly underestimate (particularly for the general group) in the number of procedures likely to be necessary to declare jurisdiction with p0 = 0.15. The number of necessary procedures appears high even when compared with other anesthetic procedures investigated using the same algorithm; a 2002 study conducted on a group of postgraduates assessed using the CUSUM algorithm and with p0 = 0.2 reported that an average 31 procedures were necessary to achieve competence in placing a lumbar epidural catheter.[17]

The main limitations related to the CUSUM algorithm is the impossibility of calculating a specific risk coefficient for each procedure to allow for the construction of an “adjusted risk” curve due to the absence of data. This curve considers the risk of greater or lesser failure linked to the characteristics of the individual patient and is better suited to clinical settings, in which each test is different from the previous one. This essentially attributes less weight to the decrease in performance if the risk of failure of the specific procedure is high.[19]

The main limitation of this study, for which it can be defined as a pilot study, is applying the method to procedures performed by a single operator.

However, the validation of this method will allow applying the assessment method to different profiles (novice, advanced beginner, etc.) to define different competence curves.

In the literature, to our knowledge, there are no studies that systematically report the number of procedures for each pain therapy technique, such as to be able to define an acquired competence. Although at an early stage, we believe that this study can lay the foundations for applying this technique to all procedures so that it can be included in the core curriculum of the various scientific societies of pain therapy.

   Conclusion Top

Research suggests that ultrasound guidance for branch block medial can represent a valid and reproducible alternative to the traditional fluoroscopic technique in select patients. Achieving competence in the ultrasound-guided block technique could be highly advantageous; however, a significant number of procedures are required to achieve competence. Despite this, the procedure has numerous limitations that affect its applicability in routine clinical settings. It is only feasible for thin patients who have not previously undergone spinal demolition surgery and who do not require branch blocking dorsal of L5. In addition to a high BMI, the presence of congenital or acquired anatomical variants can hamper the reliability of the method. Lastly, ultrasound-guided block of the medial branch does not appear to be optimal for training beginner operators, who must acquire competence in ultrasound-guided procedures involving the lumbar spine, requiring a fluoroscopic control.

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Conflicts of interest

There are no conflicts of interest.

   References Top

Balagué F, Mannion AF, Pellisé F, Cedraschi C. Non-specific low back pain. Lancet 2012;379:482-91.  Back to cited text no. 1
Perolat R, Kastler A, Nicot B, Pellat JM, Tahon F, Attye A, et al. Facet joint syndrome: From diagnosis to interventional management. Insights Imaging 2018;9:773-89.  Back to cited text no. 2
Cohen SP, Raja SN. Pathogenesis, diagnosis and tratment of lumbar zigoapophysial (facet) joint pain. Anesthesiology 2007;106:591-614.  Back to cited text no. 3
Gómez Vega JC, Acevedo-González JC. Clinical diagnosis scale for pain lumbar of facet origin: Systematic review of literature and pilot study. Neurocirugia (Astur: Engl Ed) 2019;30:133-43.  Back to cited text no. 4
Petersen T, Laslett M, Juhl C. Clinical classification in low back pain: Best-evidence diagnostic rules based on systematic reviews. BMC Musculoskelet Disord 2017;18:188.  Back to cited text no. 5
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Kestin IG. A statistical approach to measuring the competence of anesthetic trainees at practical procedures. Br J Anaesth 1995;75:805-9.  Back to cited text no. 19
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  [Figure 1], [Figure 2], [Figure 3]

  [Table 1]


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