Spectral CT electron density for evaluation of lumbar intervertebral disk degeneration

Masanori Nakajo; Tsubasa Nakano; Tomohito Hasegawa; Kiyohisa Kamimura; Koji Takumi; Hiroaki Nagano; Masatoyo Nakajo; Hiroyuki Tominaga; Mutsukazu Hayashi; Takashi Iwanaga; Fumiko Kanzaki; Eran Langzam; Graeme Campbell; Ko Higuchi; Takashi Yoshiura

doi:10.1371/journal.pone.0357658

. 2026 Sep 1;21(9):e0357658. doi: 10.1371/journal.pone.0357658

Spectral CT electron density for evaluation of lumbar intervertebral disk degeneration

Masanori Nakajo ¹, Tsubasa Nakano ¹, Tomohito Hasegawa ¹, Kiyohisa Kamimura ¹, Koji Takumi ¹, Hiroaki Nagano ¹, Masatoyo Nakajo ¹, Hiroyuki Tominaga ², Mutsukazu Hayashi ³, Takashi Iwanaga ³, Fumiko Kanzaki ¹, Eran Langzam ⁴, Graeme Campbell ⁵, Ko Higuchi ⁶, Takashi Yoshiura ^1,^*

Editor: Ali Fathi Jouzdani⁷

¹ Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan

² Department of Orthopaedic Surgery, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan

³ Department of Radiological Technology, Kagoshima University Hospital, Kagoshima, Japan

⁴ CT Clinical Science, Philips Healthcare, Haifa, Israel

⁵ CT Clinical Science, Philips GmbH Market DACH, Hamburg, Germany

⁶ CT Clinical Science, Philips Japan, Tokyo, Japan

⁷IPM: Institute for Research in Fundamental Sciences, IRAN, ISLAMIC REPUBLIC OF

Competing Interests: The authors declare that they have no competing interests except employment by Philips Healthcare (Eran Langzam, Graeme Campbell and Ko Higuchi). The Kagoshima University Department of Radiology received the technical support from Philips Healthcare.

^✉

* E-mail: yoshiura@m3.kufm.kagoshima-u.ac.jp

Roles

Masanori Nakajo: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Visualization, Writing – original draft, Writing – review & editing

Tsubasa Nakano: Conceptualization, Data curation, Investigation, Methodology, Writing – original draft, Writing – review & editing

Tomohito Hasegawa: Data curation, Investigation, Writing – original draft, Writing – review & editing

Kiyohisa Kamimura: Data curation, Writing – original draft, Writing – review & editing

Koji Takumi: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Hiroaki Nagano: Conceptualization, Writing – original draft, Writing – review & editing

Masatoyo Nakajo: Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Hiroyuki Tominaga: Data curation, Resources, Writing – original draft, Writing – review & editing

Mutsukazu Hayashi: Investigation, Writing – original draft, Writing – review & editing

Takashi Iwanaga: Investigation, Writing – original draft, Writing – review & editing

Fumiko Kanzaki: Writing – original draft, Writing – review & editing

Eran Langzam: Resources, Writing – original draft, Writing – review & editing

Graeme Campbell: Resources, Writing – original draft, Writing – review & editing

Ko Higuchi: Resources, Writing – original draft, Writing – review & editing

Takashi Yoshiura: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing

Ali Fathi Jouzdani: Editor

PMCID: PMC13533366 PMID: 42678973

Abstract

Objective

This study aimed to investigate the ability of spectral CT parameters to evaluate lumbar intervertebral disk degeneration (LIDD).

Summary of background data

LIDD is the most prevalent cause of low back pain. However, the usefulness of spectral CT for LIDD evaluation remains unclear.

Methods

This retrospective study included consecutive patients who underwent spectral CT and Magnetic resonance imaging for spinal disease examination from February 2018 to June 2021 on a single center. The conventional polyenergetic 120-kVp computed tomography value (CT_conv), electron density (ED), and effective atomic number (Z_eff) were measured in the annulus fibrosus (AF) and nucleus pulposus (NP) in each disk. Additionally, differences in each spectral CT parameter were obtained between the anterior AF and NP and between the posterior AF and NP. These parametric values were correlated with modified Pfirrmann grade (mPG) using Spearman’s rank correlation coefficients. The receiver operating characteristic curve analysis was used to assess diagnostic performances for differentiating between normal and degenerative disks.

Results

Three hundred thirty-eight lumbar intervertebral disks of 100 patients were analyzed. The CT_conv and ED were negatively correlated with mPG in AF (ρ = −0.29 to −0.36) and positively correlated with mPG in NP (ρ = 0.16–0.45), whereas Z_eff in NP was negatively correlated with mPG (ρ = −0.29 to −0.38). The ED differences between the anterior AF and NP and between the posterior AF and NP were strongly correlated with mPG (ρ = −0.71 and −0.64, respectively) and demonstrated high diagnostic performances in differentiating between normal and degenerative disks (area under the receiver operating characteristic curve values = 0.92 and 0.88, respectively).

Conclusion

Spectral CT parameters, particularly ED, can diagnose lumbar intervertebral disk degeneration.

Introduction

Lumbar intervertebral disk degeneration is the most prevalent cause of low back pain [1,2], and it causes herniated disk disease, lumbar degenerative spondylosis, and lumbar spinal canal stenosis [3].

The intervertebral disk is centrally and peripherally composed of the nucleus pulposus (NP) and the annulus fibrosus (AF), respectively. The AF consists of a fibrocartilaginous structure that primarily contains type I collagen, whereas the NP is rich in water and proteoglycans in a loose network of type II collagen [4]. Proteoglycans in disk degeneration, which function to bind water, decrease, thereby causing dehydration and relatively increased type I collagen within the NP, and tears and degenerate cysts of AF [5]. Lumbar intervertebral disk degeneration evaluation is conventionally performed using Magnetic resonance imaging (MRI) [1,2,5–7]. Pfirrmann grade and modified Pfirrmann grade (mPG) based on T2-weighted images are predominantly used for grading degenerative disk disease [6,7]. Thus, MRI is useful for intervertebral disk degeneration evaluation. However, MRI is unavailable for patients with contraindicated metal implantation or claustrophobia. Moreover, MRI may not be an optimal tool for diagnosing other causative diseases of lower back pain than spinal diseases such as urinary tract stones, aortic dissection, etc. Computed tomography (CT) effectively evaluated these diseases, but its usefulness for lumbar intervertebral disk degeneration evaluation has not been established.

Spectral CT imaging encompasses a unique generation of CT systems that utilize energy-dependent information, with dual-energy CT (DECT) representing its first generation, which can be implemented through various technical approaches including dual-source CT, rapid kVp-switching, and dual-layer spectral detector CT (DLCT) [8]. DECT analyzes data of Compton scattering and the photoelectric effect of X–rays of two energies using various algorithms. DECT studies of intervertebral disk diseases have been reported in recent years, specifically including virtual non-calcium imaging for disk herniation and degeneration [9–13], water imaging for disk degeneration [14], collagen mapping for disk degeneration [15–17], and electron density (ED) imaging for disk herniation [12,13]. ED and effective atomic number (Z_eff) are recently available as DECT derived parameters [18]. DECT enable more accurate measurements of ED and Z_eff through improved dose distribution accuracy, which were difficult to obtain with conventional single-energy CT [19]. While these measurements have been primarily investigated for improving dose calculation accuracy in radiation treatment planning [20], their utility in diagnostic imaging has remained underexplored. Recently, however, the diagnostic value of ED for evaluating disk herniation has been reported [12,13]. To the best of our knowledge, the use of ED and Z_eff images for lumbar intervertebral disk degeneration evaluation remains unknown. Therefore, this study aimed to investigate whether spectral CT-derived ED and Zeff can accurately differentiate varying degrees of lumbar disk degeneration.

Materials and methods

Patient population

The institutional review board approved this retrospective study under protocol number 200284 and waived the need to obtain informed consent because of the retrospective study design. The data used in this study were accessed on 19 March 2021 for research purposes. We accessed the data that had been appropriately anonymized to ensure the privacy of individual participants. The inclusion criterion was consecutive patients with suspected lumbar disorders who underwent lumbar spectral CT from February 2018 to June 2021. The exclusion criteria were (a) no lumbar MRI available, or an interval of more than one month between spectral CT and MRI examinations; (b) only contrast-enhanced CT scan available; (c) missing spectral data of spectral CT. Intervertebral disks with metallic artifacts, disk inflammation, and severe disk degeneration findings, including vacuum phenomenon, disk calcification, intradiscal fluid, and severe disk height reduction that precluded region of interest (ROI) placement as well as herniated disks, were further excluded. Consequently, the final population comprised 338 lumbar intervertebral disks of 100 patients. (Fig 1). We used the STARD reporting guideline [21] to draft this manuscript, and the STARD reporting checklist [22] when editing, included in S5 Checklist.

Spectral CT imaging protocols

The CT scanner involved a 64 multidetector row DLCT system (IQon Spectral CT; Philips Healthcare) which is equipped with a dual-layer spectral detector and a single X–ray source constantly enabling the acquisition of high and low-energy projection data and retrospective dual-energy data analysis. The imaging parameters were tube voltage of 120 kVp, gantry rotation time of 0.4 s, effective tube current–exposure time product of 140 mAs with automodulation, pitch of 0.703, and detector-row configuration of 64 × 0.625 mm. Images of the conventional polyenergetic 120-kVp computed tomography value (CT_conv), ED, and Z_eff were generated using a dedicated workstation (IntelliSpace Portal; Philips Healthcare). ED denotes the number of electrons per unit volume and is presented as a relative value to the ED of water in percent (%EDW) [23]. Z_eff indicates the effective atomic number when the compound consists of several elements and is replaced by one of the elements [24].

MRI protocols

All MRI scans were conducted using 3.0-T systems (Achieve dStream 3.0 T; Philips Healthcare, Best, the Netherlands and Prisma; Siemens, Erlangen, Germany). S1 Table summarizes the sagittal T2-weighted imaging protocols.

Image analysis

Two independent radiologists (17 and 8 years of experience in CT and MRI interpretation centered on neuroradiology) evaluated images from spectral CT and MRI. The readers were blinded to the clinical information of the patients and individually evaluated spectral CT and MRI data at 1-month intervals. They evaluated lumbar intervertebral disk degeneration according to the mPG [10]. For cases with discordant grades, the mPG was determined by the consensus of the two radiologists. Each intervertebral disk was further categorized as normal (mPG1 and 2) or degenerated (mPG3–8) [24–26].

Five ROIs (10 mm²) were drawn in each disk on the midsagittal plane, labeled as N1–N5 from anterior to posterior—N1 and N5 in AF and N2–N4 in NP (Fig 2).

ROIs were set on CT_conv images and then duplicated across ED and Z_eff images. The mean CT_conv, ED, and Z_eff were measured for each ROI using a dedicated workstation (IntelliSpace Portal; Philips Healthcare). Furthermore, differences between anterior AF and NP, i.e., Δ(N1 − N3) and between posterior AF and NP, i.e., Δ(N5 − N3) were obtained for all parameters.

Statistical analysis

The software packages Statistical Package for the Social Sciences version 28.0.1.0 (SPSS, Chicago, IL, USA) and MedCalc (ver. 22.013; Mariakerke, Belgium) were used for statistical analyses. Kolmogorov–Smirnov test was used to assess data normality. Inter-observer agreement was evaluated using the intraclass correlation coefficient (ICC) for parameters with normal distribution and the weighted kappa analysis for parameters with non-normal distribution, respectively (ICC and κ-values of.00–0.20, 0.21–0.40, 0.41–0.60, 0.61–0.80, and 0.81–1.00 indicate poor, fair, moderate, substantial, and almost perfect agreement, respectively).

The ROI measurements from the two readers were averaged for further analyses. The ROI mean values for N1 to N5, Δ(N1 − N3), and Δ(N5 − N3) of all parameters were correlated with mPG using the Spearman’s rank correlation coefficient (|ρ| of 0.00–0.19, 0.20–0.39, 0.40–0.59, 0.60–0.79, and 0.80–1.00 indicate very weak, weak, moderate, strong, and very strong correlations, respectively). The independent samples T-test and the Mann–Whitney U test were used for parameters with normal distribution and those with non-normal distribution, respectively, to compare all parameters between normal (mPG1 and 2) and degenerated disks (mPG3–8). The receiver operating characteristic curve analysis was used to assess its diagnostic ability in differentiating normal and degenerated disks on all parameters. The sensitivity, specificity, and accuracy for differentiating degenerated disks (mPG3–8) from normal disks (mPG1 and 2) were calculated using a threshold criterion that was identified by the largest Youden index [27]. The area under the receiver operating characteristic curve (AUC) values of all parameters for the five ROIs, Δ(N1 − N3), and Δ(N5 − N3) were compared using the DeLong method [28]. A P value of < 0.05 indicates a significant difference.

Results

Patient characteristics

The final population included 338 lumbar intervertebral disks of 100 patients (mean age, 58.5 ± 20.0 years; range, 10–89 years, 55 men and 45 women) (Table 1).

Table 1. Participant characteristics.

Characteristic	Value
Number of patients	100
Number of lumber intervertebral disks	338
L1/2	74
L2/3	73
L3/4	62
L4/5	56
L5/S1	73
Mean age (y)*	58.5 ± 20.0
Sex (men, women)	(55, 45)
Clinical diagnoses
Lumbar spinal canal stenosis	26
Lumbar vertebral fracture	12
Scoliosis	12
Spinal schwannoma	10
Lumbar disk herniation	9
Lumbar spondylolysis	4
Spinal dysraphism	4
Pyogenic spondylitis	3
Ossification of the yellow ligament	2
Perineural cyst	2
Spinal arteriovenous fistula	2
Spinal meningioma	2
Spinal vertebral metastasis	2
Synovial cyst	2
Adhesive arachnoiditis	1
Spinal cerebrospinal fluid leakage	1
Lumbar kyphosis	1
Spinal cavernous hemangioma	1
Spinal choroid plexus papilloma	1
Spinal meningocele	1
Spinal tuberculosis	1
Spondylitis	1

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Unless otherwise indicated, data are number of patients. *Age is presented as the mean ± standard deviation.

The mPG of lumbar intervertebral disks

The 338 lumbar intervertebral disks were classified following mPG with normal disks in 154 (mPG 1, n = 41; mPG 2, n = 113) and degenerated disks in 184 (mPG 3, n = 98; mPG 4, n = 68; mPG 5–7, n = 18; mPG 8, n = 0). Fig 3 shows representative T2-weighted MRI and spectral CT parametric images for each mPG.

Inter-observer agreements of mPG and spectral CT parameters

The inter-observer agreement for the mPG was substantial (κ = 0.80, 95% confidence interval [CI]: 0.76–0.84). The inter-observer agreement for the CT_conv was moderate (ICC = 0.56, 95% CI: 0.52–0.59), whereas those for ED and Z_eff were almost perfect (ICC = 0.86, 95% CI: 0.85–0.87), and substantial (ICC = 0.73, 95% CI: 0.71–0.75), respectively.

Correlation between spectral CT parameters and lumbar intervertebral disk degeneration

Fig 4 shows the states in mean CT_conv, ED, and Z_eff N1–5 associated with the mPGs of lumbar intervertebral disk degeneration.

Table 2 summarizes the correlations between spectral CT parameters and mPGs in AF (N1 and N5) and NP (N2–4) and their differences between AF and NP.

Table 2. Correlations between spectral CT parameters and mPG in AF, NP, and their differences.

ROIs	CT_conv		ED		Z_eff
ROIs	ρ	P value	ρ	P value	ρ	P value
N1	−0.33	<0.001	−0.36	<0.001	−0.08	0.151
N2	0.16	0.004	0.34	<0.001	−0.30	<0.001
N3	0.24	<0.001	0.45	<0.001	−0.38	<0.001
N4	0.16	0.003	0.31	<0.001	−0.29	<0.001
N5	−0.29	<0.001	−0.29	<0.001	−0.08	0.166
Δ(N1 − N3)	−0.52	<0.001	−0.71	<0.001	0.34	<0.001
Δ(N5 − N3)	−0.46	<0.001	−0.64	<0.001	0.25	<0.001

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AF: Annulus fibrosus; CT_conv: Conventional polyenergetic 120-kVp computed tomography; ED: Electron density; mPG: Modified pfirrmann grade; NP: Nucleus pulposus; Δ(N1 − N3): Difference between anterior AF and NP; Δ(N5 − N3): Difference between posterior AF and NP; ROIs: Regions of interest; Z_eff: Effective atomic number.

The mean CT_conv values in NP were positively very weakly or weakly correlated with mPG (ρ = 0.16–0.24, P < 0.001, or = 0.004), whereas those in AF were negatively weakly correlated with mPG (ρ = −0.33, and −0.29, each P < 0.001). The mean ED values in NP were positively weakly or moderately correlated with mPG (ρ = 0.31–0.45, each P < 0.001), whereas those in AF were negatively weakly correlated with mPG (ρ = −0.36, and −0.29, each P < 0.001). The mean Z_eff values in NP were negatively weakly correlated with mPG (ρ = −0.29 – −0.38, each P < 0.001), but we revealed no evidence of a correlation between the Z_eff values in AF and mPG (P = 0.151, and 0.166). Δ(N1 − N3) and Δ(N5 − N3) of CT_conv were negatively moderately correlated with mPG (ρ = −0.52, and −0.46, each P < 0.001), whereas those of ED were negatively strongly correlated with mPG (ρ = −0.71, and −0.64, each P < 0.001) and those of Z_eff were positively weakly correlated with mPG (ρ = 0.34, and 0.25, each P < 0.001).

Comparison of spectral CT parameters between normal and degenerated disks

Fig 5 shows comparisons of spectral CT parameters in NP and AF between normal and degenerated disks. The CT_conv and ED values in NP were higher in degenerated disks (82.55–84.20 HU, 107.79–108.05%EDW) than in normal disks (78.72–80.80 HU, 107.09–107.56%EDW) (P < 0.001–0.004), whereas Z_eff was lower in degenerated disks (7.31–7.35) than in normal disks (7.38–7.43) (each P < 0.001). S2 Table summarizes complete crosstabulation of spectral CT parameters between normal and degenerated intervertebral disks.

The CT_conv and ED values in AF were lower in degenerated disks (93.52 and 88.93 HU, 108.70 and 108.21%EDW) than in normal disks (102.52 and 97.08HU, 109.00 and 109.62%EDW) (each P < 0.001), whereas we found no evidence of a difference in Z_eff between normal and degenerated disks. Δ(N1 − N3) and Δ(N5 − N3) of CT_conv and ED were lower in degenerative disks (9.31 and 4.73 HU, 0.85 and 0.36%EDW) than in normal disks (23.81 and 18.36 HU, 2.52 and 1.90%EDW) (each P < 0.001), whereas those of Z_eff were higher in degenerated disks (−0.02 and 0.08) than in normal disks (−0.10 and 0.00) (each P < 0.001).

Diagnostic performances of spectral CT parameters in differentiating degenerated disks from normal disks

The AUC values of CT_conv for differentiating degenerated disks from normal disks were 0.73 and 0.68 in AF and 0.56–0.62 in NP, whereas 0.76 and 0.71 in AF and 0.64–0.72 in NP for ED, and 0.65–0.71 in NP for Z_eff, respectively (Table 3).

Table 3. Diagnostic performances of spectral CT parameters in AF, NP, and their differences in detecting degenerated disks.

		AUC values	Cutoff	Sensitivity (%)	Specificity (%)	Accuracy (%)
	N1	0.73 (0.68, 0.78)	≤97.9 HU	66.9 [123/184]	70.8 [109/154]	68.6 [232/338]
	N2	0.57 (0.52, 0.63)	>81.45 HU	61.4 [113/184]	53.3 [82/154]	57.7 [195/338]
	N3	0.62 (0.56, 0.67)	>80.35 HU	62.0 [114/184]	55.8 [86/154]	59.2 [200/338]
CT_conv	N4	0.56 (0.51, 0.62)	>93.55 HU	23.9 [44/184]	91.6 [141/154]	54.7 [185/338]
	N5	0.68 (0.63, 0.73)	≤89.4 HU	53.3 [98/184]	80.5 [124/154]	65.7 [222/338]
	Δ(N1 − N3)	0.81 (0.76, 0.85)	≤14.75 HU	69.6 [128/184]	76.0 [117/154]	72.5 [245/338]
	Δ(N5 − N3)	0.77 (0.72, 0.81)	≤12.7 HU	76.1 [140/184]	66.9 [103/154]	71.9 [243/338]
	N1	0.76 (0.71, 0.80)	≤109.35%EDW	80.4 [148/184]	64.3 [99/154]	73.1 [232/338]
	N2	0.65 (0.59, 0.70)	>107.85%EDW	58.7 [108/184]	66.2 [102/154]	62.1 [210/338]
	N3	0.72 (0.67, 0.76)	>107.75%EDW	56.0 [103/184]	79.2 [122/154]	66.6 [225/338]
ED	N4	0.64 (0.59, 0.69)	>107. 50%EDW	62.5 [115/184]	59.7 [92/154]	61.2 [207/338]
	N5	0.71 (0.66, 0.76)	≤109.1%EDW	81.0 [149/184]	49.4 [76/154]	66.6 [225/338]
	Δ(N1 − N3)	0.92 (0.88, 0.94)	≤1.8%EDW	85.3 [157/184]	83.8 [129/154]	84.6 [286/338]
	Δ(N5 − N3)	0.88 (0.84, 0.91)	≤1.05%EDW	85.9 [158/184]	76.6 [118/154]	81.7 [276/338]
	N1	0.53 (0.48, 0.59)	≤7.35	70.7 [130/184]	38.3 [59/154]	55.9 [189/338]
	N2	0.66 (0.61, 0.71)	≤7.38	75.5 [139/184]	52.0 [80/154]	64.8 [219/338]
	N3	0.71 (0.66, 0.75)	≤7.36	64.1 [118/184]	71.4 [110/154]	67.5 [228/338]
Z_eff	N4	0.65 (0.60, 0.70)	≤7.40	70.1 [129/184]	57.1 [88/154]	64.2 [217/338]
	N5	0.53 (0.47, 0.58)	≤7.27	21.7 [40/184]	89.6 [138/154]	52.7 [178/338]
	Δ(N1 − N3)	0.69 (0.64, 0.74)	>−0.03	52.7 [97/184]	77.9 [120/154]	64.2 [217/338]
	Δ(N5 − N3)	0.65 (0.60, 0.70)	>0.01	66.3 [122/184]	61.7 [95/154]	64.2 [217/338]

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Data in parentheses are 95% confident intervals and those in brackets are numbers of patients. AF: annulus fibrosus; AUC: area under the receiver operating characteristic curve; CT_conv: Conventional polyenergetic 120-kVp computed tomography value; ED: Electron density; %EDW: A relative value to the ED of water in percent; NP: Nucleus pulposus; Δ(N1 − N3): Difference between anterior AF and NP; Δ(N5 − N3): Difference between posterior AF and NP; Z_eff: Effective atomic number.

The AUC values for Δ(N1 − N3) and Δ(N5 − N3) were 0.81 and 0.77 for CT_conv, 0.92 and 0.88 for ED, and 0.69 and 0.65 for Z _eff, respectively (Table 3). The DeLong method revealed significantly higher AUC values of ED for Δ(N1 − N3) and Δ(N5 − N3) (0.92 and 0.88) than those of CT_conv (0.81 and 0.77) and Z_eff (0.69 and 0.65) (P < 0.001–0.007) (Figs 6 and S3).

S3 Table summarizes the results of the other comparisons.

Discussion

Low back pain is a symptom afflicting individuals globally, and one of the primary causes of low back pain is lumbar intervertebral disk degeneration. MRI is the predominant diagnostic tool for lumbar intervertebral disk degeneration, and the etiology of low back pain is multifaceted, making the identification of its cause difficult with only MRI. CT is useful for diagnosing other causes, but the use of CT for diagnosing lumbar intervertebral disk degeneration remains unknown. Our study revealed the potential usefulness of spectral CT parameters, particularly differences in ED value between the AF and the NP for evaluating lumbar intervertebral disk degeneration (AUC values of 0.92 and 0.88, each P < 0.001). These findings would contribute to the use of CT for assessing patients with low back pain, including those who cannot undergo MRI due to conditions, including long-term postural difficulty, cardiac pacemakers, or claustrophobia.

Mean ED values were positively weakly to moderately correlated with mPG in NP, whereas negatively weakly correlated with mPG in AF. ED differences between AF and NP demonstrated strong negative correlations with mPG and were significantly lower in degenerated disks than in normal disks. These indicate a sharp contrast on ED maps between AF and NP in normal disks, and this sharp contrast in normal disks diminishes in degenerated disks. The intervertebral disk consists of centrally located NP which consists of rich water contents, and peripherally located AF which is densely packed with fibrous components [4]. Intervertebral disk degeneration progression causes dehydration and acceleration of fibrosis in the NP, as well as cyst formation and tearing in the AF [5]. The ED value of water (100%EDW) is lower than that of fibrous tissue or connective tissue (approximately 110%EDW) [18,20,29]; thus, those pathologies would explain the increased ED in NP and decreased ED in AF in degenerated disks. Noteworthily, higher CT_conv and ED in AF were observed for mPG 5–8 compared to mPG 3 and 4 (Fig 4). It may indicate the presence of visually undetectable microscopic calcifications which generally increase with advancing grades of degeneration [30]. Previous studies have reported correlations between other spectral CT parameters, specifically VNC and collagen maps, and intervertebral disc degeneration. Shinohara et al. demonstrated that VNC values in NP showed a positive correlation with mPG (R² = 0.574, P < 0.05), whereas no significant correlation was observed between VNC values and mPG in the annulus fibrosus (AF) (R² = −0.015, P = 0.846) [10]. Pohlan et al reported that collagen map density in the anterior anulus fibrosus, but not in the nucleus pulposus, significantly declined with age (r = −0.09341, p = 0.0003), reflecting age-dependent reduction in collagen and proteoglycan content [15]. In this study, ED correlated with disc degeneration in both the NP and AF, and the difference in ED between these compartments showed a strong negative correlation with mPG. This contrasts with VNC, which correlated only with NP degeneration, and collagen maps, which reflected age-related changes only in the AF. Therefore, ED has the unique advantage of simultaneously assessing degenerative changes in both compartments of the intervertebral disc and may serve as a more comprehensive parameter for evaluating overall disc degeneration.

Our study revealed that ED was more closely correlated with mPG than CT_conv and Z_eff in almost all ROIs and the differences between AF and NP. Moreover, the AUC values of ED difference between AF and NP for disk degeneration detection were significantly higher than those of CT_conv and Z_eff. These indicate that ED is a more useful disk degeneration indicator than CT_conv and Z_eff. This may be due to the higher sensitivity of ED than the other two parameters to the above-mentioned pathological changes in degenerative disks. Additionally, noise suppression in ED images may partly explain the better detection of disk degeneration than the conventional polyenergetic CT images. Shinohara et al. reported that mean VNC values in the NP differed significantly between mPG grades (P < 0.05), except between grades 3 and 4 (P = 0.111), while mean VNC values in the AF showed no significant differences across mPG grades (P = 0.160–1.000) [10]. Regarding collagen maps, Bernatz et al. demonstrated an overall accuracy of 81% for visual assessment of disc degeneration [17]. While these spectral CT parameters, VNC and collagen maps, have proven useful in diagnosing disc degeneration, no studies to date, including the present investigation, have directly compared ED, VNC, and collagen maps in the context of disc degeneration. However, Jeong et al. directly compared ED, conventional CT, and VNC images for detecting lumbar disk herniation and reported that ED images achieved superior diagnostic performance due to lower coefficient of variation and higher normalized contrast ratio values [12]. This finding is consistent with our quantitative results demonstrating a stronger correlation between ED parameters and the degree of disk degeneration. Future studies should investigate whether comparative and integrated analyses of ED, VNC, and collagen mapping could further enhance diagnostic accuracy in the assessment of intervertebral disk degeneration

ED difference between anterior AF and NP demonstrated a stronger correlation with mPG and better performance in detecting disk degeneration than the ED difference between posterior AF and NP. These observations may be accounted for by the previously reported regional biochemical difference in AF that significantly decreased sulfated glycosaminoglycans concentration in anterior AF in an old-aged group with a higher Pfirrmann grade compared to the middle-aged group with a lower Pfirrmann grade, but no such difference was observed in the posterior AF [31].

The Z_eff value was negatively weakly correlated with mPG in NP but with no significant correlation with mPG in AF. The decrease in Z_eff in degenerated NP may be explained by loss of water, whose Z_eff value (approximately 7.68) is higher than that of fibrous tissue (approximately 7.30) [20,23,29]. Conversely, Z_eff was insensitive to AF degeneration. The lower performance of Z_eff in comparison with ED indicates the relatively limited usefulness of Z_eff in detecting disk degeneration.

Our study has some limitations. First, this was a single-center retrospective study involving patients with suspected spinal and spinal cord diseases, without healthy controls. The use of a single spectral CT platform (Philips Healthcare DLCT) may limit generalizability, and selection bias related to disease characteristics and severity cannot be excluded. Second, the gold standard for lumbar disk assessment in this study was mPG based on T2-weighted MRI, and we did not evaluate the histopathological change of disk degeneration. Third, inter-observer agreement for ROI measurements was moderate to substantial (mPG: weighted κ = 0.80; ED: ICC = 0.86; Z_eff: ICC = 0.73; CT_conv: ICC = 0.56), indicating suboptimal reproducibility. This may be attributed to manual ROI placement on single midsagittal images; volumetric measurements might improve reproducibility and accuracy. The lower agreement for CT_conv likely reflects inherent variability in conventional CT measurements rather than reader-related factors such as differences in radiological experience, as identical ROIs were used across all parameter maps. Fourth, the diagnostic performance of spectral CT did not reach the level of MRI, which remains the gold standard for disk degeneration assessment. Given the radiation exposure, our findings do not justify routine use of CT for disk degeneration assessment. At present, spectral CT may serve as an alternative imaging modality for patients with MRI contraindications (e.g., pacemakers, claustrophobia, metallic implants) or when simultaneous evaluation of other causes of low back pain is needed. Future multicenter prospective studies involving multiple spectral CT platforms from different vendors are warranted to validate inter-vendor reproducibility and establish the clinical utility of spectral CT parameters across diverse patient populations and technologies.

Conclusions

we revealed the use of spectral CT parameters, especially ED, in assessing lumbar intervertebral disk degeneration. Our results may expand the role of CT in screening the cause of low back pain, potentially guiding more effective treatment strategies.

Supporting information

S1 Table. The sagittal T2-weighted imaging protocols.

SENSE: Sensitivity encoding; GRAPPA: Generalized autocalibrating partially parallel acquisitions.

(DOCX)

pone.0357658.s001.docx^{(15.5KB, docx)}

S2 Table. Complete crosstabulation for Diagnostic performances of Spectral CT parameters in AF, NP, and their differences in detecting degenerated disks.

AF: Annulus fibrosus; AUC: Area under the receiver operating characteristic curve; CT_conv: Conventional polyenergetic 120-kVp computed tomography value; DBE: Difference between areas; ED: Electron density; NP: Nucleus pulposus; Δ(N1 − N3): Difference between anterior AF and NP; Δ(N5 − N3): Difference between posterior AF and NP; Z_eff: Effective atomic number.

(DOCX)

pone.0357658.s002.docx^{(26.6KB, docx)}

S3 Table. Comparisons of AUC for Δ(N1 − N3) and Δ(N5 − N3) of spectral CT parameters for detecting degenerated disks.

(DOCX)

pone.0357658.s003.docx^{(19KB, docx)}

S4 Data. Raw data underlying the results presented in this study.

(XLS)

pone.0357658.s004.xls^{(333KB, xls)}

S5 Checklist. The STARD reporting checklist.

(DOCX)

pone.0357658.s005.docx^{(34KB, docx)}

Acknowledgments

We thank Dr. Chihaya Koriyama, Department of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan, for statistical review and advice.

Data Availability

All relevant data are within the paper and its Supporting information files.

Funding Statement

This study was supported by grants from the Grants-in-Aid for Scientific Research (KAKENHI) from the Japan Society for the Promotion of Science (JSPS) [Grant Number 21K15830]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0357658.r001

Decision Letter 0

Aloysius Gonzaga Mubuuke

29 Oct 2025

Dear Dr. Yoshiura,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Partly

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2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: I Don't Know

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Reviewer #2: No

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Reviewer #2: Yes

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Reviewer #1: I have carefully reviewed the manuscript and find it to be well written and scientifically sound. The objective is clearly stated, achievable, and the findings contribute meaningfully to the growing body of knowledge in computed tomography (CT) science. The study also highlights novel potential applications of CT technology. However, a few issues require clarification or further elaboration:

1. CT Dose Justification:

Did the researcher consider patient radiation dose during CT examinations for intervertebral degeneration assessment? Please clarify whether the use of CT for this indication is justified in terms of benefit versus exposure.

2. Introduction Contextual Clarity:

The introduction mentions that DECT studies of intervertebral disk diseases have been reported in recent years. Although this statement is referenced, it would strengthen the background if specific examples of such disk diseases were mentioned. Additionally, the author should explain why effective atomic number (Zeff) and electron density (ED) images for lumbar intervertebral disk degeneration (LIDD) remain underexplored. Are there particular research or technical limitations contributing to this gap?

3. Methods Reader Experience:

Under the analysis section, there appears to be a considerable difference in professional experience between the two radiologists (8 years vs. 17 years). Please clarify whether both radiologists possess similar expertise in DECT interpretation and whether this variation could have influenced the image reading accuracy or overall results.

4. Generalisability:

The study appears to have been conducted at a single center. The authors should discuss how this limitation might affect the generalisability of the findings to other clinical settings or populations.

5. Clinical Applicability:

Based on the study outcomes, do the authors recommend adopting this DECT-based method for clinical assessment of intervertebral disk degeneration, or is further validation and research still warranted before routine clinical implementation?

Overall, this is a well-conceived and informative paper, and with the above clarifications, it could make a valuable contribution to the field.

Reviewer #2: The authors present a study on spectral CT for assessing lumbar disc degeneration, utilizing basic parameters such as electron density (ED) and effective atomic number (Zeff) to characterize the intervertebral disc. However, they overlook a comparison or discussion of previously reported techniques, such as VNCa and collagen mapping. The results and discussion sections are lengthy and lack organization. Additionally, the authors miss the opportunity to clearly articulate the hypothesis of their work in the introduction. Below are further specific points for consideration.

**Major Points:**

The introduction is overly broad and lacks specificity, reiterating established facts. I recommend streamlining it to focus on spectral CT and discussing why the authors believe electron density is a valuable target, especially since this approach has not been previously explored in depth.

The term "DECT" is inaccurate here, as the authors did not employ "two energies" but instead utilized a dual-layer detector. This terminology should be revised throughout the manuscript to reflect "spectral CT."

Furthermore, scoring and reliability data for MRI are absent.

The authors should consider transferring some data from tables to figures (e.g., table 3) for better clarity.

It is essential for the authors to complete a STARD checklist and provide the missing information, particularly the complete crosstabulation.

Lastly, the discussion lacks a comparison to existing literature.

**Minor Points:**

I have concerns regarding the correlation analysis; it would be prudent to have it reviewed by a professional statistician.

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PLoS One. 2026 Sep 1;21(9):e0357658. doi: 10.1371/journal.pone.0357658.r002

Author response to Decision Letter 1

26 Jan 2026

EDITOR’S COMMENTS:

[E# 1] The introduction section needs to be more focused to the research problem and the research question should be clearly implied within your introduction.

We thank the editor for this comment and have deleted some sentences to focus on spectral CT and research problem.

New sentence: Lumbar intervertebral disk degeneration is the most prevalent cause of low back pain [1, 2], and it causes herniated disk disease, lumbar degenerative spondylosis, and lumbar spinal canal stenosis [3].

The intervertebral disk is centrally and peripherally composed of the nucleus pulposus (NP) and the annulus fibrosus (AF), respectively. The AF consists of a fibrocartilaginous structure that primarily contains type I collagen, whereas the NP is rich in water and proteoglycans in a loose network of type II collagen [4]. Proteoglycans in disk degeneration, which function to bind water, decrease, thereby causing dehydration and relatively increased type I collagen within the NP, and tears and degenerate cysts of AF [5]. Lumbar intervertebral disk degeneration evaluation is conventionally performed using Magnetic resonance imaging (MRI) [1, 2, 5–7]. Pfirrmann grade and modified Pfirrmann grade (mPG) based on T2-weighted images are predominantly used for grading degenerative disk disease [6, 7]. Thus, MRI is useful for intervertebral disk degeneration evaluation. However, MRI is unavailable for patients with contraindicated metal implantation or claustrophobia. Moreover, MRI may not be an optimal tool for diagnosing other causative diseases of lower back pain than spinal diseases such as urinary tract stones, aortic dissection, etc. Computed tomography (CT) effectively evaluated these diseases, but its usefulness for lumbar intervertebral disk degeneration evaluation has not been established.

Spectral CT imaging encompasses a unique generation of CT systems that utilize energy-dependent information, with dual-energy CT (DECT) representing its first generation, which can be implemented through various technical approaches including dual-source CT, rapid kVp-switching, and dual-layer spectral detector CT (DLCT) [8]. DECT analyzes data of Compton scattering and the photoelectric effect of X–rays of two energies using various algorithms. DECT studies of intervertebral disk diseases have been reported in recent years, specifically including virtual non-calcium imaging for disk herniation and degeneration [9–13], water imaging for disk degeneration [14], collagen mapping for disk degeneration [15–17], and electron density (ED) imaging for disk herniation [12, 13]. ED and effective atomic number (Zeff) are recently available as DECT derived parameters [18]. DECT enable more accurate measurements of ED and Zeff through improved dose distribution accuracy, which were difficult to obtain with conventional single-energy CT [19]. While these measurements have been primarily investigated for improving dose calculation accuracy in radiation treatment planning [20], their utility in diagnostic imaging has remained underexplored. Recently, however, the diagnostic value of ED for evaluating disk herniation has been reported [12, 13]. To the best of our knowledge, the use of ED and Zeff images for lumbar intervertebral disk degeneration evaluation remains unknown. Therefore, this study aimed to investigate whether spectral CT-derived ED and Zeff can accurately differentiate varying degrees of lumbar disk degeneration. (P3, line4- P4, line12).

[E# 2]Second, you need to discuss the limitations around generalizability of your findings.

We thank the editor for this comment and added the following sentences as a limitation in Discussion according to Editor’s suggestion.

New sentence: First, this was a single-center retrospective study involving patients with suspected spinal and spinal cord diseases, without healthy controls. The use of a single spectral CT platform (Philips Healthcare DLCT) may limit generalizability, and selection bias related to disease characteristics and severity cannot be excluded. (P21,line13-15).

REVIEWER’S COMMENTS

Reviewer# 1

I have carefully reviewed the manuscript and find it to be well written and scientifically sound. The objective is clearly stated, achievable, and the findings contribute meaningfully to the growing body of knowledge in computed tomography (CT) science. The study also highlights novel potential applications of CT technology. However, a few issues require clarification or further elaboration:

[R# 1-1] 1. CT Dose Justification:

We thank the reviewer for this comment and added the following sentences as a limitation in Discussion according to reviewer’s suggestion.

New sentence: Fourth, the diagnostic performance of spectral CT did not reach the level of MRI, which remains the gold standard for disk degeneration assessment. Given the radiation exposure, our findings do not justify routine use of CT for disk degeneration assessment. At present, spectral CT may serve as an alternative imaging modality for patients with MRI contraindications (e.g., pacemakers, claustrophobia, metallic implants) or when simultaneous evaluation of other causes of low back pain is needed. Future multicenter prospective studies involving multiple spectral CT platforms from different vendors are warranted to validate inter-vendor reproducibility and establish the clinical utility of spectral CT parameters across diverse patient populations and technologies. (P22, line4-10).

[R# 1-2] 2. Introduction Contextual Clarity:

We thank the reviewer for this comment and added the following sentences in Introduction according to reviewer’s suggestion.

New sentence: DECT studies of intervertebral disk diseases have been reported in recent years, specifically including virtual non-calcium imaging for disk herniation and degeneration [9–13], water imaging for disk degeneration [14], collagen mapping for disk degeneration [15–17], and electron density (ED) imaging for disk herniation [12, 13]. ED and effective atomic number (Zeff) are recently available as DECT derived parameters [18]. DECT enable more accurate measurements of ED and Zeff through improved dose distribution accuracy, which were difficult to obtain with conventional single-energy CT [19]. While these measurements have been primarily investigated for improving dose calculation accuracy in radiation treatment planning [20], their utility in diagnostic imaging has remained underexplored. Recently, however, the diagnostic value of ED for evaluating disk herniation has been reported [12, 13] (P4, line4-10).

[R# 1-3]3. Methods Reader Experience:

We thank the reviewer for this comment and added the following sentences as a limitation in Discussion according to reviewer’s suggestion.

New sentence: Third, inter-observer agreement for ROI measurements was moderate to substantial (mPG: weighted κ = 0.80; ED: ICC = 0.86; Zeff: ICC = 0.73; CTconv: ICC = 0.56), indicating suboptimal reproducibility. This may be attributed to manual ROI placement on single midsagittal images; volumetric measurements might improve reproducibility and accuracy. The lower agreement for CTconv likely reflects inherent variability in conventional CT measurements rather than reader-related factors such as differences in radiological experience, as identical ROIs were used across all parameter maps. (P21, line16-P22, line4).

[R# 1-4]4. Generalisability:

We thank the reviewer for this comment and added the following sentences as a limitation in Discussion according to reviewer’s suggestion.

[R# 1-5]5. Clinical Applicability:

Overall, this is a well-conceived and informative paper, and with the above clarifications, it could make a valuable contribution to the field.

We thank the reviewer for this comment and added the following sentences as a limitation in Discussion according to reviewer’s suggestion.

Reviewer #2:

The authors present a study on spectral CT for assessing lumbar disc degeneration, utilizing basic parameters such as electron density (ED) and effective atomic number (Zeff) to characterize the intervertebral disc. However, they overlook a comparison or discussion of previously reported techniques, such as VNCa and collagen mapping. The results and discussion sections are lengthy and lack organization. Additionally, the authors miss the opportunity to clearly articulate the hypothesis of their work in the introduction. Below are further specific points for consideration.

**Major Points:**

[R#2-1] The introduction is overly broad and lacks specificity, reiterating established facts. I recommend streamlining it to focus on spectral CT and discussing why the authors believe electron density is a valuable target, especially since this approach has not been previously explored in depth.

We thank the reviewer for this comment and have deleted some sentences to focus on spectral CT and research problem.

The intervertebral disk is centrally and peripherally composed of the nucleus pulposus (NP) and the annulus fibrosus (AF), respectively. The AF consists of a fibrocartilaginous structure that primarily contains type I collagen, whereas the NP is rich in water and proteoglycans in a loose network of type II collagen [4]. Proteoglycans in disk degeneration, which function to bind water, decrease, thereby causing dehydration and relatively increased type I collagen within the NP, and tears and degenerate cysts of AF [5]. Lumbar intervertebral disk degeneration evaluation is conventionally performed using Magnetic resonance imaging (MRI) [1, 2, 5–7]. Pfirrmann grade and modified Pfirrmann grade (mPG) based on T2-weighted images are predominantly used for grading degenerative disk disease [6, 7]. Thus, MRI is useful for intervertebral disk degeneration evaluation. However, MRI is unavailable for patients with contraindicated metal implantation or claustrophobia. Moreover, MRI may not be an optimal tool for diagnosing other causative diseases of lower back pain than spinal diseases such as urinary tract stones, aortic dissection, etc. Computed tomography (CT) effectively evaluated these diseases, but its usefulness for lumbar intervertebral disk degeneration evaluation has not been established.

Spectral CT imaging encompasses a unique generation of CT systems that utilize energy-dependent information, with dual-energy CT (DECT) representing its first generation, which can be implemented through various technical approaches including dual-source CT, rapid kVp-switching, and dual-layer spectral detector CT (DLCT) [8]. DECT analyzes data of Compton scattering and the photoelectric effect of X–rays of two energies using various algorithms. DECT studies of intervertebral disk diseases have been reported in recent years, specifically including virtual non-calcium imaging for disk herniation and degeneration [9–13], water imaging for disk degeneration [14], collagen mapping for disk degeneration [15–17], and electron density (ED) imaging for disk herniation [12, 13]. ED and effective atomic number (Zeff) are recently available as DECT derived parameters [18]. DECT enable more accurate measurements of ED and Zeff through improved dose distribution accuracy, which were difficult to obtain with conventional single-energy CT [19]. While these measurements have been primarily investigated for improving dose calculation accuracy in radiation treatment planning [20], their utility in diagnostic imaging has remained underexplored. Recently, however, the diagnostic value of ED for evaluating disk herniation has been reported [12, 13]. To the best of our knowledge, the use of ED and Zeff images for lumbar intervertebral disk degeneration evaluation remains unknown. Therefore, this study aimed to investigate whether spectral CT-derived ED and Zeff can accurately differentiate varying degrees of lumbar disk degeneration. (P3, line4- P4, line12).

[R#2-2] The term "DECT" is inaccurate here, as the authors did not employ "two energies" but4, lineead utilized a dual-layer detector. This terminology should be revised throughout the manuscript to reflect "spectral CT."

We thank the reviewer for this comment. We have clarified the relationship between spectral CT, DECT, and DLCT in the Introduction and replaced "DECT" with "spectral CT" where appropriate throughout the manuscript.

New sentence: Spectral CT imaging encompasses a unique generation of CT systems that utilize energy-dependent information, with dual-energy CT (DECT) representing its first generation, which can be implemented through various technical approaches including dual-source CT, rapid kVp-switching, and dual-layer spectral detector CT (DLCT) [8]. (P4, line1-3).

[R#2-3] Furthermore, scoring and reliability data for MRI are absent.

We thank the reviewer for this comment. We have added the inter-observer agreement results for mPG (MRI-based disc degeneration grading) to the "Inter-observer agreements of mPG and spectral CT parameters" section in the Results.

New sentence: The inter-observer agreement for the mPG was substantial (κ = 0.80, 95% confidence interval [CI]：0.76-0.84). (P12, line2).

[R#2-4] The authors should consider transferring some data from tables to figures (e.g., table 3) for better clarity.

We thank the reviewer for this comment. We have changed Table 3 to Figure 5 as suggested. (P15, line9-13)

[R#2-5] It is essential for the authors to complete a STARD checklist and pr

Attachment

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PLoS One. doi: 10.1371/journal.pone.0357658.r003

Decision Letter 1

Ali Fathi Jouzdani

20 Aug 2026

Spectral CT electron density for evaluation of lumbar intervertebral disk degeneration

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PLoS One. doi: 10.1371/journal.pone.0357658.r004

Acceptance letter

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Supplementary Materials

S1 Table. The sagittal T2-weighted imaging protocols.

SENSE: Sensitivity encoding; GRAPPA: Generalized autocalibrating partially parallel acquisitions.

(DOCX)

pone.0357658.s001.docx^{(15.5KB, docx)}

S2 Table. Complete crosstabulation for Diagnostic performances of Spectral CT parameters in AF, NP, and their differences in detecting degenerated disks.

(DOCX)

pone.0357658.s002.docx^{(26.6KB, docx)}

S3 Table. Comparisons of AUC for Δ(N1 − N3) and Δ(N5 − N3) of spectral CT parameters for detecting degenerated disks.

(DOCX)

pone.0357658.s003.docx^{(19KB, docx)}

S4 Data. Raw data underlying the results presented in this study.

(XLS)

pone.0357658.s004.xls^{(333KB, xls)}

S5 Checklist. The STARD reporting checklist.

(DOCX)

pone.0357658.s005.docx^{(34KB, docx)}

Attachment

Submitted filename: Response to Reviewers.doc

pone.0357658.s007.doc^{(80.5KB, doc)}

Data Availability Statement

All relevant data are within the paper and its Supporting information files.

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PERMALINK

Spectral CT electron density for evaluation of lumbar intervertebral disk degeneration

Masanori Nakajo

Tsubasa Nakano

Tomohito Hasegawa

Kiyohisa Kamimura

Koji Takumi

Hiroaki Nagano

Masatoyo Nakajo

Hiroyuki Tominaga

Mutsukazu Hayashi

Takashi Iwanaga

Fumiko Kanzaki

Eran Langzam

Graeme Campbell

Ko Higuchi

Takashi Yoshiura

Roles

Abstract

Objective

Summary of background data

Methods

Results

Conclusion

Introduction

Materials and methods

Patient population

Fig 1. Inclusion flowchart of study participants and lumbar intervertebral disks.

Spectral CT imaging protocols

MRI protocols

Image analysis

Fig 2. ROIs in each spectral CT image.

Statistical analysis

Results

Patient characteristics

Table 1. Participant characteristics.

The mPG of lumbar intervertebral disks

Fig 3. The mPG classification of 338 lumbar intervertebral disks.

Inter-observer agreements of mPG and spectral CT parameters

Correlation between spectral CT parameters and lumbar intervertebral disk degeneration

Fig 4. Box plots of mean CTconv, ED, and Zeff values in 5 ROIs following the mPG.

Table 2. Correlations between spectral CT parameters and mPG in AF, NP, and their differences.

Comparison of spectral CT parameters between normal and degenerated disks

Fig 5. Comparisons of spectral CT parameters in AF, NP, and their differences between normal and degenerated disks.

Diagnostic performances of spectral CT parameters in differentiating degenerated disks from normal disks

Table 3. Diagnostic performances of spectral CT parameters in AF, NP, and their differences in detecting degenerated disks.

Fig 6. Receiver operating characteristic curves for differences of the CTconv, ED, and Zeff on Δ(N1 − N3) and Δ(N5 − N3) for detecting degenerated disks.

Discussion

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Aloysius Gonzaga Mubuuke

Roles

Author response to Decision Letter 1

Decision Letter 1

Ali Fathi Jouzdani

Roles

Acceptance letter

Ali Fathi Jouzdani

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Fig 4. Box plots of mean CT_conv, ED, and Z_eff values in 5 ROIs following the mPG.

Fig 6. Receiver operating characteristic curves for differences of the CT_conv, ED, and Z_eff on Δ(N1 − N3) and Δ(N5 − N3) for detecting degenerated disks.